Quantitative image morphology
Natural systems undergo several morphological changes with time. To study spatiotemporal dynamics of such natural systems, and to further understand the morphological dynamical behaviors, various images that show several macro- and micro-level phenomena, acquired by various types of sensors need to...
| Main Authors: | , |
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| Format: | Article |
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2003
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| Online Access: | http://shdl.mmu.edu.my/2586/ |
| _version_ | 1848790095394504704 |
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| author | Sagar, , BSD Rao, , CB |
| author_facet | Sagar, , BSD Rao, , CB |
| author_sort | Sagar, , BSD |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | Natural systems undergo several morphological changes with time. To study spatiotemporal dynamics of such natural systems, and to further understand the morphological dynamical behaviors, various images that show several macro- and micro-level phenomena, acquired by various types of sensors need to be analyzed in spatio-temporal scales. Such analyses, to facilitate the researcher to model the spatio-temporal organization of a desired phenomenon, evidently require the robust procedures to extract specific error-free features from multiscale-temporal images represented in discrete space. Geometry and topology based features, such as edges of unique type and general type, are the indicators to record the changes that occur temporally. Extraction of such information is essential prerequisite to develop cogent models to understand the spatio-temporal organization. |
| first_indexed | 2025-11-14T18:07:10Z |
| format | Article |
| id | mmu-2586 |
| institution | Multimedia University |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:07:10Z |
| publishDate | 2003 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-25862011-08-23T07:15:55Z http://shdl.mmu.edu.my/2586/ Quantitative image morphology Sagar, , BSD Rao, , CB QA75.5-76.95 Electronic computers. Computer science Natural systems undergo several morphological changes with time. To study spatiotemporal dynamics of such natural systems, and to further understand the morphological dynamical behaviors, various images that show several macro- and micro-level phenomena, acquired by various types of sensors need to be analyzed in spatio-temporal scales. Such analyses, to facilitate the researcher to model the spatio-temporal organization of a desired phenomenon, evidently require the robust procedures to extract specific error-free features from multiscale-temporal images represented in discrete space. Geometry and topology based features, such as edges of unique type and general type, are the indicators to record the changes that occur temporally. Extraction of such information is essential prerequisite to develop cogent models to understand the spatio-temporal organization. 2003-03 Article NonPeerReviewed Sagar, , BSD and Rao, , CB (2003) Quantitative image morphology. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 17 (2). pp. 163-165. ISSN 0218-0014 |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science Sagar, , BSD Rao, , CB Quantitative image morphology |
| title | Quantitative image morphology |
| title_full | Quantitative image morphology |
| title_fullStr | Quantitative image morphology |
| title_full_unstemmed | Quantitative image morphology |
| title_short | Quantitative image morphology |
| title_sort | quantitative image morphology |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | http://shdl.mmu.edu.my/2586/ |