Brief review of invariant texture analysis methods

Jianguo Zhang (1) , Tieniu Tan (1)

1 NLPR - National Laboratory of Pattern Recognition [Beijing]

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.

Mots clés: Invariant texture analysis; Statistical methods; Model based methods; Structural methods

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Jianguo Zhang, Tieniu Tan. Brief review of invariant texture analysis methods. Pattern Recognition, 2002, 35 (3), pp.735--747. ⟨10.1016/S0031-3203(01)00074-7⟩. ⟨inria-00548263⟩