The biometric is used to identify a person effectively and employ in almost all applications of day to day activities. In this paper, we propose compression based face recognition using Discrete Wavelet Transform (DWT) and Support Vector Machine (SVM). The novel concept of converting many images of single person into one image using averaging technique is introduced to reduce execution time and memory. The DWT is applied on averaged face image to obtain approximation (LL) and detailed bands. The LL band coefficients are given as input to SVM to obtain Support vectors (SV's). The LL coefficients of DWT and SV's are fused based on arithmetic addition to extract final features. The Euclidean Distance (ED) is used to compare test image features with database image features to compute performance parameters. It is observed that, the proposed algorithm is better in terms of performance compared to existing algorithms.

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