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Comparative Analysis of Color-Based Segmentation Methods Used for Smartphone Camera Captured Fingerphotos

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Artificial Intelligence and Sustainable Computing

Part of the book series: Algorithms for Intelligent Systems ((AIS))

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Abstract

The advantages of touchless fingerprint recognition over touch-based recognition have been studied by researchers for more than a decade. Due to its high usability, acceptability, and requirement of a less-constraint environment for finger acquisition, touchless fingerprint technology is increasingly used in smartphone authentication. However, touchless fingerprint recognition is coping with various factors such as low ridge valley contrast, motion blur, and rotated or pitched finger which mainly affects its matching performance. Therefore, the recognition rate is highly dependent on the pre-processing task which includes finger segmentation, Region of Interest (RoI) extraction, orientation estimation, and enhancement. This paper primarily focused on the finger segmentation in a fingerphoto acquired from the smartphone camera. The main aim is to perform the comparative analysis of color-based segmentation methods utilizing three color models, namely YCbCr, CMYK, and CIELAB discussed in the literature. The simulation results have been carried out on IIITD smartphone fingerphoto database v1 (ISPFDv1) which contains finger photographs captured with varying illumination and background. The performance evaluation is based on determining the percentage of correctly identified skin and non-skin pixels.

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Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, GLA University, Mathura, India

    Diwakar Agarwal

  2. Department of Computer Engineering and Applications, GLA University, Mathura, India

    Deepak Mangal

Authors
  1. Diwakar Agarwal
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  2. Deepak Mangal
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Correspondence to Diwakar Agarwal .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Madhav Institute of Technology and Science, Gwalior, India

    Manjaree Pandit

  2. Madhav Institute of Technology and Science, Gwalior, India

    M. K. Gaur

  3. Thapar Institute of Engineering and Technology, Patiala, India

    Prashant Singh Rana

  4. Madhav Institute of Technology and Science, Gwalior, India

    Akhilesh Tiwari

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Agarwal, D., Mangal, D. (2022). Comparative Analysis of Color-Based Segmentation Methods Used for Smartphone Camera Captured Fingerphotos. In: Pandit, M., Gaur, M.K., Rana, P.S., Tiwari, A. (eds) Artificial Intelligence and Sustainable Computing. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-1653-3_5

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