2D CROSS CORRELATION MULTI-MODAL IMAGE RECOGNITION
C Yuganya1, A V Khirthana2, and Udayakumara pandian3
|Corresponding Author: C Yuganya, E-mail: [email protected]|
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The bio-metric is ultra secure and more than one form of biometric identification is required. To use a combination of different biometric recognition we are using multi-modal biometric recognition. In this paper, the multi-level wavelet transform algorithm that combines information from palm, face, iris, and digital signature images and recognition of signature that makes use of biometric traits to recognize individuals. Multimodal biometric systems technology uses more than one biometric identifier to compare the identity of the image..A multi modal biometric system of iris and palm print based on Wavelet Packet Analysis is described. The visible texture of a person's face, palm, iris and signature is encoded into a compact sequence of 2-D wavelet packet coefficients, which generate a "feature vector code". The multi-resolution approach based on Wavelet Packet Transform (WPT) for texture analysis and recognition of face, iris, palm, and signature images. WPT sub images coefficients are quantized into 1, 0 or -1 as multi-resolution. The input of the iris,palm,face and signature is matched and stores as a scrumbled image usin DWT algorithm,then reconstruct the method and then gives the result to get access into the data.