Biometric systems are widely used in access control and security-based applications. The goal of the biometric system is to utilize physical and/or behavioral characteristics to identify/verify the subject of interest. There are so many biometric systems that are based on physical and/or behavioral properties such as the face, iris, speech, keystroke, palmprint, retina, etc. Among these, the palmprint-based biometric system that has been investigated for over 15 years has demonstrated its applicability as a successful biometric modality. It shows a unique feature that can be obtained using texture features which are present due to the presence of palm creases, wrinkles, and ridges. Furthermore, the palmprints can be captured using low-cost sensors with a very low-resolution imaging. In this paper we propose a novel scheme for palmprint recognition using a shape and Texture-based feature (like Average gray level, Average contrast, Measure of smoothness Measure of uniformity, Entropy, Static Moment & Centroid) analysis obtained from Statistical Image Features. The palmprint image is characterized by a rich set of features including principal lines, ridges, and wrinkles. Thus, the use of an appropriate texture descriptor scheme is expected to capture this information accurately.