Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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A New Approach For Off-Line Signature Verification Using Fuzzy ARTMAP

  • Published : 1995.12.01
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Abstract

This paper delas with the detection of freehand forgeries of signatures based on the averaged directional amplitudes of gradient vetor which are related to the overall shape of the handwritten signature and fuzzy ARTMAP neural network classifier. In the first step, signature images are extracted from the background by a process involving noise reduction and automatic thresholding. Next, twelve directional amplitudes of gradient vector for each pixel on the signature line are measure and averaged through the entire signature image. With these twelve averaged directional gradient amplitudes, the fuzzy ARTMAP neural network is trained and tested for the detection of freehand forgeries of singatures. The experimental results show that the fuzzy ARTMAP neural network cna lcassify a signature whether genuine or forged with greater than 95% overall accuracy.

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References

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