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Chinese Conference on Pattern Recognition

CCPR 2016: Pattern Recognition pp 766–778Cite as

Fractional Orthogonal Fourier-Mellin Moments for Pattern Recognition

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 662))

Abstract

In this paper, we generalize the orthogonal Fourier-Mellin moments (OFMMs) to the fractional orthogonal Fourier-Mellin moments (FOFMMs), which are based on the fractional radial polynomials. We propose a new method to construct FOFMMs by using a continuous parameter \( t \) \( \left( {t > 0} \right) \). The fractional radial polynomials of FOFMMs have the same number of zeros as OFMMs with the same degree. But the zeros of FOFMMs polynomial are more uniformly distributed than which of OFMMs and the first zero is closer to the origin. A recursive method is also given to reduce computation time and improve numerical stability. Experimental results show that the proposed FOFMMs have better performance.

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Acknowledgments

This work is partly supported by National Natural Science Foundation of China (Grant no. 61379106), the Shandong Provincial Natural Science Foundation (Grant nos. ZR2013FM036, ZR2015FM011), the Open Project Program of the State Key Lab of CAD&CG (Grant no. A1315), Zhejiang University, the Fundamental Research Funds for the Central Universities (Grant nos. 14CX02032A, 14CX02031A).

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Authors and Affiliations

  1. China University of Petroleum (Huadong), 66# Changjiang West Road, Qingdao Economic and Technological Development Zone, Beijing, 266580, Shandong, China

    Huaqing Zhang, Zongmin Li & Yujie Liu

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  1. Huaqing Zhang
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  2. Zongmin Li
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  3. Yujie Liu
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Corresponding author

Correspondence to Zongmin Li .

Editor information

Editors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Tieniu Tan

  2. Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China

    Xuelong Li

  3. Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China

    Xilin Chen

  4. Tsinghua University , Beijing, China

    Jie Zhou

  5. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

  6. University of Electronic Science and Technology, Chengdu, Sichuan, China

    Hong Cheng

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© 2016 Springer Nature Singapore Pte Ltd.

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Zhang, H., Li, Z., Liu, Y. (2016). Fractional Orthogonal Fourier-Mellin Moments for Pattern Recognition. In: Tan, T., Li, X., Chen, X., Zhou, J., Yang, J., Cheng, H. (eds) Pattern Recognition. CCPR 2016. Communications in Computer and Information Science, vol 662. Springer, Singapore. https://doi.org/10.1007/978-981-10-3002-4_62

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  • DOI: https://doi.org/10.1007/978-981-10-3002-4_62

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3001-7

  • Online ISBN: 978-981-10-3002-4

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