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There is a long history of using handwritten signatures to verify or authenticate a “signer” of the signed document. With the development of Internet technology, many tasks can be accomplished through the document management system, such as the applications of digital contracts or important documents, and more secure signature verification is demanded. Thus, the live handwriting signatures are attracting more interest for biological human identification. In this paper, we propose a handwriting signature verification algorithm by using four live waveform elements as the verification features. A new Aho-Corasick Histogram mechanism is proposed to perform this live signature verification. The benefit of the ACH algorithm is mainly its ability to convert time-series waveforms into time-series short patterns and then perform a statistical counting on the AC machine to measure the similarity. Since AC is a linearly time complexity algorithm, our ACH method can own a deterministic processing time. According to our experiment result, the proposed algorithm has satisfying performance in terms of speed and accuracy with an average of 91% accuracy.
Tseng et al. (Wed,) studied this question.