Possibilistic Clustering Algorithm Incorporating Grey-Level Histogram and Spatial Information for Image Segmentation
Image segmentation is a process of segmenting an image into non-intersecting regions containing homogeneous pixels that are inhomogeneous with those in other adjacent regions. In this paper, a possibilistic clustering algorithm incorporating grey-level histogram and spatial information (PCA_HS) for...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2016-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | http://dx.doi.org/10.1051/matecconf/20165602002 |
| _version_ | 1818415786618781696 |
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| author | Yu Jing Kuang Yujun Fu Xinchuan |
| author_facet | Yu Jing Kuang Yujun Fu Xinchuan |
| author_sort | Yu Jing |
| collection | DOAJ |
| description | Image segmentation is a process of segmenting an image into non-intersecting regions containing homogeneous pixels that are inhomogeneous with those in other adjacent regions. In this paper, a possibilistic clustering algorithm incorporating grey-level histogram and spatial information (PCA_HS) for image segmentation is proposed. The grey-level histogram speeds up the algorithm and the spatial information enhances its robustness to noise and outliers. To assess the proposed algorithm, four widely used validity indexes are computed and discussed. As the experimental quantitative and qualitative results on real images with and without noise show, PCA_HS can preserve the homogeneity and integrality of the regions and hence is more effective and efficient than traditional PCA. |
| first_indexed | 2024-12-14T11:40:32Z |
| format | Article |
| id | doaj.art-4a0f95b688874ca1a13a8c82485b3397 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-14T11:40:32Z |
| publishDate | 2016-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-4a0f95b688874ca1a13a8c82485b33972022-12-21T23:02:51ZengEDP SciencesMATEC Web of Conferences2261-236X2016-01-01560200210.1051/matecconf/20165602002matecconf_iccae2016_02002Possibilistic Clustering Algorithm Incorporating Grey-Level Histogram and Spatial Information for Image SegmentationYu JingKuang YujunFu XinchuanImage segmentation is a process of segmenting an image into non-intersecting regions containing homogeneous pixels that are inhomogeneous with those in other adjacent regions. In this paper, a possibilistic clustering algorithm incorporating grey-level histogram and spatial information (PCA_HS) for image segmentation is proposed. The grey-level histogram speeds up the algorithm and the spatial information enhances its robustness to noise and outliers. To assess the proposed algorithm, four widely used validity indexes are computed and discussed. As the experimental quantitative and qualitative results on real images with and without noise show, PCA_HS can preserve the homogeneity and integrality of the regions and hence is more effective and efficient than traditional PCA.http://dx.doi.org/10.1051/matecconf/20165602002 |
| spellingShingle | Yu Jing Kuang Yujun Fu Xinchuan Possibilistic Clustering Algorithm Incorporating Grey-Level Histogram and Spatial Information for Image Segmentation MATEC Web of Conferences |
| title | Possibilistic Clustering Algorithm Incorporating Grey-Level Histogram and Spatial Information for Image Segmentation |
| title_full | Possibilistic Clustering Algorithm Incorporating Grey-Level Histogram and Spatial Information for Image Segmentation |
| title_fullStr | Possibilistic Clustering Algorithm Incorporating Grey-Level Histogram and Spatial Information for Image Segmentation |
| title_full_unstemmed | Possibilistic Clustering Algorithm Incorporating Grey-Level Histogram and Spatial Information for Image Segmentation |
| title_short | Possibilistic Clustering Algorithm Incorporating Grey-Level Histogram and Spatial Information for Image Segmentation |
| title_sort | possibilistic clustering algorithm incorporating grey level histogram and spatial information for image segmentation |
| url | http://dx.doi.org/10.1051/matecconf/20165602002 |
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