抄録
In this paper, a novel fast approach is proposed to achieve image segmentation in color image. This method helps to refine the foreground regions and achieves the goal of robust color image segmentation throw the following four steps. First, modified Karhunen-Loeve transform is performed to reduce the redundant component, thus selecting the most important part of the color images. Second, a multi-threshold Otsu method is carried out to select the best thresholds from image histogram. Thereby, the conventional Otsu method has been extended from gray level to color level. Third, improved Sobel edge detection is added to enhance the weight of edge detail of the foreground image. Finally, a K-Means Clustering is used to merge the over-segmented regions. Experimental results prove that this method has a good performance even when the color image has a complicated structure in the background.
本文言語 | English |
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ホスト出版物のタイトル | Proceedings - 2011 5th International Conference on Genetic and Evolutionary Computing, ICGEC 2011 |
ページ | 377-380 |
ページ数 | 4 |
DOI | |
出版ステータス | Published - 2011 |
イベント | 5th International Conference on Genetic and Evolutionary Computing, ICGEC2011 - Xiamen 継続期間: 2011 8月 29 → 2011 9月 1 |
Other
Other | 5th International Conference on Genetic and Evolutionary Computing, ICGEC2011 |
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City | Xiamen |
Period | 11/8/29 → 11/9/1 |
ASJC Scopus subject areas
- 計算理論と計算数学
- コンピュータ サイエンスの応用