AN ADAPTIVE COMPUTATIONAL MODEL FOR TEXTURE SEGMENTATION

被引：29

作者：

CAELLI, TM ^{[1
]}

机构：

[1] INST MED PSYCHOL,D-8000 MUNCHEN 2,FED REP GER

来源：

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS | 1988年 / 18卷 / 01期

关键词：

SIGNAL FILTERING AND PREDICTION;

D O I：

10.1109/21.87051

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Extensions to current models for texture segmentation are presented, in which the underlying detector (filter) mechanisms are allowed to adapt to the incoming signal in terms of their dynamical response range and associativities. This system converges on new texton (B. Julesz, 1981) profiles of minimal dimensionality that are used to classify texture regions by a minimum distance classifier in the texture feature space. The three processes of convolution, cooperativity, and classification are individually analyzed and compared with some observations from human texture discrimination experiments.

引用

页码：9 / 17

页数：9

共 33 条

[1] CHARACTERIZATION OF TEXTURES BY EIGENFILTERS [J].