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Robust Detection of Iris Region Using an Adapted SSD Framework

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Computer Vision Applications (WCVA 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1019))

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Abstract

Accurate detection of the iris is a crucial step in several biometric tasks, such as iris recognition and spoofing detection, among others. In this paper, we consider the detection task to be the delineation of the smallest square bounding box that surrounds the iris region. To overcome the various challenges of the iris detection task, we present an efficient iris detection method that leverages the SSD (Single Shot multibox Detector) model. The architecture of SSD is modified to give a lighter and simpler framework capable of performing fast and accurate detection on the relatively smaller sized iris biometric datasets. Our method is evaluated on 4 datasets taken from different biometric applications and from the literature. It is also compared with baseline methods, such as Daugman’s algorithm, HOG+SVM and YOLO. Experimental results show that our modified SSD outperforms these other techniques in terms of speed and accuracy. Moreover, we introduce our own near-infrared image dataset for iris biometric applications, containing a robust range of samples in terms of age, gender, contact lens presence, and lighting conditions. The models are tested on this dataset, and shown to generalise well. We also release this dataset for use by the scientific community.

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Notes

  1. 1.

    Print and sign the license agreement available at Saksham Jain’s website. Scan and email it to both authors, upon which the download link to the dataset will be sent to the interested researcher.

  2. 2.

    Implementation: https://github.com/Qingbao/iris.

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Author information

Authors and Affiliations

  1. Netaji Subhas Institute of Technology, Delhi, India

    Saksham Jain

  2. Delhi Technological University, Delhi, India

    Indu Sreedevi

Authors
  1. Saksham Jain
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  2. Indu Sreedevi
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Correspondence to Saksham Jain .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Delhi, New Delhi, India

    Chetan Arora

  2. Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India

    Kaushik Mitra

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Jain, S., Sreedevi, I. (2019). Robust Detection of Iris Region Using an Adapted SSD Framework. In: Arora, C., Mitra, K. (eds) Computer Vision Applications. WCVA 2018. Communications in Computer and Information Science, vol 1019. Springer, Singapore. https://doi.org/10.1007/978-981-15-1387-9_5

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  • DOI: https://doi.org/10.1007/978-981-15-1387-9_5

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  • Online ISBN: 978-981-15-1387-9

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