Brief review of invariant texture analysis methods

Jianguo Zhang, Tieniu Tan

    Research output: Contribution to journalArticlepeer-review

    356 Citations (Scopus)

    Abstract

    This paper considers invariant texture analysis. Texture analysis approaches whose performances are not affected by translation, rotation, affine, and perspective transform are addressed. Existing invariant texture analysis algorithms are carefully studied and classified into three categories: statistical methods, model based methods, and structural methods. The importance of invariant texture analysis is presented first. Each approach is reviewed according to its classification, and its merits and drawbacks are outlined. The focus of possible future work is also suggested.
    Original languageEnglish
    Pages (from-to)735-747
    Number of pages13
    JournalPattern Recognition
    Volume35
    Issue number3
    DOIs
    Publication statusPublished - Mar 2002

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