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Finger contour profile based hand biometric recognition

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Abstract

This paper presents a contactless hand biometric system at unrestricted hand pose environment. A new preprocessing technique is proposed for defining the finger contour profiles (FCP). It mainly consists of simple grayscale image transformation, subtraction, and logical XOR operation. This hand prototyping method logically decomposes global hand contour into the left and right contour profiles of each finger. A set of twenty pose-invariant geometric features is extracted from the FCP and normalized global hand shape. Experiments are conducted on two publicly available hand databases namely, the Bosphorus and IIT Delhi (IITD) databases to validate the system using the kNN, minimum distance, and random forest (RF) classifiers. Satisfactory identification accuracy of 97.82 % using the RF classifier has been achieved for the Bosphorus database with 320 subjects; and in verification, 3.28 % equal error rate (EER) is reported. The kNN classifier has been found to produce good identification success of 95.22 % for the IITD database of 230 subjects; and 4.76 % EER is obtained in verification. The average execution time of this approach is lesser than 2 s, that implies its suitability in real-world applications.

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Acknowledgements

The authors would like to thank the Editors and anonymous Reviewers for their valuable and insightful comments.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Haldia Institute of Technology, Haldia, 721657, India

    Asish Bera

  2. Department of Computer Science and Engineering, Jadavpur University, Kolkata, 700032, India

    Debotosh Bhattacharjee & Mita Nasipuri

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  1. Asish Bera
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  2. Debotosh Bhattacharjee
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  3. Mita Nasipuri
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Correspondence to Asish Bera.

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Bera, A., Bhattacharjee, D. & Nasipuri, M. Finger contour profile based hand biometric recognition. Multimed Tools Appl 76, 21451–21479 (2017). https://doi.org/10.1007/s11042-016-4075-x

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  • DOI: https://doi.org/10.1007/s11042-016-4075-x

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