Visual Sensor Based Image Segmentation by Fuzzy Classification and Subregion Merge
The extraction and tracking of targets in an image shot by visual sensors have been studied extensively. The technology of image segmentation plays an important role in such tracking systems. This paper presents a new approach to color image segmentation based on fuzzy color extractor (FCE). Differe...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2017/7347421 |
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| author | Huidong He Xiaoqian Mao Wei Li Linwei Niu Genshe Chen |
| author_facet | Huidong He Xiaoqian Mao Wei Li Linwei Niu Genshe Chen |
| author_sort | Huidong He |
| collection | DOAJ |
| description | The extraction and tracking of targets in an image shot by visual sensors have been studied extensively. The technology of image segmentation plays an important role in such tracking systems. This paper presents a new approach to color image segmentation based on fuzzy color extractor (FCE). Different from many existing methods, the proposed approach provides a new classification of pixels in a source color image which usually classifies an individual pixel into several subimages by fuzzy sets. This approach shows two unique features: the spatial proximity and color similarity, and it mainly consists of two algorithms: CreateSubImage and MergeSubImage. We apply the FCE to segment colors of the test images from the database at UC Berkeley in the RGB, HSV, and YUV, the three different color spaces. The comparative studies show that the FCE applied in the RGB space is superior to the HSV and YUV spaces. Finally, we compare the segmentation effect with Canny edge detection and Log edge detection algorithms. The results show that the FCE-based approach performs best in the color image segmentation. |
| format | Article |
| id | doaj-art-de1febda7d0f4879a7108826adadd900 |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-de1febda7d0f4879a7108826adadd9002025-02-03T01:26:40ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552017-01-01201710.1155/2017/73474217347421Visual Sensor Based Image Segmentation by Fuzzy Classification and Subregion MergeHuidong He0Xiaoqian Mao1Wei Li2Linwei Niu3Genshe Chen4School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, ChinaSchool of Electrical and Information Engineering, Tianjin University, Tianjin 300072, ChinaDepartment of Computer & Electrical Engineering and Computer Science, California State University, Bakersfield, CA 93311, USADepartment of Math and Computer Science, West Virginia State University, Institute, WV 25112, USAIntelligent Fusion Technology, Inc., Germantown, MD 20876, USAThe extraction and tracking of targets in an image shot by visual sensors have been studied extensively. The technology of image segmentation plays an important role in such tracking systems. This paper presents a new approach to color image segmentation based on fuzzy color extractor (FCE). Different from many existing methods, the proposed approach provides a new classification of pixels in a source color image which usually classifies an individual pixel into several subimages by fuzzy sets. This approach shows two unique features: the spatial proximity and color similarity, and it mainly consists of two algorithms: CreateSubImage and MergeSubImage. We apply the FCE to segment colors of the test images from the database at UC Berkeley in the RGB, HSV, and YUV, the three different color spaces. The comparative studies show that the FCE applied in the RGB space is superior to the HSV and YUV spaces. Finally, we compare the segmentation effect with Canny edge detection and Log edge detection algorithms. The results show that the FCE-based approach performs best in the color image segmentation.http://dx.doi.org/10.1155/2017/7347421 |
| spellingShingle | Huidong He Xiaoqian Mao Wei Li Linwei Niu Genshe Chen Visual Sensor Based Image Segmentation by Fuzzy Classification and Subregion Merge Journal of Electrical and Computer Engineering |
| title | Visual Sensor Based Image Segmentation by Fuzzy Classification and Subregion Merge |
| title_full | Visual Sensor Based Image Segmentation by Fuzzy Classification and Subregion Merge |
| title_fullStr | Visual Sensor Based Image Segmentation by Fuzzy Classification and Subregion Merge |
| title_full_unstemmed | Visual Sensor Based Image Segmentation by Fuzzy Classification and Subregion Merge |
| title_short | Visual Sensor Based Image Segmentation by Fuzzy Classification and Subregion Merge |
| title_sort | visual sensor based image segmentation by fuzzy classification and subregion merge |
| url | http://dx.doi.org/10.1155/2017/7347421 |
| work_keys_str_mv | AT huidonghe visualsensorbasedimagesegmentationbyfuzzyclassificationandsubregionmerge AT xiaoqianmao visualsensorbasedimagesegmentationbyfuzzyclassificationandsubregionmerge AT weili visualsensorbasedimagesegmentationbyfuzzyclassificationandsubregionmerge AT linweiniu visualsensorbasedimagesegmentationbyfuzzyclassificationandsubregionmerge AT genshechen visualsensorbasedimagesegmentationbyfuzzyclassificationandsubregionmerge |