Forensic Sketch-Photo Matching using LFDA
Ujwala T. Tayade1, Seema Biday2, Lata Ragha3

1Ujwala Tayade, Computers, Terna Engineering college, Mumbai University, Navi Mumbai, India.
2Seema Biday, Computer Department, Terna Engineering college, Mumbai University, Navi Mumbai, India.
3Lata Ragha, Computer Department, Terna Engineering college, Mumbai University, Navi Mumbai, India.
Manuscript received on August 03, 2013. | Revised Manuscript received on August 29, 2013. | Manuscript published on September 05, 2013. | PP: 242-246 | Volume-3, Issue-4, September 2013. | Retrieval Number: D1843093413
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Abstract: The advancement of biometric technology has provided criminal investigators additional tools to determine the identity of criminals. In addition to DNA and circumstantial evidence, if a latent fingerprint is found at an investigative scene or a surveillance camera captures an image of a suspect’s face, then these cues may be used to determine the culprit’s identity using automated biometric identification. However, many crimes occur where none of this information is present, but instead an eye-witness of the crime is available. In these circumstances 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. These sketches are known as forensic sketches. This problem of matching a forensic sketch to a gallery of mugshot images is addressed here using a robust framework called local feature-based discriminant analysis (LFDA). Since, forensic sketches or digital face images can be of poor quality, a pre -processing technique is used to enhance the quality of images and improve the identification performance.In this paper experiments are carried out using 52 forensic sketches for matching against a gallery of 264 photo images. The experimental results demonstrate the matching performance of the proposed algorithm with the use of preprocessing approach yields better identification accuracy compared to other methods.
Keywords: Forensic sketch, Mugshots, Feature-based approach, Local feature-based discriminant analysis, Feature descriptors.