Chapter

Advances in Visual Computing

Volume 7432 of the series Lecture Notes in Computer Science pp 378-387

Local Alignment of Gradient Features for Face Sketch Recognition

  • Ann Theja AlexAffiliated withCarnegie Mellon UniversityComputer Vision and Wide Area Surveillance Laboratory, Department of Electrical and Computer Engineering, University of Dayton
  • , Vijayan K. AsariAffiliated withCarnegie Mellon UniversityComputer Vision and Wide Area Surveillance Laboratory, Department of Electrical and Computer Engineering, University of Dayton
  • , Alex MathewAffiliated withCarnegie Mellon UniversityComputer Vision and Wide Area Surveillance Laboratory, Department of Electrical and Computer Engineering, University of Dayton

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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.