Synopsis
Image segmentation is the process of dividing an image into meaningful objects. Fuzzy connectedness (FC) based methods usually give robust segmentation results. However, most of these methods suffer from the weakness of "leaking through poorly defined boundary segments". One of these methods is the absolute or generalized fuzzy connectivity (GFC) method which has an additional weakness about determining the optimal threshold of the fuzzy connectedness scene. This threshold is usually selected manually rather than being automated. In this proposal, we introduce an algorithm based on GFC method that utilizes both fuzzy connectedness- and boundary-based information inheriting the strength qualities of them both, since they depend on different characteristics, in order to alleviate the previous weaknesses. This algorithm uses an affinity of FC that utilizes both region and boundary-based information. Moreover, it proposes an automatic selection procedure of the threshold parameter. An experiment is performed to quantitatively evaluate the proposed algorithm over a simulated data set of scenes.
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Investigation of Fuzzy Connectedness Based Image Segmentation
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LAP LAMBERT Academic Publishing Mai 2019, 2019
ISBN 10: 6202006897
ISBN 13: 9786202006897
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Image segmentation is the process of dividing an image into meaningful objects. Fuzzy connectedness (FC) based methods usually give robust segmentation results. However, most of these methods suffer from the weakness of 'leaking through poorly defined boundary segments'. One of these methods is the absolute or generalized fuzzy connectivity (GFC) method which has an additional weakness about determining the optimal threshold of the fuzzy connectedness scene. This threshold is usually selected manually rather than being automated. In this proposal, we introduce an algorithm based on GFC method that utilizes both fuzzy connectedness- and boundary-based information inheriting the strength qualities of them both, since they depend on different characteristics, in order to alleviate the previous weaknesses. This algorithm uses an affinity of FC that utilizes both region and boundary-based information. Moreover, it proposes an automatic selection procedure of the threshold parameter. An experiment is performed to quantitatively evaluate the proposed algorithm over a simulated data set of scenes. 132 pp. Englisch. Seller Inventory # 9786202006897
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Investigation of Fuzzy Connectedness Based Image Segmentation
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Farag Tamer HashemTamer Hashem Farag assistant. Prof. at MIS, College of Applied Studies and Community Service, Imam Abdulrahman Bin Faisal University. on leave from Department of Mathematics, Cairo university. He receive his Ph.D. . Seller Inventory # 298499540
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Investigation of Fuzzy Connectedness Based Image Segmentation
Published by
LAP LAMBERT Academic Publishing Mai 2019, 2019
ISBN 10: 6202006897
ISBN 13: 9786202006897
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Image segmentation is the process of dividing an image into meaningful objects. Fuzzy connectedness (FC) based methods usually give robust segmentation results. However, most of these methods suffer from the weakness of 'leaking through poorly defined boundary segments'. One of these methods is the absolute or generalized fuzzy connectivity (GFC) method which has an additional weakness about determining the optimal threshold of the fuzzy connectedness scene. This threshold is usually selected manually rather than being automated. In this proposal, we introduce an algorithm based on GFC method that utilizes both fuzzy connectedness- and boundary-based information inheriting the strength qualities of them both, since they depend on different characteristics, in order to alleviate the previous weaknesses. This algorithm uses an affinity of FC that utilizes both region and boundary-based information. Moreover, it proposes an automatic selection procedure of the threshold parameter. An experiment is performed to quantitatively evaluate the proposed algorithm over a simulated data set of scenes.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 132 pp. Englisch. Seller Inventory # 9786202006897
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Investigation of Fuzzy Connectedness Based Image Segmentation
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ISBN 10: 6202006897
ISBN 13: 9786202006897
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Taschenbuch. Condition: Neu. Investigation of Fuzzy Connectedness Based Image Segmentation | Tamer Hashem Farag (u. a.) | Taschenbuch | 132 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786202006897 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 116832917
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Investigation of Fuzzy Connectedness Based Image Segmentation
Published by
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6202006897
ISBN 13: 9786202006897
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Image segmentation is the process of dividing an image into meaningful objects. Fuzzy connectedness (FC) based methods usually give robust segmentation results. However, most of these methods suffer from the weakness of 'leaking through poorly defined boundary segments'. One of these methods is the absolute or generalized fuzzy connectivity (GFC) method which has an additional weakness about determining the optimal threshold of the fuzzy connectedness scene. This threshold is usually selected manually rather than being automated. In this proposal, we introduce an algorithm based on GFC method that utilizes both fuzzy connectedness- and boundary-based information inheriting the strength qualities of them both, since they depend on different characteristics, in order to alleviate the previous weaknesses. This algorithm uses an affinity of FC that utilizes both region and boundary-based information. Moreover, it proposes an automatic selection procedure of the threshold parameter. An experiment is performed to quantitatively evaluate the proposed algorithm over a simulated data set of scenes. Seller Inventory # 9786202006897