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A ZigZag Pattern of Local Extremum Logarithm Difference for Illumination-Invariant and Heterogeneous Face Recognition

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Transactions on Computational Science XXXI

Part of the book series: Lecture Notes in Computer Science ((TCOMPUTATSCIE,volume 10730))

Abstract

A novel methodology for matching of illumination-invariant and heterogeneous faces is proposed here. We present a novel image representation called local extremum logarithm difference (LELD). Theoretical analysis proves that LELD is an illumination-invariant edge feature in coarse level. Since edges are invariant in different modalities, more importance is given on edges. Finally, a novel local zigzag binary pattern LZZBP is presented to capture the local variation of LELD, and we call it a zigzag pattern of local extremum logarithm difference (ZZPLELD). For refinement of ZZPLELD, a model based weight value learning is suggested. We tested the proposed methodology on different illumination variations, sketch-photo and NIR-VIS benchmark databases. Rank-1 recognition of 96.93% on CMU-PIE database and 95.81% on Extended Yale B database under varying illumination, show that ZZPLELD is an efficient method for illumination invariant face recognition. In the case of viewed sketches, the rank-1 recognition accuracy of 98.05% is achieved on CUFSF database. In the case of NIR-VIS matching, the rank-1 accuracy of 99.69% is achieved and which is superior to other state-of-the-art methods.

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Authors and Affiliations

  1. Department of Information Technology, RCC Institute of Information Technology, Canal South Road, Beliaghata, Kolkata, 700015, India

    Hiranmoy Roy

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

    Debotosh Bhattacharjee

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  1. Hiranmoy Roy
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  2. Debotosh Bhattacharjee
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Correspondence to Hiranmoy Roy .

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Editors and Affiliations

  1. University of Calgary, Calgary, Alberta, Canada

    Marina L. Gavrilova

  2. Sardina Systems OÜ, Tallinn, Estonia

    C.J. Kenneth Tan

  3. University of Calcutta, Calcutta, India

    Nabendu Chaki

  4. Bialystok University of Technology, Bialystok, Poland

    Khalid Saeed

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Roy, H., Bhattacharjee, D. (2018). A ZigZag Pattern of Local Extremum Logarithm Difference for Illumination-Invariant and Heterogeneous Face Recognition. In: Gavrilova, M., Tan, C., Chaki, N., Saeed, K. (eds) Transactions on Computational Science XXXI. Lecture Notes in Computer Science(), vol 10730. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-56499-8_1

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  • DOI: https://doi.org/10.1007/978-3-662-56499-8_1

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  • Online ISBN: 978-3-662-56499-8

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