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Text-Independent Writer Identification Using Improved Structural Features

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Biometric Recognition (CCBR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8833))

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Abstract

This paper presents a method based on two structural features for text-independent writer identification, i.e. SIFT descriptor (SD) and triangular descriptor (TD). For SD, we modify the original SIFT algorithm to make the SD possess orientation information, called modified SIFT descriptor (MSD). Acodebookis constructed by clustering the MSDs extracted from training samples. Then the bag of word technique is used to compute a MSD histogram (MSDH) as a feature vector for writer identification. For TD, it is designed to represent the unique relationship between three selected points. A TD histogram (TDH) of the TD occurrences is computed as another feature vector by tracking the contour points of a handwriting image. The distances between MSDHs and TDHs are computed and combined as the final dissimilarity measurement for the handwriting images. Experimental results on two public challenging datasets demonstrate the efficiency of the proposed method.

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, China

    Youbao Tang & Xiangqian Wu

  2. Department of New Media Technologies and Arts, Harbin Institute of Technology, Harbin, 150001, China

    Wei Bu

Authors
  1. Youbao Tang
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  2. Wei Bu
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  3. Xiangqian Wu
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Editor information

Editors and Affiliations

  1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, 100190, Beijing, China

    Zhenan Sun

  2. Institute of Computing Technology, Chinese Academy of Sciences, No.6 Kexueyuan South Road, P.O. Box 2704, 100190, HaiDian, Beijing, China

    Shiguang Shan

  3. School of Information Science and Engineering, Shenyang University of Technology, No.111, Shenliao West Road, Economic and Technological Development Zone, 110870, Shenyang, China

    Haifeng Sang  & Weiqi Yuan  & 

  4. Software Engineering Institute, Tsinghua University, No. 1 Tsinghua Yuan, Haidian District, 100084, Beijing, China

    Jie Zhou

  5. School of Computer Science and Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, 100191, Beijing, China

    Yunhong Wang

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© 2014 Springer International Publishing Switzerland

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Tang, Y., Bu, W., Wu, X. (2014). Text-Independent Writer Identification Using Improved Structural Features. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds) Biometric Recognition. CCBR 2014. Lecture Notes in Computer Science, vol 8833. Springer, Cham. https://doi.org/10.1007/978-3-319-12484-1_45

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  • DOI: https://doi.org/10.1007/978-3-319-12484-1_45

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12483-4

  • Online ISBN: 978-3-319-12484-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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