We provide a survey of hand biometric techniques in the literature and incorporate several novel results of hand-based personal identification and verification. We compare several feature sets in the shape-only and shape-plus-texture categories, emphasizing the relevance of a proper hand normalization scheme in the success of any biometric scheme. The preference of the left and right hands or of ambidextrous access control is explored. Since the business case of a biometric device partly hinges on the longevity of its features and the generalization ability of its database, we have tested our scheme with time-lapse data as well as with subjects that were unseen during the training stage. Our experiments were conducted on a hand database that is an order of magnitude larger than any existing one in the literature.