SEGMENTATION OF TEXTURED IMAGES AND GESTALT ORGANIZATION USING SPATIAL SPATIAL-FREQUENCY REPRESENTATIONS

被引：115

作者：

REED, TR ^{[1
]}

WECHSLER, H ^{[1
]}

机构：

[1] GEORGE MASON UNIV,DEPT COMP SCI,FAIRFAX,VA 22030

来源：

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 1990年 / 12卷 / 01期

关键词：

Clustering; DOG; Gabor; Gestalt; Grouping; Relaxation; Spatial/spatial-frequency (s/sf) representations; Spectrogram; Texture segmentation; Wigner;

D O I：

10.1109/34.41379

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We address in this paper the generic issue of clustering/ grouping. Recent research, both in computer and human vision, suggests the use of joint spatial/spatial-frequency (s/sf) representations. Discussion on the spectrogram, the difference of Gaussians (DOG) representation, the Gabor representation, and the Wigner distribution is presented and a comparison is made. Experimental results in the area of texture segmentation and Gestalt grouping using the Wigner distribution are presented, proving the feasibility of using s/sf representations for low-level (early, preattentive) vision. © 1990 IEEE.

引用

页码：1 / 12

页数：12

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