Biometric recognition refers to the use of distinctive physiology and behavioral characteristics, called biometric identifiers for automatically recognizing individuals. Among the many current biometric technologies, fingerprint and hand verification is the most popular method widely used in different commercial and security applications. The acquired fingerprint and hand image is processed using different image enhancement techniques to extract the minutiae (key identification points that vary in every individual). These minutiae details are compared against that of a pre-acquired image of the person to verify his/her identity. We have proposed hybrid fingerprint verification based on both minutiae features and wavelet statistical features. Final matching score is calculated by fusing two matching scores of minutiae based method and wavelet based algorithm. Palm print and hand geometry features can be acquired from the same image, using a digital camera, at the same time. Each of these gray level images are aligned and then used to extract palm print and hand geometry features. These features are then examined for their individual and combined performances. © Research India Publications.