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Image Recognition by Affine Tchebichef Moment Invariants

  • Conference paper
Artificial Intelligence and Computational Intelligence (AICI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7004))

Abstract

Tchebichef moments are successfully used in the field of image analysis because of their polynomial properties of discrete and orthogonal. In this paper, two new affine invariant sets are introduced for object recognition using discrete orthogonal Tchebichef moments. The current study constructs affine Tchebichef invariants by normalization method. Firstly, image is normalized to a standard form using Tchebichef moments as normalization constraints. Then, the affine invariants can be obtained at the standard form. The experimental results are presented to illustrate the performance of the invariants for affine deformed images.

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Author information

Authors and Affiliations

  1. Department of Electronics and Communications Engineering, East China University of Science and Technology, Shanghai, 200237, China

    Qian Liu, Hongqing Zhu & Qian Li

Authors
  1. Qian Liu
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  2. Hongqing Zhu
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  3. Qian Li
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Editor information

Editors and Affiliations

  1. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, VIC, Australia

    Hepu Deng

  2. School of Electronics and Information, Tongji University, 201804, Shanghai, China

    Duoqian Miao

  3. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  4. Department of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Liu, Q., Zhu, H., Li, Q. (2011). Image Recognition by Affine Tchebichef Moment Invariants. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7004. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23896-3_58

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  • DOI: https://doi.org/10.1007/978-3-642-23896-3_58

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23895-6

  • Online ISBN: 978-3-642-23896-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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