Image understanding in unstructured environment:
In the development of autonomous sensory controlled systems, image understanding of sensory data is a difficult but important topic. Due to the unpredictable and uncertain nature of the environment, current image processing and computer vision approaches are not adequate to provide the capabilities...
Gespeichert in:
| Format: | Elektronisch E-Book |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Singapore
World Scientific Pub. Co.
c1988
|
| Schriftenreihe: | Series in automation
vol. 2 |
| Schlagworte: | |
| Online-Zugang: | FHN01 Volltext |
| Zusammenfassung: | In the development of autonomous sensory controlled systems, image understanding of sensory data is a difficult but important topic. Due to the unpredictable and uncertain nature of the environment, current image processing and computer vision approaches are not adequate to provide the capabilities needed by the systems. Thus, new approaches are required in the overall system design, including sophisticated reasoning processes, uncertainty management and adaptable architectures. This general issue is addressed by Thomas M Strat and Grahame B Smith. Lashon B Booker discusses the Bayesian approach in plausible reasoning for classification of complex ship images based on incomplete and uncertain evidence. Dynamic scene analysis is treated by Seetharaman Gunasekaran and Tzay Y Young. A spherical perspective approach is introduced to overcome some limitations of the current vision systems by Michael Penna and Su-shing Chen. Finally, Markov image models and their pixel-level approaches are extended to global approaches, through Dempster-Shafer and other techniques, by Mingchuan Zhang and Su-shing Chen |
| Beschreibung: | vii, 208 p. ill. (some col.) |
| ISBN: | 9789812812391 |
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| 520 | |a In the development of autonomous sensory controlled systems, image understanding of sensory data is a difficult but important topic. Due to the unpredictable and uncertain nature of the environment, current image processing and computer vision approaches are not adequate to provide the capabilities needed by the systems. Thus, new approaches are required in the overall system design, including sophisticated reasoning processes, uncertainty management and adaptable architectures. This general issue is addressed by Thomas M Strat and Grahame B Smith. Lashon B Booker discusses the Bayesian approach in plausible reasoning for classification of complex ship images based on incomplete and uncertain evidence. Dynamic scene analysis is treated by Seetharaman Gunasekaran and Tzay Y Young. A spherical perspective approach is introduced to overcome some limitations of the current vision systems by Michael Penna and Su-shing Chen. Finally, Markov image models and their pixel-level approaches are extended to global approaches, through Dempster-Shafer and other techniques, by Mingchuan Zhang and Su-shing Chen | ||
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| isbn | 9789812812391 |
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| spelling | Image understanding in unstructured environment edited by Su-shing Chen Singapore World Scientific Pub. Co. c1988 vii, 208 p. ill. (some col.) txt rdacontent c rdamedia cr rdacarrier Series in automation vol. 2 In the development of autonomous sensory controlled systems, image understanding of sensory data is a difficult but important topic. Due to the unpredictable and uncertain nature of the environment, current image processing and computer vision approaches are not adequate to provide the capabilities needed by the systems. Thus, new approaches are required in the overall system design, including sophisticated reasoning processes, uncertainty management and adaptable architectures. This general issue is addressed by Thomas M Strat and Grahame B Smith. Lashon B Booker discusses the Bayesian approach in plausible reasoning for classification of complex ship images based on incomplete and uncertain evidence. Dynamic scene analysis is treated by Seetharaman Gunasekaran and Tzay Y Young. A spherical perspective approach is introduced to overcome some limitations of the current vision systems by Michael Penna and Su-shing Chen. Finally, Markov image models and their pixel-level approaches are extended to global approaches, through Dempster-Shafer and other techniques, by Mingchuan Zhang and Su-shing Chen Image processing / Digital techniques Computer vision Maschinelles Sehen (DE-588)4129594-8 gnd rswk-swf Bildverarbeitung (DE-588)4006684-8 gnd rswk-swf Mustererkennung (DE-588)4040936-3 gnd rswk-swf 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content Bildverarbeitung (DE-588)4006684-8 s Maschinelles Sehen (DE-588)4129594-8 s 2\p DE-604 Mustererkennung (DE-588)4040936-3 s 3\p DE-604 Chen, Su-shing Sonstige oth Erscheint auch als Druck-Ausgabe 9789971504779 Erscheint auch als Druck-Ausgabe 9971504774 Erscheint auch als Druck-Ausgabe 9971504782 http://www.worldscientific.com/worldscibooks/10.1142/0530#t=toc Verlag URL des Erstveroeffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Image understanding in unstructured environment Image processing / Digital techniques Computer vision Maschinelles Sehen (DE-588)4129594-8 gnd Bildverarbeitung (DE-588)4006684-8 gnd Mustererkennung (DE-588)4040936-3 gnd |
| subject_GND | (DE-588)4129594-8 (DE-588)4006684-8 (DE-588)4040936-3 (DE-588)4143413-4 |
| title | Image understanding in unstructured environment |
| title_auth | Image understanding in unstructured environment |
| title_exact_search | Image understanding in unstructured environment |
| title_full | Image understanding in unstructured environment edited by Su-shing Chen |
| title_fullStr | Image understanding in unstructured environment edited by Su-shing Chen |
| title_full_unstemmed | Image understanding in unstructured environment edited by Su-shing Chen |
| title_short | Image understanding in unstructured environment |
| title_sort | image understanding in unstructured environment |
| topic | Image processing / Digital techniques Computer vision Maschinelles Sehen (DE-588)4129594-8 gnd Bildverarbeitung (DE-588)4006684-8 gnd Mustererkennung (DE-588)4040936-3 gnd |
| topic_facet | Image processing / Digital techniques Computer vision Maschinelles Sehen Bildverarbeitung Mustererkennung Aufsatzsammlung |
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