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    Local Tchebichef Moments for Texture Analysis (2014)

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    Type of Content
    Chapters
    UC Permalink
    http://hdl.handle.net/10092/9755
    
    Publisher's DOI/URI
    https://doi.org/10.15579/gcsr.vol1.ch6
    
    Publisher
    Science Gate Publishing
    University of Canterbury. Computer Science and Software Engineering
    ISBN
    978-618-81418-0-3
    Collections
    • Engineering: Chapters and Books [30]
    Authors
    Mukundan, R.show all
    Editors
    Papakostas, G.A.
    Abstract

    Orthogonal moment functions based on Tchebichef polynomials have found several applications in the field of image analysis because of their superior feature representation capabilities. Local features represented by such moments could also be used in the design of efficient texture descriptors. This chapter introduces a novel method of constructing feature vectors from orthonormal Tchebichef moments evaluated on 5x5 neighborhoods of pixels, and encoding the texture information as a Lehmer code that represents the relative strengths of the evaluated moments. The features will be referred to as Local Tchebichef Moments (LTMs). The encoding scheme provides a byte value for each pixel, and generates a gray-level "LTM-image" of the input image. The histogram of the LTM-image is then used as the texture descriptor for classification. The theoretical framework as well as the implementation aspects of the descriptor are discussed in detail.

    Citation
    Mukundan, R. (2014) Local Tchebichef Moments for Texture Analysis. In G.A. Papakostas (Ed.). Moments and Moment Invariants - Theory and Applications (pp. 127-142). Thrace, Greece: Science Gate Publishing.
    This citation is automatically generated and may be unreliable. Use as a guide only.
    Keywords
    image analysis and texture classification; texture analysis; texture feature descriptors; Tchebichef moments; local moments; image classification
    ANZSRC Fields of Research
    46 - Information and computing sciences::4603 - Computer vision and multimedia computation::460306 - Image processing
    08 - Information and Computing Sciences::0801 - Artificial Intelligence and Image Processing::080109 - Pattern Recognition and Data Mining
    Rights
    https://hdl.handle.net/10092/17651
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