Brief review of invariant texture analysis methods

被引:299
作者
Zhang, JG [1 ]
Tan, TN [1 ]
机构
[1] Chinese Acad Sci, Inst Automat, NLPR, Beijing 100080, Peoples R China
关键词
invariant texture analysis; statistical methods; model based methods; structural methods;
D O I
10.1016/S0031-3203(01)00074-7
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (C) 2001 Pattern Recognition Society, Published by Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:735 / 747
页数:13
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