A proposed scenario to improve the Ncut algorithm in segmentation
In image segmentation, there are many methods to accomplish the result of segmenting an image into k clusters. However, the number of clusters k is always defined before running the process. It is defined by some observation or knowledge based on the application. In this paper, we propose a new scen...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-03-01
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| Series: | Frontiers in Big Data |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fdata.2023.1134946/full |
| _version_ | 1811160788841267200 |
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| author | Nhu Y. Tran Nhu Y. Tran Huynh Trung Hieu Pham The Bao |
| author_facet | Nhu Y. Tran Nhu Y. Tran Huynh Trung Hieu Pham The Bao |
| author_sort | Nhu Y. Tran |
| collection | DOAJ |
| description | In image segmentation, there are many methods to accomplish the result of segmenting an image into k clusters. However, the number of clusters k is always defined before running the process. It is defined by some observation or knowledge based on the application. In this paper, we propose a new scenario in order to define the value k clusters automatically using histogram information. This scenario is applied to Ncut algorithm and speeds up the running time by using CUDA language to parallel computing in GPU. The Ncut is improved in four steps: determination of number of clusters in segmentation, computing the similarity matrix W, computing the similarity matrix's eigenvalues, and grouping on the Fuzzy C-Means (FCM) clustering algorithm. Some experimental results are shown to prove that our scenario is 20 times faster than the Ncut algorithm while keeping the same accuracy. |
| first_indexed | 2024-04-10T06:03:26Z |
| format | Article |
| id | doaj.art-0af1f8601921432083ec8ff0b3e4d92f |
| institution | Directory Open Access Journal |
| issn | 2624-909X |
| language | English |
| last_indexed | 2024-04-10T06:03:26Z |
| publishDate | 2023-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Big Data |
| spelling | doaj.art-0af1f8601921432083ec8ff0b3e4d92f2023-03-03T05:03:48ZengFrontiers Media S.A.Frontiers in Big Data2624-909X2023-03-01610.3389/fdata.2023.11349461134946A proposed scenario to improve the Ncut algorithm in segmentationNhu Y. Tran0Nhu Y. Tran1Huynh Trung Hieu2Pham The Bao3Faculty of Information Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City, VietnamInformation Technology Faculty, Ho Chi Minh City University of Food Industry, Ho Chi Minh City, VietnamFaculty of Information Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City, VietnamInformation Science Faculty, Sai Gon University, Ho Chi Minh City, VietnamIn image segmentation, there are many methods to accomplish the result of segmenting an image into k clusters. However, the number of clusters k is always defined before running the process. It is defined by some observation or knowledge based on the application. In this paper, we propose a new scenario in order to define the value k clusters automatically using histogram information. This scenario is applied to Ncut algorithm and speeds up the running time by using CUDA language to parallel computing in GPU. The Ncut is improved in four steps: determination of number of clusters in segmentation, computing the similarity matrix W, computing the similarity matrix's eigenvalues, and grouping on the Fuzzy C-Means (FCM) clustering algorithm. Some experimental results are shown to prove that our scenario is 20 times faster than the Ncut algorithm while keeping the same accuracy.https://www.frontiersin.org/articles/10.3389/fdata.2023.1134946/fullGPUCPUparallel computingNcutFCM |
| spellingShingle | Nhu Y. Tran Nhu Y. Tran Huynh Trung Hieu Pham The Bao A proposed scenario to improve the Ncut algorithm in segmentation Frontiers in Big Data GPU CPU parallel computing Ncut FCM |
| title | A proposed scenario to improve the Ncut algorithm in segmentation |
| title_full | A proposed scenario to improve the Ncut algorithm in segmentation |
| title_fullStr | A proposed scenario to improve the Ncut algorithm in segmentation |
| title_full_unstemmed | A proposed scenario to improve the Ncut algorithm in segmentation |
| title_short | A proposed scenario to improve the Ncut algorithm in segmentation |
| title_sort | proposed scenario to improve the ncut algorithm in segmentation |
| topic | GPU CPU parallel computing Ncut FCM |
| url | https://www.frontiersin.org/articles/10.3389/fdata.2023.1134946/full |
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