| Summary: | 碩士 === 國立臺灣大學 === 電信工程學研究所 === 105 === In the past couple of decades, techniques for handwritten signature verification have been thoroughly studied and put into practice in various systems, which include security systems and financial field where credit cards verification is much needed. Generally speaking, handwritten signature verification system can be categorized into two kinds, online and offline verification. The former requires stylus pens and tablet computers to capture dynamic signature information, whilst for offline verification, a scanner is used to turn handwritten information into static formats such as image files.
Due to the fact that there is not yet a scientific system for signatures verification upon forgery problems in the Taiwan judicial system, the procedure is mainly carried out through trained human eyes, with which validate the signatures with different unique cursive writing styles. In this thesis, a more systematic and dependable method on signatures verification is proposed. With the rapid development of computer vision and machine learning, it is possible to identify whether the signature is forged even under limited data.
The layout of this thesis is as follows:
The first three chapters give a brief introduction and provide background knowledge in the field of handwritten signature verification. The fourth chapter focuses on system architecture design, including data preprocessing, transformation, classification, and testing. Chapter five present the comparison with different parameters and simulation models. And finally, the last chapter wraps up the thesis with discussion and future work.
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