Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach
Region merging approach is used to reduce over segmented regions produced by region-based image segmentation algorithms. It is performed by merging the over segmented regions progressively to produce the final segmentation as spatially contiguous regions with closed boundaries. Predominantly, region...
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| المؤلف الرئيسي: | |
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| التنسيق: | أطروحة |
| اللغة: | English |
| منشور في: |
2020
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| الوصول للمادة أونلاين: | http://eprints.usm.my/55616/1/Pages%20from%20THESIS%20by%20MOGANA%20cut.pdf |
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my-usm-ep.55616 |
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my-usm-ep.556162022-11-11T02:00:32Z Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach 2020-02 Vadiveloo, Mogana QA75.5-76.95 Electronic computers. Computer science Region merging approach is used to reduce over segmented regions produced by region-based image segmentation algorithms. It is performed by merging the over segmented regions progressively to produce the final segmentation as spatially contiguous regions with closed boundaries. Predominantly, region merging is performed between two neighboring regions solely on a local merging criterion. This may fail most existing region merging approaches to detect large non-homogeneous visual objects that have global semantic similarity but consist of diverse set of over segmented regions. Besides that, improper selection of global feature information by partitional clustering algorithm in turn affects the merging criterion derivation in region merging eventually causing leakages into adjacent visual object regions. Consequently, this thesis aims to solve these two issues by proposing a region merging approach to merge the over segmented regions producing semantic segments of visual objects regions. 2020-02 Thesis http://eprints.usm.my/55616/ http://eprints.usm.my/55616/1/Pages%20from%20THESIS%20by%20MOGANA%20cut.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Komputer (School of Computer Sciences) |
| institution |
Universiti Sains Malaysia |
| collection |
USM Institutional Repository |
| language |
English |
| topic |
QA75.5-76.95 Electronic computers Computer science |
| spellingShingle |
QA75.5-76.95 Electronic computers Computer science Vadiveloo, Mogana Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach |
| description |
Region merging approach is used to reduce over segmented regions produced by region-based image segmentation algorithms. It is performed by merging the over segmented regions progressively to produce the final segmentation as spatially contiguous regions with closed boundaries. Predominantly, region merging is performed between two neighboring regions solely on a local merging criterion. This may fail most existing region merging approaches to detect large non-homogeneous visual objects that have global semantic similarity but consist of diverse set of over segmented regions. Besides that, improper selection of global feature information by partitional clustering algorithm in turn affects the merging criterion derivation in region merging eventually causing leakages into adjacent visual object regions. Consequently, this thesis aims to solve these two issues by proposing a region merging approach to merge the over segmented regions producing semantic segments of visual objects regions. |
| format |
Thesis |
| qualification_name |
Doctor of Philosophy (PhD.) |
| qualification_level |
Doctorate |
| author |
Vadiveloo, Mogana |
| author_facet |
Vadiveloo, Mogana |
| author_sort |
Vadiveloo, Mogana |
| title |
Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach |
| title_short |
Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach |
| title_full |
Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach |
| title_fullStr |
Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach |
| title_full_unstemmed |
Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach |
| title_sort |
hybrid region merging for image segmentation using optimal global feature with global merging criterion approach |
| granting_institution |
Universiti Sains Malaysia |
| granting_department |
Pusat Pengajian Sains Komputer (School of Computer Sciences) |
| publishDate |
2020 |
| url |
http://eprints.usm.my/55616/1/Pages%20from%20THESIS%20by%20MOGANA%20cut.pdf |
| _version_ |
1776101099579637760 |