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Matching Forensic Composite Sketches with Digital Face Photos: A Bidirectional Local Binary Pattern-Based Approach

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Computer Networks, Big Data and IoT

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 117))

Abstract

Facial sketches are extensively used by investigators in order to identify the suspects involved in criminal activities. The manual method of identifying suspects is slow and complex. To make the process automated, proposed method attempts to map the computer created composite sketches to face photos automatically. This research work focuses on searching for missing and wanted persons who are involved in criminal activities that in turn assist investigative agencies in locating suspects in a timely manner. Proposed method attempts to address the challenge of mapping composite sketch to facial photos using bidirectional local binary pattern (BLBP). In the proposed method, Viola–Jones algorithm is used to detect composite sketch; feature extraction is done using BLBP; classification and recognition are done using two-dimensional convolution neural networks (2D-CNNs). The experimental results show that BLBP and 2D-CNN combined approach achieves recognition accuracy of 90% in comparison with other existing methods (Han et al. in IEEE Trans. Inf. Forensics Secur. 8, 191–204, 2013; Hochreiter et al. in Neural Comput. 9, 1735–1780, 1997; Paritosh et al.: in International Conference on Biometrics, Phuket, Thailand, pp. 251–256, 2015; Roy, H., Bhattacharjee, D.: Adv. Intell. Syst. Comput. 883, 2019).

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysore, Karnataka, India

    H. T. Chethana & Trisiladevi C. Nagavi

  2. Department of Computer Science and Engineering, S. J. College of Engineering, JSS Science and Technology University, Mysore, Karnataka, India

    H. T. Chethana

Authors
  1. H. T. Chethana
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  2. Trisiladevi C. Nagavi
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Corresponding author

Correspondence to H. T. Chethana .

Editor information

Editors and Affiliations

  1. Dean (R&D), CARE College of Engineering, Trichy, India

    A. Pasumpon Pandian

  2. Department of Electrical and Computer Engineering, Ryerson Communications Lab, Toronto, ON, Canada

    Xavier Fernando

  3. Go Perception Laboratory, Cornell University, Ithaca, NY, USA

    Wang Haoxiang

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Chethana, H.T., Nagavi, T.C. (2022). Matching Forensic Composite Sketches with Digital Face Photos: A Bidirectional Local Binary Pattern-Based Approach . In: Pandian, A.P., Fernando, X., Haoxiang, W. (eds) Computer Networks, Big Data and IoT. Lecture Notes on Data Engineering and Communications Technologies, vol 117. Springer, Singapore. https://doi.org/10.1007/978-981-19-0898-9_28

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  • DOI: https://doi.org/10.1007/978-981-19-0898-9_28

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  • Online ISBN: 978-981-19-0898-9

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