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A review on image segmentation techniques

luckting 添加于 2010-10-11 11:04 | 1595 次阅读 | 0 个评论

作者
Pal NR, Pal SK
摘要
Many image segmentation techniques are available in the literature. Some of these techniques use only the gray level histogram, some use spatial details while others use fuzzy set theoretic approaches. Most of these techniques are not suitable for noisy environments. Some works have been done using the Markov Random Field (MRF) model which is robust to noise, but is computationally involved. Neural network architectures which help to get the output in real time because of their parallel processing ability, have also been used for segmentation and they work fine even when the noise level is very high. The literature on color image segmentation is not that rich as it is for gray tone images. This paper critically reviews and summarizes some of these techniques. Attempts have been made to cover both fuzzy and non-fuzzy techniques including color image segmentation and neural network based approaches. Adequate attention is paid to segmentation of range images and magnetic resonance images. It also addresses the issue of quantitative evaluation of segmentation results.
详细资料
- 文献种类:期刊
- 期刊名称: Pattern Recognition
- 期刊缩写: Pattern Recognition
- 期卷页: 1993年第26卷第9期 1277-1294页
- ISBN: 0031-3203
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