Face Sketch to Photo Matching Using LFDA

The progression of biometric technology has provided criminal investigators additional tools to determine the criminal’s identity. In addition to DNA and circumstantial evidence, if a dormant fingerprint is found at an investigative sight or a surveillance camera captures an image of a suspect’s face, then these cues may be used to determine the identity of culprit’s, using automated biometric identification. However, many crimes occur when none of such information is present, but instead an eye-witness of the crime is available. In such situation a forensic artist is often used to work with the witness or the victim in order to draw a sketch that depicts the facial appearance of the culprit according to the verbal description; such sketch drawn depending on the description given by an eye witness is called forensic sketch. Using feature based approach how to match a forensic sketch to a gallery of mugshot images described here. To match forensic sketches against mugshot images a robust framework called local feature-based discriminant analysis (LFDA) is used. In this paper experiments are carried out using 45 forensic sketches for matching against a gallery of 150 photo images. In this framework, both sketch and photo images are considered for extracting feature descriptors using scale invariant feature transform (SIFT) and multiscale local binary pattern (MLBP) method. The experimental results demonstrate the matching performance using the presented feature based approach.