Handwritten signature is one of the most popular distinguishing biometric feature which can be used for a secure personal authentication. In this paper a handwritten signature recognition system is proposed for static images. The system consists of three primary stages (preprocessing, feature extraction and recognition). In preprocessing stage a set of image processing methods is applied to remove the undesired noise and extracting signature region (ROI). After that, a new set of spatio- statistical features is determined form extracted ROI body, these features represent the density of the signature in each image block. The set of introduced features is determined from the spatial domain after partitioning it into overlapped blocks. Then, the spatio-statistical features are determined from each block separately and assembled into one feature vector that representing the tested signature sample. The experimental results showed that the developed system can gave recognition accuracy around 98% when tested on a database consists of 612 signature images belong to 102 persons.