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Biogeography particle swarm optimization based counter propagation network for sketch based face recognition

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Abstract

In this paper, we present a Biogeography Particle Swarm Optimization (BPSO) based Counter Propagation Network (CPN) i.e. BPSO-CPN for Sketch Based Face Recognition (SBFR) system. A new criterion of selecting exemplar vector using biogeography learning based PSO is used for optimization of Mean Square Error (MSE) between feature vector of sketch and photo. In this work, we use Histogram of Gradient (HOG) feature vector for similarity measures between sketch and photo. Select a sketch as query image from database and using BPSO-CPN to retrieves similar photos from database. Proposed BPSO-CPN method is tested on CUHK and IIITD sketch dataset containing about 1000 sketches and photos. The experimental result envisage that, BPSO-CPN gives promising results and achieves high precision as comparison with other existing methods and neural networks. Motivation behind this research work is to find missing or wanted persons who involve in antinational activities and it help investigating agencies to narrow down the suspects quickly.

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Authors and Affiliations

  1. Department of CSE & IT, Madhav Institute of Technology and Science, Gwalior, 474005, India

    Suchitra Agrawal & Rajeev Kumar Singh

  2. School of Mathematics, Shri Mata Vaishno Devi University, Katra, Jammu, 182320, India

    Uday Pratap Singh

  3. Department of Computer Science & Engineering, Shri Mata Vaishno Devi University, Katra, 182320, India

    Sanjeev Jain

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  1. Suchitra Agrawal
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Agrawal, S., Singh, R.K., Singh, U.P. et al. Biogeography particle swarm optimization based counter propagation network for sketch based face recognition. Multimed Tools Appl 78, 9801–9825 (2019). https://doi.org/10.1007/s11042-018-6542-z

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