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Face Sketch Matching Using Speed up Robust Feature Descriptor

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Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 709))

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Abstract

In this paper, face sketch and face image matching problem is presented. Matching of the sketch with face is crucial for the law enforcement applications and received attention of the researchers in the recent years. Face sketch and face images are the two different modality representations of the same face. Face sketch is drawn based on description given by the witness when no other source of information is available about the suspect. Matching of the sketch with the face image is challenging problem due to the visual difference between a face sketch and face image. To find the potential suspect, the sketch is compared with the different face images. Speed Up Robust Feature (SURF) descriptor used for matching similarity between sketch and the face image. The result shows that, SURF descriptor gives better result as compared to Scale Invariant Feature Transform descriptor for the viewed and forensic sketches.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, College of Engineering, Pune, India

    N. K. Bansode & P. K. Sinha

Authors
  1. N. K. Bansode
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  2. P. K. Sinha
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Corresponding author

Correspondence to N. K. Bansode .

Editor information

Editors and Affiliations

  1. The University of South Dakota, Vermillion, South Dakota, USA

    K.C. Santosh

  2. Karnatak Arts, Science and Commerce College, Bidar, India

    Mallikarjun Hangarge

  3. Polytecnico di Bari, Bari, Italy

    Vitoantonio Bevilacqua

  4. University of Hyderabad, Hyderabad, India

    Atul Negi

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Bansode, N.K., Sinha, P.K. (2017). Face Sketch Matching Using Speed up Robust Feature Descriptor. In: Santosh, K., Hangarge, M., Bevilacqua, V., Negi, A. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2016. Communications in Computer and Information Science, vol 709. Springer, Singapore. https://doi.org/10.1007/978-981-10-4859-3_38

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  • DOI: https://doi.org/10.1007/978-981-10-4859-3_38

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4858-6

  • Online ISBN: 978-981-10-4859-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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