DocumentCode :
1564564
Title :
Fruit Images Segmentation Based on Fuzzy Art Model
Author :
Cao, Yukun ; Wang, ChengLiang ; Li, Yunfeng
Author_Institution :
Dept. of Comput. Sci. & Eng., Chongqing Univ.
Volume :
2
fYear :
2005
Firstpage :
784
Lastpage :
787
Abstract :
Fruits image segmentation, i.e. classifying the image into homogeneous regions, is a key step of image analysis and computer vision tasks. In this paper, an efficient segmentation method of fruit images by fuzzy clustering is presented. The new approach essentially employs a neural network based on adaptive resonance theory. This approach has the advantage of neural network computation, to improve the precise and robustness of the segmentation. The experimental results have also shown that the proposed method can obtain satisfactory results of fruit image segmentation (to locate stems, to detect blemishes), for the subsequent automatic grading of fruit and image processing systems
Keywords :
computer vision; fuzzy set theory; image segmentation; neural nets; adaptive resonance theory; computer vision tasks; fruit images segmentation; fuzzy art model; fuzzy clustering; image analysis; neural network; Adaptive systems; Art; Computer networks; Computer vision; Image analysis; Image processing; Image segmentation; Neural networks; Resonance; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
Type :
conf
DOI :
10.1109/ICNNB.2005.1614742
Filename :
1614742
Link To Document :
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