A fuzzy region growing approach for segmentation of color images

被引:124
|
作者
Moghaddamzadeh, A
Bourbakis, N
机构
[1] SUNY BINGHAMTON,DEPT EE,AAAI LAB,BINGHAMTON,NY 13902
[2] UNIV CRETE,DEPT ECE,KHANIA 73100,GREECE
关键词
segmentation; color segmentation; fuzzy image processing; fuzzy segmentation; region growing;
D O I
10.1016/S0031-3203(96)00084-2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Segmentation is one of the most important preprocessing steps towards pattern recognition and image understanding and a significant step towards image compression and coding. With detecting edges, most of the large segments can be found and separated from others by edge pixels. It is, however, the pixels on edge locations or those in high detailed areas whose association to adjacent segments must be found A pixel can be a part of the closest segment or in association with the neighboring pixels from a new smaller segment. In this paper, two segmentation algorithms are presented. One is used for fine segmentation towards compression and coding of images and the other for coarse segmentation towards other applications like object recognition and image understanding. Edge detection and region growing approaches are combined to find large and crisp segments for coarse segmentation. Segments can grow or expand based on two fuzzy criteria. The fuzzy region growing and expanding approaches presented here use histogram tables for fine segmentation. The procedures introduced here can be used in any order or combination to yield the best result for any particular application or image type. (C) 1997 Pattern Recognition Society.
引用
收藏
页码:867 / 881
页数:15
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