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Content Provider | IEEE Xplore Digital Library |
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Author | Zhu Yux Wang Yuhua Liang Haibo |
Copyright Year | 2010 |
Abstract | The Fuzzy C-means (FCM) clustering is simple and easy to implement in color image segmentation, but firstly, some problems should be solved such as the number of calculating, centers and large computation. So we have designed an improved FCM algorithm based on hybrid color space and firstly transformed the color image from RGB color space into HSV color space, where the number of clustering can be calculated, and after the initial cluster center is calculated in CIELAB color space, FCM algorithm will be used for segmentation. Experiments show that the improved approach can reduce the number of iterations of FCM and greatly enhance the speed of segmentation, which has been applied to the fast segmentation of the colorful wall and floor tiles image successfully. |
Starting Page | 4605 |
Ending Page | 4607 |
File Size | 334175 |
Page Count | 3 |
File Format | |
ISBN | 9781424468805 |
e-ISBN | 9781424468812 |
DOI | 10.1109/iCECE.2010.1112 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2010-06-25 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Image segmentation Histograms Image color analysis Tiles Space technology FCM algorithm Clustering algorithms Color Imagesegmentation Colorspace Fuzzy lustering |
Content Type | Text |
Resource Type | Article |
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