Advanced Hybrid Information Processing. First International Conference, ADHIP 2017, Harbin, China, July 17–18, 2017, Proceedings

Research Article

Offline Chinese Signature Verification Based on AlexNet

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  • @INPROCEEDINGS{10.1007/978-3-319-73317-3_5,
        author={Cui Wencheng and Guo Xiaopeng and Shao Hong and Zou Limin},
        title={Offline Chinese Signature Verification Based on AlexNet},
        proceedings={Advanced Hybrid Information Processing. First International Conference, ADHIP 2017, Harbin, China, July 17--18, 2017, Proceedings},
        proceedings_a={ADHIP},
        year={2018},
        month={2},
        keywords={AlexNet Convolution neural network Offline signature verification Writer-dependent},
        doi={10.1007/978-3-319-73317-3_5}
    }
    
  • Cui Wencheng
    Guo Xiaopeng
    Shao Hong
    Zou Limin
    Year: 2018
    Offline Chinese Signature Verification Based on AlexNet
    ADHIP
    Springer
    DOI: 10.1007/978-3-319-73317-3_5
Cui Wencheng1, Guo Xiaopeng1,*, Shao Hong1, Zou Limin1
  • 1: Shenyang University of Technology
*Contact email: wayneguo279@gmail.com

Abstract

In order to break the limitation of traditional pattern recognition in offline Chinese signature verification, the method of applying machine learning is put forward. First, the offline Chinese signature data set is pre-processed, include removing noises, binarization and normalization. Then the architecture and implementation methods of AlexNet are proposed. The experimental results show the average accuracy of classification has been up to 99.77%, and verification rate is 87.5%.