Document analysis and recognition software is greatly required in office automation. The ability to efficiently process small handwritten samples, like those founds on check and envelopes, is one of the major driving forces behind the current research. Hampered by the large amount of variation between handwritten samples, researchers have had to find techniques that will improve the ability of computers to represent and recognize handwritten samples. One approach that has shown great impact is the use of artificial neural network. In this approach, an artificial neural network is trained to identify similarities and patters among different samples. This project will explore the topic of automated signature recognition using artificial neural network.