COMPRESSION BASED FACE RECOGNITION USING TRANSFORM DOMAIN FEATURES FUSED AT MATCHING LEVEL

The physiological biometric trait face images are used to identify a person effectively. In this paper, we propose compression based face recognition using transform domain features fused at matching level. The 2D images are converted into 1-D vectors using mean to compress number of pixels. The Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT) are used to extract features. The low and high frequency coefficients of DWT are concatenated to obtained final DWT features. The performance parameters are computed by comparing database and test image features of FFT and DWT using Euclidian Distance (ED). The performance parameters of FFT and DWT are fused at matching level to obtain better results. It is observed that the performance of proposed method is better than the existing methods.