신경망을 이용한 서명 인식 = Signature Verification Using the Neural Network

다국어 초록 (Multilingual Abstract)

Recently, many algorithms for the image pattern recognition using the neural network have been proposed.
In this paper, the characteristic parameters of signature pattern can be extracted by using discrete consine transform.
The neural network is implemented with back propagation, generalized delta rule which is able to learn multi-layer perceptron among the various model and it is applied to the signature verification system as pattern classifier.
Through the experimentation, the input of signature pattern which has N=16, is transformed with 2-dimension discrete cosine transform, and the characteristic parameters is applied to 3-layer perceptron neural network model.
The experimental result shows the signature verification could be possible to verify them and the applied algorithms of neural network model could be applied to the signature verification.

목차 (Table of Contents)

• Ⅰ. 서 론
• Ⅱ. 이산 코사인 변환
• Ⅲ. 신경망 모델
• Ⅳ. 실험 및 검토
• Ⅴ. 결 론