Abstract:
Off-line handwritten signature is broadly used for personal identification in financial, commercial
and legal document bindings. The automatic verification of human handwritten signature is a key
research area with respect to improve the verification of forged signature and to reduce the crimes.
The objective of this research is to provide a fast, reliable, and easy method to verify off-line
handwritten signatures. Image processing techniques and Artificial Neural Network (ANN) are
used in this research to achieve a better performance. This research is evaluated on a benchmark dataset , which contains 24 people,s signatures. five genunie and five fOff-line handwritten signature is broadly used for personal identification in financial, commercial
and legal document bindings. The automatic verification of human handwritten signature is a key
research area with respect to improve the verification of forged signature and to reduce the crimes.
The objective of this research is to provide a fast, reliable, and easy method to verify off-line
handwritten signatures. Image processing techniques and Artificial Neural Network (ANN) are
used in this research to achieve a better performance. This research is evaluated on a benchmark
