This project is designed based on the paper "Matching Forensic Sketches to Mug Shot Photos".Forensic sketches differ from viewed sketches in that they are drawn by a police sketch artist using the description of the subject provided by an eyewitness. So far sketch matching only offered solutions to matching highly accurate sketches that were drawn while looking at the subject (viewed sketches). Matching a forensic sketch to a gallery of mug shot images are designed in the project using Matlab. In our sketch matching framework, two feature descriptors are used: SIFT and LBP. Our matching uses the sum of score fusion of MLBP and SIFT LFDA, as this was the highest performing method for matching viewed sketches. We apply this method to match a data set of forensic sketches against a mug shot gallery containing 88 images and performance results shown in the simulation video demo.

Reference Paper-1: Matching Forensic Sketches to Mug Shot Photos

Author’s Name: Brendan F. Klare, Zhifeng Li, and Anil K. Jain

Source: IEEE Transactions on Pattern Analysis and Machine Intelligence


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SIMULATION VIDEO DEMO