Sinopsis
The arecanut palm bearing the scientific name Areca Catechu Linn and included in the tribe Arecae of the family palmae. The palm owes its rating of importance to the fruits known as the arecanut, which forms the principal chewing material in India and in the far eastern countries. Arecanut is almost symbolic of the great culture of some of the oriented nations especially Indians and Indonesians. Color and texture of arecanut are the most important parameters that allows for the evaluation of their degree of quality, and existence of faults and also color along with its level of homogeneity influences the degree of acceptance of consumers, as well as the pricing.Human has a prominent role in classification of arecanut.This leads to time consuming, expensive for labour and inconsistency in classification. Computer vision based technology is required to address the above problem. Color features are the dominant features for classification of arecanut with husk. Texture features are dominant features in classification of arecanut without husk.
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Acerca del autor
Dr. Suresha M received the Master of Computer Applications degree and Ph. D in Computer Science from the Kuvempu University, India in 2003 and 2014 respectively. His research is focused on Image processing and Pattern Recognition. He has 14 years of experience in various capacities such as Teaching, Industry, Administration and Research.
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Arecanut Classification
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LAP LAMBERT Academic Publishing Mrz 2017, 2017
ISBN 10: 3330062746
ISBN 13: 9783330062740
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The arecanut palm bearing the scientific name Areca Catechu Linn and included in the tribe Arecae of the family palmae. The palm owes its rating of importance to the fruits known as the arecanut, which forms the principal chewing material in India and in the far eastern countries. Arecanut is almost symbolic of the great culture of some of the oriented nations especially Indians and Indonesians. Color and texture of arecanut are the most important parameters that allows for the evaluation of their degree of quality, and existence of faults and also color along with its level of homogeneity influences the degree of acceptance of consumers, as well as the pricing.Human has a prominent role in classification of arecanut.This leads to time consuming, expensive for labour and inconsistency in classification. Computer vision based technology is required to address the above problem. Color features are the dominant features for classification of arecanut with husk. Texture features are dominant features in classification of arecanut without husk. 140 pp. Englisch. Nº de ref. del artículo: 9783330062740
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Arecanut Classification: - A Computer Vision Approach
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ISBN 13: 9783330062740
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Arecanut Classification
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Suresha M.Dr. Suresha M received the Master of Computer Applications degree and Ph. D in Computer Science from the Kuvempu University, India in 2003 and 2014 respectively. His research is focused on Image processing and Pattern Recog. Nº de ref. del artículo: 151235611
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Arecanut Classification: - A Computer Vision Approach
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Arecanut Classification: - A Computer Vision Approach
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Arecanut Classification
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The arecanut palm bearing the scientific name Areca Catechu Linn and included in the tribe Arecae of the family palmae. The palm owes its rating of importance to the fruits known as the arecanut, which forms the principal chewing material in India and in the far eastern countries. Arecanut is almost symbolic of the great culture of some of the oriented nations especially Indians and Indonesians. Color and texture of arecanut are the most important parameters that allows for the evaluation of their degree of quality, and existence of faults and also color along with its level of homogeneity influences the degree of acceptance of consumers, as well as the pricing.Human has a prominent role in classification of arecanut.This leads to time consuming, expensive for labour and inconsistency in classification. Computer vision based technology is required to address the above problem. Color features are the dominant features for classification of arecanut with husk. Texture features are dominant features in classification of arecanut without husk.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 140 pp. Englisch. Nº de ref. del artículo: 9783330062740
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Arecanut Classification : A Computer Vision Approach
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LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330062746
ISBN 13: 9783330062740
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The arecanut palm bearing the scientific name Areca Catechu Linn and included in the tribe Arecae of the family palmae. The palm owes its rating of importance to the fruits known as the arecanut, which forms the principal chewing material in India and in the far eastern countries. Arecanut is almost symbolic of the great culture of some of the oriented nations especially Indians and Indonesians. Color and texture of arecanut are the most important parameters that allows for the evaluation of their degree of quality, and existence of faults and also color along with its level of homogeneity influences the degree of acceptance of consumers, as well as the pricing.Human has a prominent role in classification of arecanut.This leads to time consuming, expensive for labour and inconsistency in classification. Computer vision based technology is required to address the above problem. Color features are the dominant features for classification of arecanut with husk. Texture features are dominant features in classification of arecanut without husk. Nº de ref. del artículo: 9783330062740
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Arecanut Classification | - A Computer Vision Approach
Publicado por
LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330062746
ISBN 13: 9783330062740
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Taschenbuch. Condición: Neu. Arecanut Classification | - A Computer Vision Approach | M. Suresha (u. a.) | Taschenbuch | 140 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330062740 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Nº de ref. del artículo: 108830651
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