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FACE AND THUMB RECOGNITION BY PCA AND DWT

Biometrics is the science and technology of measuring and analyzing biological data of human body, extracting a feature set from the acquired data, and comparing this set against to the template set in the database. Experimental studies show that Unimodal biometric systems had many disadvantages regarding performance and accuracy. Multimodal biometric systems perform better than Unimodal biometric systems and are popular even more complex also. In this paper we introduce face and thumb images recognition using Transform Domain and Spatial Domain Techniques. Also In this paper we use a pixel-level image fusion scheme using discreet wavelet transform (DWT). Wavelet coefficients at different decomposing levels are fused using absolute maximum fusion rule. And extract the feature of fused images by Principal Component Analysis (PCA) and texture feature extraction. Person will be categorized as known or unknown face after matching with the present database. The test and database fused features are compared using Euclidean Distance (ED).