Title: Dense noise face recognition based on sparse representation and algorithm optimization
Abstract:To improve the speed and anti-noise performance of face recognition based on sparse representation,the Cross-And-Bouquet(CAB) model and Compressed Sensing(CS) reconstruction algorithm were studied.Con...To improve the speed and anti-noise performance of face recognition based on sparse representation,the Cross-And-Bouquet(CAB) model and Compressed Sensing(CS) reconstruction algorithm were studied.Concerning the large matrix inversion of reconstruction algorithm,a Fast Orthogonal Matching Pursuit(FOMP) algorithm was proposed.The proposed algorithm could convert the high complexity operations of matrix inversion into the lightweight operation of vector-matrix computation.To increase the amount of effective information in dense noise pictures,several practical and efficient methods were put forward.The experimental results verify that these methods can effectively improve the face recognition rate in dense noise cases,and identifiable noise ratio can reach up to 75%.These methods are of practical values.Read More
Publication Year: 2012
Publication Date: 2012-01-01
Language: en
Type: article
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