Signature Verification

Handwriting recognition is a process in recognizing handwritten letter images. For this project, the main purpose is to identify signature's owners to prevent from skilled forger. Therefore, the project is more focused on the signature verification rather than the character recognition. Signature verification can prevent falsification by detecting the flow ofthe curve ofthe signature and using the distance similarity. The main objective of this project is to verify the signature. The secondary objectives are to make life easier by having the signature verification system to identify the skilled forger from using someone else's credit card and to increase the security measure on credit card. The method that will be used in this project is using the neural network classification in the backpropagation network. This is because backpropagation can get the input to give the correct output, which has been used by many researchers. In implementing the prototype, a distance measure is used as the verification method but backpropagation is one of the suitable methods in designing it for future expansion. Matlab software is used in developing the system. Basically, this system will be using the Matlab software and for the hardware part by using the digitized tabiet with the pen tip in order to capture the user signature image. Beside that, some calculations will be used in measuring the signature attributes andas for the error part; there will bethepercentage ofthe error occurs