Local Alignment of Gradient Features for Face Sketch Recognition

  • Ann Theja Alex
  • Vijayan K. Asari
  • Alex Mathew
Conference paper

DOI: 10.1007/978-3-642-33191-6_37

Volume 7432 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Alex A.T., Asari V.K., Mathew A. (2012) Local Alignment of Gradient Features for Face Sketch Recognition. In: Bebis G. et al. (eds) Advances in Visual Computing. ISVC 2012. Lecture Notes in Computer Science, vol 7432. Springer, Berlin, Heidelberg

Abstract

Automatic recognition of face sketches is a challenging problem. It has application in forensics. An artist drawn sketch based on the descriptions from the witnesses can be used as the test image to recognize a person from the photo database of suspects. In this paper, we propose a novel method for face sketch recognition. We use the edge features of a face sketch and face photo image to create a feature string called ’edge-string’. The edge-strings of the face photo and face sketch are then compared using the Smith-Waterman algorithm for local alignments. The results on CUHK (Chinese University of Hong Kong) student dataset show the effectiveness of the proposed approach in face sketch recognition.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ann Theja Alex
    • 1
  • Vijayan K. Asari
    • 1
  • Alex Mathew
    • 1
  1. 1.Computer Vision and Wide Area Surveillance Laboratory, Department of Electrical and Computer EngineeringUniversity of DaytonDaytonUSA