Abstract
Dean (R&D) RCET, Bhilai, (C.G) India, ABSTRACTpaper proposed feature extraction method based on centre of gravity for offline signature. Similar to other biometric measures, signatures have inherent variability and so pose a difficult recognition problem. Signature probably is one of the oldest biometric recognition methods, with high legal acceptance Signature has been a distinguishing feature for person identification through ages. Even today an increasing number of transactions, especially financial, are being authorized via signatures. In this paper, signature is preprocessed through binarization, cutting edges and thinning which provides more accurate platform for feature extraction methods. We have computed centre of gravity in two level by considering centre of gravity of all the characters separately instead of taking one common centre of gravity for entire signature and finally we would be able to built a system for signature recognition by taking mean values of all the centre of gravity values of various characters present in the signature.
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