Brief review of invariant texture analysis methods

Jianguo Zhang, T. Tan

Research output: Contribution to journalArticlepeer-review

363 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 (3)
Issue number3
DOIs
Publication statusPublished - Mar 2002

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Electrical and Electronic Engineering

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