A Linear Fitting Density Peaks Clustering Algorithm for Image Segmentation
Clustering by fast search and finding of density peaks algorithm (DPC) is a recently developed method and can obtain promising results. However, DPC needs users to determine the number of clusters in advance, thus the clustering results are unstable and deeply influenced by the number of clusters. T...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2018-01-01
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| Series: | Tehnički Vjesnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/298277 |
| _version_ | 1827282873482215424 |
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| author | You Zhou Tiantian Zhao Yizhang Wang Jianan Wu Xu Zhou |
| author_facet | You Zhou Tiantian Zhao Yizhang Wang Jianan Wu Xu Zhou |
| author_sort | You Zhou |
| collection | DOAJ |
| description | Clustering by fast search and finding of density peaks algorithm (DPC) is a recently developed method and can obtain promising results. However, DPC needs users to determine the number of clusters in advance, thus the clustering results are unstable and deeply influenced by the number of clusters. To address this issue, we proposed a novel algorithm, namely LDPC (Linear fitting Density Peaks Clustering algorithm). LDPC uses a novel linear fitting method to choose cluster centres automatically. In the experiments, we use public datasets to access the effectiveness of LDPC. Especially, we applied LDPC to image segmentation tasks. The experimental results show that LDPC can obtain competitive results compared with other clustering algorithms. |
| first_indexed | 2024-04-24T09:25:23Z |
| format | Article |
| id | doaj.art-20c57b5035864cb89f3e1c2a608ff737 |
| institution | Directory Open Access Journal |
| issn | 1330-3651 1848-6339 |
| language | English |
| last_indexed | 2024-04-24T09:25:23Z |
| publishDate | 2018-01-01 |
| publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
| record_format | Article |
| series | Tehnički Vjesnik |
| spelling | doaj.art-20c57b5035864cb89f3e1c2a608ff7372024-04-15T14:53:33ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392018-01-0125380881210.17559/TV-20171125161944A Linear Fitting Density Peaks Clustering Algorithm for Image SegmentationYou Zhou0Tiantian Zhao1Yizhang Wang2Jianan Wu3Xu Zhou4College of Computer Science and Technology, Jilin University, Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, 2699 Qianjin Street, Changchun, 130012, ChinaCollege of Computer Science and Technology, Jilin University, 2699 Qianjin Street, Changchun, 130012, ChinaCollege of Computer Science and Technology, Jilin University, 2699 Qianjin Street, Changchun, 130012, ChinaCollege of Computer Science and Technology, Changchun University, 6543 Weixing Road, Changchun 130022, ChinaCollege of Computer Science and Technology, Jilin University / Center for Computer Fundamental Education, Jilin University, 2699 Qianjin Street, Changchun, 130012, ChinaClustering by fast search and finding of density peaks algorithm (DPC) is a recently developed method and can obtain promising results. However, DPC needs users to determine the number of clusters in advance, thus the clustering results are unstable and deeply influenced by the number of clusters. To address this issue, we proposed a novel algorithm, namely LDPC (Linear fitting Density Peaks Clustering algorithm). LDPC uses a novel linear fitting method to choose cluster centres automatically. In the experiments, we use public datasets to access the effectiveness of LDPC. Especially, we applied LDPC to image segmentation tasks. The experimental results show that LDPC can obtain competitive results compared with other clustering algorithms.https://hrcak.srce.hr/file/298277clusteringdensity peaksimage segmentationlinear fitting |
| spellingShingle | You Zhou Tiantian Zhao Yizhang Wang Jianan Wu Xu Zhou A Linear Fitting Density Peaks Clustering Algorithm for Image Segmentation Tehnički Vjesnik clustering density peaks image segmentation linear fitting |
| title | A Linear Fitting Density Peaks Clustering Algorithm for Image Segmentation |
| title_full | A Linear Fitting Density Peaks Clustering Algorithm for Image Segmentation |
| title_fullStr | A Linear Fitting Density Peaks Clustering Algorithm for Image Segmentation |
| title_full_unstemmed | A Linear Fitting Density Peaks Clustering Algorithm for Image Segmentation |
| title_short | A Linear Fitting Density Peaks Clustering Algorithm for Image Segmentation |
| title_sort | linear fitting density peaks clustering algorithm for image segmentation |
| topic | clustering density peaks image segmentation linear fitting |
| url | https://hrcak.srce.hr/file/298277 |
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