Title

Local alignment of gradient features for face photo and face sketch recognition

Date of Award

2012

Degree Name

M.S. in Electrical Engineering

Department

Department of Electrical and Computer Engineering

Advisor/Chair

Advisor: Vijayan K. Asari

Abstract

Automatic recognition of human faces (face photo recognition) irrespective of the expression variations and occlusions is a challenging problem. In the proposed technique, the edges of a face are identified, and a feature string is created from edge pixels. This forms a symbolic descriptor corresponding to the edge image referred to as 'edge-string.' The 'edge-strings' are then compared using the Smith-Waterman algorithm to match them. The class corresponding to each image is identified based on the number of string primitives that match. This method needs only a single training image per class. The proposed technique is also applicable to face sketch recognition. In face sketch recognition, a sketch drawn based on the descriptions of the victims or witnesses is compared against the photos in the mug shot database to facilitate a faster investigation. The effectiveness of the proposed method is compared with state-of-the-art algorithms on several databases. The method is observed to give promising results for both face photo recognition and face sketch recognition.

Keywords

Human face recognition (Computer science), Face Identification, Optical pattern recognition, Face recognition; face sketch recognition; string matching; Smith Waterman algorithm; edge features; biometrics

Rights Statement

Copyright 2012, author

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