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Genetic Approach Based Recognizing Surgically Altered Face Images for Real Time Security Application


R. Aarthi , P. S. R. Engineering College, Sivakasi, India; D. Arun Shunmugam, P.S.R Engineering College, Sivakasi, India


Face Recognition, Genetic Approach, Plastic Surgery, Granular computing.


Widespread acceptability and use of biometrics for person authentication has instigated several techniques for evading identification. One such technique is altering facial appearance using surgical procedures that has raised a challenge for face recognition algorithms. Increasing popularity of plastic surgery and its effect on automatic face recognition has attracted attention from the research community. However, the nonlinear variations introduced by plastic surgery remain difficult to be modeled by existing face recognition systems. In this work, a multiobjective evolutionary granular algorithm is proposed to match face images before and after plastic surgery. The algorithm first generates non-disjoint face granules at multiple levels of granularity. The granular information is assimilated using a multiobjective genetic approach that simultaneously optimizes the selection of feature extractor for each face granule along with the weights of individual granules. On the plastic surgery face database, the proposed algorithm yields high identification accuracy as compared to existing algorithms and a commercial face recognition system.

Other Details

Paper ID: IJSRDV2I2419
Published in: Volume : 2, Issue : 2
Publication Date: 01/05/2013
Page(s): 780-784

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