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Charlier and Meixner Moments and Their Application for Texture and Image De-noising Problems

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Information, Photonics and Communication

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 79))

Abstract

Moment-based features have been employed for solving various problems in pattern recognition and image processing. In this paper, we choose Charlier and Meixner moments separately, to solve texture segmentation, classification, and de-noising of images corrupted with Gaussian noise. In order to solve the texture classification problem, we propose to use lower-order Charlier and Meixner moments of 12 Haralick’s texture features and a two-class support vector machine. But, for texture segmentation problem, we use these moment-based texture energy features suggested for geometric moments by Mihran Tuceryan. Further, these energy features are used in K-means, Fuzzy K-means, and Kohonen’s neural network for solving texture segmentation problem, whereas for image de-noising problem, we use non-local mean (NLM) filter with Charlier and Meixner moments-based similarity values instead of pixel-based similarity values used in NLM for filter weights calculation. The simulation results show that the proposed applications worked well for two-class texture segmentation, classification of texture images and de-noising of images corrupted with a small amount of noise.

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Acknowledgements

Author was supported by the University Grants Commission, New Delhi, under Emeritus fellowship. No. F.6-6/2017-18/EMERITUS-2017-18-GEN-10889/(SA-II). Author also thanks Mr. Bharath, Research scholor, ECE, Dept, OU, for assisting in the preparation of the document.

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Authors and Affiliations

  1. Department of ECE, College of Engineering, Osmania University, Hyderabad, 500007, India

    Perugu Ananth Raj

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  1. Perugu Ananth Raj
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Correspondence to Perugu Ananth Raj .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, India

    Jyotsna Kumar Mandal

  2. University of Calcutta, Kolkata, West Bengal, India

    Kallol Bhattacharya

  3. B.P. Poddar Institute of Management and Technology, Kolkata, West Bengal, India

    Ivy Majumdar

  4. B.P. Poddar Institute of Management and Technology, Kolkata, West Bengal, India

    Surajit Mandal

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Raj, P.A. (2020). Charlier and Meixner Moments and Their Application for Texture and Image De-noising Problems. In: Mandal, J., Bhattacharya, K., Majumdar, I., Mandal, S. (eds) Information, Photonics and Communication. Lecture Notes in Networks and Systems, vol 79. Springer, Singapore. https://doi.org/10.1007/978-981-32-9453-0_13

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  • DOI: https://doi.org/10.1007/978-981-32-9453-0_13

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-32-9452-3

  • Online ISBN: 978-981-32-9453-0

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