<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="data-paper" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.122759.1</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Data Note</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>AFHIRIS: African Human Iris Dataset (Version 1)</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 1 approved, 1 approved with reservations]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Akande</surname>
                        <given-names>Oluwatobi</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-6846-5360</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Ojimba</surname>
                        <given-names>Nzube</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Oghenekaro</surname>
                        <given-names>Atele</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Abikoye</surname>
                        <given-names>Oluwakemi</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-8912-6333</uri>
                    <xref ref-type="aff" rid="a4">4</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Ogundokun</surname>
                        <given-names>Roseline</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-2592-2824</uri>
                    <xref ref-type="corresp" rid="c2">b</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a5">5</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Akindele</surname>
                        <given-names>Akinyinka</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Department of Computer Science, Landmark University, Omu Aran, Kwara State, 251101, Nigeria</aff>
                <aff id="a2">
                    <label>2</label>Computer Science Department, Ladoke Akintola University of Technology Open and Distance Learning Center, Ogbomoso, Oyo, Nigeria</aff>
                <aff id="a3">
                    <label>3</label>Computer Science Department, Baze University, Abuja, Nigeria</aff>
                <aff id="a4">
                    <label>4</label>Computer Science Department, University of Ilorin, Ilorin, Ilorin, Kwara State, 240003, Nigeria</aff>
                <aff id="a5">
                    <label>5</label>Department of Multimedia Engineering, Kaunas University of Technology, Kaunas, 44249, Lithuania</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:akande.noah@lmu.edu.ng">akande.noah@lmu.edu.ng</email>
                </corresp>
                <corresp id="c2">
                    <label>b</label>
                    <email xlink:href="mailto:ogundokun.roseline@lmu.edu.ng">ogundokun.roseline@lmu.edu.ng</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>21</day>
                <month>12</month>
                <year>2022</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2022</year>
            </pub-date>
            <volume>11</volume>
            <elocation-id>1549</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>26</day>
                    <month>10</month>
                    <year>2022</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2022 Akande O et al.</copyright-statement>
                <copyright-year>2022</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/11-1549/pdf"/>
            <abstract>
                <p>Biometric systems remain the most widely used methods for identification and authentication purposes. Their wide acceptability has opened up more research into new application areas of biometric systems. However, biometric research requires an appropriate biometric dataset to validate the proposed technique. This dataset could be privately owned or publicly available for research purposes. In the field of iris biometric research, the iris dataset produced by the Chinese Academy of Sciences (CASIA) is the first, most popular, and widely used publicly available iris dataset. However, the increasing popularity and acceptability of human iris-related research have called for additional benchmarks, and therefore, new publicly available databases of human iris images. Existing publicly available human iris datasets have been collected from non-African subjects; therefore, this dataset is the first publicly available human iris dataset of African descent. Three categories of images were collected from 1028 volunteers that participated in the data collection task. The first category was made up of four iris images that were captured when the volunteers used spectacles, while the second category includes four iris images that were captured when the volunteers wore no spectacles. However, the third category of iris images was obtained from eight volunteers that used print-patterned contact lenses. Only four images were captured from volunteers in this category as they were not asked to put on spectacles. In addition to the iris images captured, soft biometric features such as age, gender, state of origin, weight, and height of the volunteers were also captured. It is strongly believed that this unique collection of iris datasets of African descent will open up new research in the study of the human iris.</p>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>African Human Iris images</kwd>
                <kwd>Age Prediction</kwd>
                <kwd>Ethnicity Prediction</kwd>
                <kwd>Gender Prediction</kwd>
                <kwd>Biometrics</kwd>
                <kwd>Personal Recognition</kwd>
            </kwd-group>
            <funding-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec id="sec1" sec-type="intro">
            <title>Introduction</title>
            <p>The iris recognition system is one of the most widely used and acceptable means of personal recognition and authentication. It has recently become an official means of national identification in India. The Unique Identification Authority of India (UIDAI) has successfully captured 1.5 billion irises from Indian citizens for identification and recognition purposes.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> Many countries have done the same and this increasing popularity and acceptability of human iris as a means of national identification and recognition has called for additional benchmarks, and therefore, new publicly available databases of human iris images.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> Though several human iris datasets exist,
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> iris datasets of African descents are presently not publicly available. This research effort aimed at bridging this gap in the African continent by embarking on the capture and subsequent creation of human iris images of people of African descent to make them publicly available for research purposes. In the words of Prof. John Daugman:</p>
            <p>&#x201c;There is a more urgent need for an African FACE image database because researchers into face recognition have famously (or infamously) used primarily non-African face images, leading to high levels of bias in algorithms, and disastrous classification performance when they are tested on African face images&#x201d;.</p>
            <p>Therefore, the authors believe the human iris dataset presented in this data article
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> will be of great value to researchers willing to advance iris-related research across the African continent. The following are some of the uniqueness of the iris dataset described in this article:
                <list list-type="bullet">
                    <list-item>
                        <label>&#x2022;</label>
                        <p>The dataset presented in this Data Note is the first publicly available human iris dataset of African descent.</p>
                    </list-item>
                    <list-item>
                        <label>&#x2022;</label>
                        <p>In addition to the iris images, the dataset provides soft biometric features about each volunteer. This additional information will open up new multi-modal biometric research.</p>
                    </list-item>
                    <list-item>
                        <label>&#x2022;</label>
                        <p>The dataset can serve as a benchmark for evaluating iris recognition methods and other human iris-related research.</p>
                    </list-item>
                    <list-item>
                        <label>&#x2022;</label>
                        <p>The dataset can be used to validate results obtained from existing iris-related research that used non-African iris images for their research validation.</p>
                    </list-item>
                    <list-item>
                        <label>&#x2022;</label>
                        <p>The dataset can be used to enhance studies such as personal recognition, age, gender, or ethnicity prediction as well as iris color pigment research on the African continent.</p>
                    </list-item>
                </list>
            </p>
        </sec>
        <sec id="sec2" sec-type="methods">
            <title>Methods</title>
            <sec id="sec3">
                <title>Ethical considerations</title>
                <p>Approvals were obtained from the Ethical and Review Committee of participating Universities before the commencement of the data collection exercise. This was done to ensure and guarantee that the data collection task would not hurt the health of the volunteers and that the publication of the data collected would not infringe on their privacy in any way. Also, all volunteers (willingly without any form of cohesion or pressure) agreed to participate in the iris data collection task with the awareness that the collected data would be made publicly available for research purposes. The privacy of the volunteers was respected as personal details that could make the data traceable to them were not collected.</p>
                <p>A Vista EY2H dual iris camera was employed for the iris image capture. The iris camera is a RoHS compliant device that uses a cutting-edge, high-resolution CMOS sensor to produce ISO/IEC 19794-6-compliant images of both irises simultaneously. The camera uses a multi-wavelength near-infrared band of light (NIR: 700nm - 900nm) illumination for superior iris images in all environments. The capturing process meets international eye safety requirements and also has a live eye anti-Spoof detection feature that can be used to reliably detect when a subject is alive. At a click of the capture button, a large 2560 by 720-pixel iris image was produced from the camera; this image is automatically separated into four images with a dimension of 640 by 480 pixels. These are the left and right iris images with the iris region localized, and another set of left and right iris images without the iris section localized. An overview of the camera is provided in 
                    <xref ref-type="fig" rid="f1">Figures 1a-c:</xref>
                </p>
                <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                    <label>Figure 1. </label>
                    <caption>
                        <title>(a). The Camera&#x2019;s Front View. (b). The Camera&#x2019;s Back View. (c). The Camera&#x2019;s Side View.</title>
                    </caption>
                    <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure1.gif"/>
                </fig>
                <p>Images have been reproduced from Vista Imaging
                    <sup>
                        <xref ref-type="bibr" rid="ref8">8</xref>
                    </sup> with the appropriate permissions.</p>
                <p>Digital Weighing scale: a digital weighing scale as shown in 
                    <xref ref-type="fig" rid="f2">Fig. 2</xref> was employed to measure the weight (soft biometric data) of volunteers.</p>
                <fig fig-type="figure" id="f2" orientation="portrait" position="float">
                    <label>Figure 2. </label>
                    <caption>
                        <title>Digital Weighing Scale.</title>
                        <p>Image reproduced from 
                            <ext-link ext-link-type="uri" xlink:href="http://www.jumia.com.ng">www.jumia.com.ng</ext-link> with the appropriate permissions.</p>
                    </caption>
                    <graphic id="gr2" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure2.gif"/>
                </fig>
                <p>
                    <bold>Digital Height Measurement Scale</bold>: a height measurement scale as shown in 
                    <xref ref-type="fig" rid="f3">Fig. 3</xref> was employed to measure the height of the volunteers.</p>
                <fig fig-type="figure" id="f3" orientation="portrait" position="float">
                    <label>Figure 3. </label>
                    <caption>
                        <title>Digital Height Measuring Scale.</title>
                        <p>Image reproduced from 
                            <ext-link ext-link-type="uri" xlink:href="http://www.jumia.com.ng">www.jumia.com.ng</ext-link> with the appropriate permissions.</p>
                    </caption>
                    <graphic id="gr3" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure3.gif"/>
                </fig>
            </sec>
            <sec id="sec4">
                <title>Data collection set up</title>
                <p>Three standard approaches are generally employed for iris image capturing. They are self-enrollment; handheld, self-enrollment (fixed on a tripod); and operator-assisted enrolment. For fast and accurate data capture, the operator-assisted enrolment method was used. The capture device was fixed on a tripod and volunteers were only asked to place their forehead horizontally with their eyes gazing at the lens of the camera. When a perfect range of the irises had been set, the operator clicked the capture button on the camera to initiate the capture process. The captured images were automatically saved on the investigator&#x2019;s personal computer connected to the scanning device. Afterward, soft biometric features such as: volunteer&#x2019;s height, weight, age, gender, and state of origin were collected with the respective measuring devices. The data collection sheet shown in 
                    <xref ref-type="fig" rid="f4">Figure 4</xref> was used to initially document the data collected</p>
                <fig fig-type="figure" id="f4" orientation="portrait" position="float">
                    <label>Figure 4. </label>
                    <caption>
                        <title>Data Collection Sheet.</title>
                    </caption>
                    <graphic id="gr4" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure4.gif"/>
                </fig>
            </sec>
            <sec id="sec5">
                <title>Dataset presentation</title>
                <p>Detailed information about the iris data collected is presented in this section.</p>
            </sec>
            <sec id="sec6">
                <title>Data description</title>
                <p>The human iris images presented in this data article are publicly available on 
                    <ext-link ext-link-type="uri" xlink:href="https://data.mendeley.com/datasets/r3ypmmp2gs/1">Mendeley Data</ext-link>. The dataset contains 8192 human iris images obtained from 1028 volunteers who were students and members of staff in two Nigerian Universities. The human iris images were captured using a handheld VistaEY2H dual iris camera. The first category of images was captured when the volunteers wore spectacles while the second category of images was captured when the volunteers wore no spectacles. The third category contains iris images captured from volunteers that used print-patterned contact lenses. Moreover, the capture device automatically took four images for each category. All images were saved in .bmp image format. In addition, soft biometrics such as height, weight, age, gender, and state of origin were also collected.</p>
                <p>(a)&#x2003;
                    <bold>First category of images collected</bold>
                </p>
                <p>The VistaEY2H dual iris camera used for the automatic capture produced four images per volunteer at each capturing instance. These are the right and left iris images of each volunteer as shown in 
                    <xref ref-type="fig" rid="f5">Figure 5</xref>, the right and left iris images of each volunteer with the iris region automatically localized; this is shown in 
                    <xref ref-type="fig" rid="f6">Figure 6</xref>, the right iris image of the volunteer as shown in 
                    <xref ref-type="fig" rid="f7">Figure 7</xref> and left iris image of the individual as shown in 
                    <xref ref-type="fig" rid="f8">Figure 8</xref>.</p>
                <fig fig-type="figure" id="f5" orientation="portrait" position="float">
                    <label>Figure 5. </label>
                    <caption>
                        <title>Right and left irises of volunteer A without spectacles.</title>
                    </caption>
                    <graphic id="gr5" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure5.gif"/>
                </fig>
                <fig fig-type="figure" id="f6" orientation="portrait" position="float">
                    <label>Figure 6. </label>
                    <caption>
                        <title>Localized right and left irises of volunteer A without spectacles.</title>
                    </caption>
                    <graphic id="gr6" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure6.gif"/>
                </fig>
                <fig fig-type="figure" id="f7" orientation="portrait" position="float">
                    <label>Figure 7. </label>
                    <caption>
                        <title>Right iris image of volunteer A.</title>
                    </caption>
                    <graphic id="gr7" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure7.gif"/>
                </fig>
                <fig fig-type="figure" id="f8" orientation="portrait" position="float">
                    <label>Figure 8. </label>
                    <caption>
                        <title>Left iris image of volunteer A.</title>
                    </caption>
                    <graphic id="gr8" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure8.gif"/>
                </fig>
                <p>(b)&#x2003;
                    <bold>Second category of images collected</bold>
                </p>
                <p>The second category of images was collected from volunteers that wore spectacles. The images generated were the right and left iris images of each volunteer (as shown in 
                    <xref ref-type="fig" rid="f9">Figure 9</xref>), the right and left iris images of each volunteer with the iris region automatically localized (this is shown in 
                    <xref ref-type="fig" rid="f10">Figure 10</xref>), right iris image of the volunteer as shown in 
                    <xref ref-type="fig" rid="f11">Figure 11</xref> and left iris image of the volunteer as shown in 
                    <xref ref-type="fig" rid="f12">Figure 12</xref>.</p>
                <fig fig-type="figure" id="f9" orientation="portrait" position="float">
                    <label>Figure 9. </label>
                    <caption>
                        <title>Right and left irises of volunteer A with spectacles.</title>
                    </caption>
                    <graphic id="gr9" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure9.gif"/>
                </fig>
                <fig fig-type="figure" id="f10" orientation="portrait" position="float">
                    <label>Figure 10. </label>
                    <caption>
                        <title>Localized right and left irises of Volunteer A with spectacles.</title>
                    </caption>
                    <graphic id="gr10" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure10.gif"/>
                </fig>
                <fig fig-type="figure" id="f11" orientation="portrait" position="float">
                    <label>Figure 11. </label>
                    <caption>
                        <title>Right iris image of volunteer A.</title>
                    </caption>
                    <graphic id="gr11" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure11.gif"/>
                </fig>
                <fig fig-type="figure" id="f12" orientation="portrait" position="float">
                    <label>Figure 12. </label>
                    <caption>
                        <title>Left iris image of volunteer A.</title>
                    </caption>
                    <graphic id="gr12" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure12.gif"/>
                </fig>
                <p>(c)&#x2003;
                    <bold>Third category of images collected</bold>
                </p>
                <p>The third category was captured from volunteers that used print-patterned contact lenses. Only four images were captured from volunteers in this category as they were not asked to put on spectacles. However, the use of print-patterned contact lenses was not popular among the population considered, therefore, only eight volunteers used lenses. Examples of these images are provided in 
                    <xref ref-type="fig" rid="f13">Figures 13-16</xref>.</p>
                <fig fig-type="figure" id="f13" orientation="portrait" position="float">
                    <label>Figure 13. </label>
                    <caption>
                        <title>Right and left irises of volunteer B with lenses.</title>
                    </caption>
                    <graphic id="gr13" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure13.gif"/>
                </fig>
                <fig fig-type="figure" id="f14" orientation="portrait" position="float">
                    <label>Figure 14. </label>
                    <caption>
                        <title>Localized right and left irises of volunteer B with lenses.</title>
                    </caption>
                    <graphic id="gr14" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure14.gif"/>
                </fig>
                <fig fig-type="figure" id="f15" orientation="portrait" position="float">
                    <label>Figure 15. </label>
                    <caption>
                        <title>Right iris image of volunteer B.</title>
                    </caption>
                    <graphic id="gr15" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure15.gif"/>
                </fig>
                <fig fig-type="figure" id="f16" orientation="portrait" position="float">
                    <label>Figure 16. </label>
                    <caption>
                        <title>Left iris image of volunteer B.</title>
                    </caption>
                    <graphic id="gr16" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure16.gif"/>
                </fig>
                <p>(d)&#x2003;
                    <bold>Soft biometric features</bold>
                </p>
                <p>Soft biometric features of each volunteer were also recorded. These are the age, gender, height, weight, and State of origin of volunteers. For instance, the soft biometric features for volunteer B are shown in 
                    <xref ref-type="table" rid="T1">Table 1</xref>:</p>
                <table-wrap id="T1" orientation="portrait" position="float">
                    <label>Table 1. </label>
                    <caption>
                        <title>Soft Biometric Feature.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Soft biometric feature</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Value</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Age</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">19</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Gender</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Male</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Height (cm)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">182</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Weight (kg)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">100.7</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">State of origin</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">OYO</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec7">
                <title>Supplementary data files</title>
                <p>To easily distinguish the images, the capturing device automatically generated a unique identification number for each image. For instance, the corresponding unique identification number for each image captured from volunteers A and B are presented in 
                    <xref ref-type="table" rid="T2">Table 2</xref>:</p>
                <table-wrap id="T2" orientation="portrait" position="float">
                    <label>Table 2. </label>
                    <caption>
                        <title>Naming Nomenclature for the Images.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Sample number</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Figures</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Unique identification number</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">1.</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <xref ref-type="fig" rid="f1">Figure 1</xref>: Right and left irises of volunteer A</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Iris_20210429_110713_Dual</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">2.</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <xref ref-type="fig" rid="f2">Figure 2</xref>: Localized right and left irises of volunteer A</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Iris_20210429_110713_Diag</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">3.</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <xref ref-type="fig" rid="f3">Figure 3</xref>: Right iris image of volunteer A</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Iris_20210429_110713_Right</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">4.</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <xref ref-type="fig" rid="f4">Figure 4</xref>: Left iris image of volunteer A</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Iris_20210429_110713_Left</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">5.</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <xref ref-type="fig" rid="f5">Figure 5</xref>: Right and left irises of volunteer A with spectacles</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Iris_20210429_110730_Dual</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">6.</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <xref ref-type="fig" rid="f6">Figure 6</xref>: Right and Left Irises of Volunteer A with Spectacles and Localized iris region</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Iris_20210429_110730_Diag</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">7.</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <xref ref-type="fig" rid="f7">Figure 7</xref>: Right iris image of volunteer A</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Iris_20210429_110730_Right</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">8.</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <xref ref-type="fig" rid="f8">Figure 8</xref>: Left iris image of volunteer A</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Iris_20210429_110730_Left</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <p>The supplementary file in Excel format contains the detailed unique identification number for each iris image as well as the biometric features for each volunteer. cell A of the supplementary file is the serial number of the image, cell B contains the last six digits of the unique identification number of a volunteer without spectacles, and cell C contains the last six digits of the unique identification number of the same volunteer with spectacles while cells D to H contain the soft biometric traits of the same volunteer.</p>
            </sec>
            <sec id="sec8">
                <title>Statistics of volunteers</title>
                <p>A total number of 1028 volunteers participated in the iris image capturing task. The gender of volunteers is provided in 
                    <xref ref-type="fig" rid="f17">Figure 17</xref>. The age range of the volunteers are provided in 
                    <xref ref-type="fig" rid="f18">Figure 18</xref>.</p>
                <fig fig-type="figure" id="f17" orientation="portrait" position="float">
                    <label>Figure 17. </label>
                    <caption>
                        <title>Gender of volunteers.</title>
                    </caption>
                    <graphic id="gr17" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure17.gif"/>
                </fig>
                <fig fig-type="figure" id="f18" orientation="portrait" position="float">
                    <label>Figure 18. </label>
                    <caption>
                        <title>Age range of volunteers.</title>
                    </caption>
                    <graphic id="gr18" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/134790/e72b40af-c257-4cd2-97af-2d6416e8eb14_figure18.gif"/>
                </fig>
            </sec>
        </sec>
        <sec id="sec9" sec-type="conclusions">
            <title>Conclusions</title>
            <p>This data article has extensively described the experimental setup behind 1056 human iris datasets of African descent collected to enhance iris-related research in the African continent and beyond. It is believed that the collection could serve as a benchmark for evaluating existing and new iris recognition techniques. Most importantly, the dataset could be used to validate results obtained from existing iris-related research that used non-African iris images for their research validation. The authors look forward to creating more iris datasets captured under different circumstances.</p>
        </sec>
    </body>
    <back>
        <sec id="sec12" sec-type="data-availability">
            <title>Data Availability</title>
            <sec id="sec13">
                <title>Underlying data</title>
                <p>Mendely Data: AFHIRIS: African Human Iris Dataset (Version 1), doi: 
                    <ext-link ext-link-type="uri" xlink:href="https://data.mendeley.com/datasets/r3ypmmp2gs/1">10.17632/r3ypmmp2gs.1</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref7">7</xref>
</sup>
                </p>
            </sec>
            <sec id="sec14">
                <title>Extended data</title>
                <p>Mendeley Data: AFHIRIS: African Human Iris Dataset (Version 1) Supplementary File&#x201d;, doi: 
                    <ext-link ext-link-type="uri" xlink:href="https://data.mendeley.com/datasets/gp8vj2379m/1">10.17632/gp8vj2379m.1</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref9">9</xref>
</sup>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
            </sec>
        </sec>
        <ack>
            <title>Acknowledgments</title>
            <p>The authors appreciate the Landmark University Centre for Research and Development (LUCRID) for sponsoring the publication of this data article. All volunteers who made the data collection achievable are also appreciated. Most importantly the members of staff and students of Landmark University, Kwara State, Nigeria, and Ladoke Akintola University of Technology Open and Distance Learning Centre, Oyo State, Nigeria.</p>
        </ack>
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            <title>References</title>
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                        </name>

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                            <surname>Pavlovicova</surname>
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                        </name>

                        <etal/>
</person-group>:
                    <article-title>A survey of iris datasets.</article-title>
                    <source>

                        <italic toggle="yes">Image and Vision Computing.</italic>
</source>
                    <year>2021</year>;<volume>108</volume>:<fpage>104109</fpage>.
                    <pub-id pub-id-type="doi">10.1016/j.imavis.2021.104109</pub-id>
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                    <article-title>CASIA Iris Ageing database v. 1.</article-title>Accessed: 2022-04-01.
                    <ext-link ext-link-type="uri" xlink:href="http://biometrics.idealtest.org/dbDetailForUser.do?id=14">Reference Source</ext-link>
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                <label>4</label>
                <mixed-citation publication-type="other">
                    <article-title>IIT Delhi Iris Database (Version 1.0).</article-title>Accessed: 2018-10-24.
                    <ext-link ext-link-type="uri" xlink:href="http://www4.comp.polyu.edu.hk/csajaykr/IITD/Database_Iris.htmAccessed:">Reference Source</ext-link>
                </mixed-citation>
            </ref>
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                <label>5</label>
                <mixed-citation publication-type="other">
                    <article-title>CUHK Iris Image Dataset.</article-title>Accessed: 2020-05-20.
                    <ext-link ext-link-type="uri" xlink:href="http://www.mae.cuhk.edu.hk/~cvl/main_database.htm">Reference Source</ext-link>
                </mixed-citation>
            </ref>
            <ref id="ref6">
                <label>6</label>
                <mixed-citation publication-type="other">
                    <article-title>Quality-Face/Iris Research Ensemble (Q-FIRE).</article-title>Accessed: 2020-05-20.
                    <ext-link ext-link-type="uri" xlink:href="https://citer.clarkson.edu/researchresources/biometric-dataset-collections-2/quality-faceiris-research-ensemble-qfire/">https://citer.clarkson.edu/researchresources/biometric-dataset-collections-2/quality-faceiris-research-ensemble-qfire/</ext-link>
                </mixed-citation>
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                            <surname>Ojimba</surname>
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                        </name>

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                            <surname>Atele</surname>
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                        </name>

                        <etal/>
</person-group>:
                    <article-title>AFHIRIS: African Human Iris Dataset (Version 1).</article-title>
                    <source>

                        <italic toggle="yes">Mendeley Data.</italic>
</source>
                    <year>2022</year>;<volume>V1</volume>.
                    <pub-id pub-id-type="doi">10.17632/r3ypmmp2gs.1</pub-id>
                </mixed-citation>
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                    <article-title>VISTAEY2H installation &amp;amp; user manual, version 1.4, Vista Imaging, Inc.</article-title>
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                    <article-title>AFHIRIS: African Human Iris Dataset (Version 1) Supplementary File.</article-title>
                    <source>

                        <italic toggle="yes">Mendeley Data.</italic>
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                    <year>2022</year>;<volume>V1</volume>.
                    <pub-id pub-id-type="doi">10.17632/gp8vj2379m.1</pub-id>
                </mixed-citation>
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    </back>
    <sub-article article-type="reviewer-report" id="report188975">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.134790.r188975</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Winston</surname>
                        <given-names>J. Jenkin</given-names>
                    </name>
                    <xref ref-type="aff" rid="r188975a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-1482-795X</uri>
                </contrib>
                <aff id="r188975a1">
                    <label>1</label>Karunya University, Coimbatore, India</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>31</day>
                <month>8</month>
                <year>2023</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Winston JJ</copyright-statement>
                <copyright-year>2023</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport188975" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.122759.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>Suggestions for Improvement: 
                <list list-type="order">
                    <list-item>
                        <p>Along with the age range of the volunteers, the distribution of gender across each group can also be specified.</p>
                    </list-item>
                    <list-item>
                        <p>The information on the image pixel resolution of localized irises and left or right iris images can be mentioned to add more information.</p>
                    </list-item>
                    <list-item>
                        <p>The dataset format of soft biometric details can be mentioned.</p>
                    </list-item>
                    <list-item>
                        <p>The advantage of Near Infrared Imaging in comparison to Visible Light Imaging can be given to claim the NIR camera modality.</p>
                    </list-item>
                    <list-item>
                        <p>1028 volunteers have participated in image capturing. But, the number of images captured from each subject is missing.</p>
                    </list-item>
                    <list-item>
                        <p>Images with certain artifacts can be included other than spectacles and lens as it can give researchers to try innovative algorithms to work on those biometric images.</p>
                    </list-item>
                    <list-item>
                        <p>Can this dataset be used for liveliness detection?</p>
                    </list-item>
                    <list-item>
                        <p>Histogram of a raw image captured using Vista EY2H can be added.</p>
                    </list-item>
                    <list-item>
                        <p>The size of the entire dataset can be mentioned with a weblink to access the database.</p>
                    </list-item>
                    <list-item>
                        <p>An illustrative view on the contained environment used for image capturing can be given.&#x00a0;</p>
                    </list-item>
                </list>
            </p>
            <p>Are sufficient details of methods and materials provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Is the rationale for creating the dataset(s) clearly described?</p>
            <p>Yes</p>
            <p>Are the datasets clearly presented in a useable and accessible format?</p>
            <p>Yes</p>
            <p>Are the protocols appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Biometric recognition and Medical Image Analysis</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report177096">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.134790.r177096</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Czajka</surname>
                        <given-names>Adam</given-names>
                    </name>
                    <xref ref-type="aff" rid="r177096a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-2379-2533</uri>
                </contrib>
                <aff id="r177096a1">
                    <label>1</label>University of Notre Dame, Notre Dame, Indiana, USA</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>22</day>
                <month>6</month>
                <year>2023</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Czajka A</copyright-statement>
                <copyright-year>2023</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport177096" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.122759.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>Strengths:</p>
            <p> </p>
            <p> S1) Relatively large subject pool (1,028 volunteers) compared to other existing iris datasets, significantly increasing the number of iris scans acquired from African subjects available to researchers.</p>
            <p> </p>
            <p> S2) The dataset is already available and can be downloaded seamlessly. This is highly appreciated.</p>
            <p> </p>
            <p> S3) Inclusion of the selected demographical information, especially gender.</p>
            <p> </p>
            <p> S4) Inclusion of subjects wearing glasses and contact lenses.</p>
            <p> </p>
            <p> Suggestions for improvements:</p>
            <p> </p>
            <p> I1) The statements that the &#x201c;Existing publicly available human iris datasets have been collected from non-African subjects therefore, this dataset is the first publicly available human iris dataset of African descent&#x201d; and that &#x201c;iris datasets of African descents are presently not publicly available&#x201d; may be too strong. Iris image datasets collected at universities admitting international students may already include samples from African subjects. For instance, those collected at the University of Notre Dame (
                <ext-link ext-link-type="uri" xlink:href="https://cvrl.nd.edu/projects/data/">https://cvrl.nd.edu/projects/data/</ext-link>) include approx. 1% of iris images acquired from subjects who declared their race as &#x201c;Black-or-African-American&#x201d;. There seem to be also one published dataset specifically collected from African subjects: Badejo, Majekodunmi &amp; Atayero (2012)
                <sup>
                    <xref ref-type="bibr" rid="rep-ref-177096-1">1</xref>
                </sup>. I think that listing these past efforts would be worth considering by the authors.</p>
            <p> </p>
            <p> I2) Probably the most important limitation of this collection is lack of multiple acquisitions from the same eye. This prevents from conducting intra-subject-related research since the genuine comparison scores cannot be generated. I would suggest commenting in the paper the reasons for not taking multiple scans from each eye, since this is rather atypical for biometric data collections.</p>
            <p> </p>
            <p> I3) Minor suggestions: 
                <list list-type="bullet">
                    <list-item>
                        <p>If the contact lens brands are known, it would be good to add this information to the paper and/or metadata.</p>
                    </list-item>
                    <list-item>
                        <p>&#x201c;This data article has extensively described the experimental setup behind 1056 human iris datasets of African descent collected to enhance iris-related research in the African continent and beyond.&#x201d; &#x2013; Did the authors want to mention &#x201c;1056 human iris datasets&#x201d; here?</p>
                    </list-item>
                </list>
            </p>
            <p>Are sufficient details of methods and materials provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Is the rationale for creating the dataset(s) clearly described?</p>
            <p>Yes</p>
            <p>Are the datasets clearly presented in a useable and accessible format?</p>
            <p>Yes</p>
            <p>Are the protocols appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Biometrics, computer vision, pattern recognition.</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.</p>
        </body>
        <back>
            <ref-list>
                <title>References</title>
                <ref id="rep-ref-177096-1">
                    <label>1</label>
                    <mixed-citation>
                        <person-group person-group-type="author"/>:
                        <article-title>Development of CUiris: A Dark-Skinned African Iris Dataset for Enhancement of Image Analysis and Robust Personal Recognition</article-title>.
                        <source>
                            <italic>WCECS 2012, San Francisco, USA, October 24-26</italic>
                        </source>.<year>2012</year>;<volume>1</volume>:
                        <ext-link ext-link-type="uri" xlink:href="https://core.ac.uk/download/pdf/12356563.pdf">Reference source</ext-link>
                    </mixed-citation>
                </ref>
            </ref-list>
        </back>
    </sub-article>
</article>
