Arecanut Classification: - A Computer Vision Approach
Language: English
Published by LAP LAMBERT Academic Publishing, 2017
- Softcover
- New

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- Title
- Arecanut Classification: - A Computer Vision Approach
- Author
- Suresha, M.; Danti, Ajit
- Publisher
- LAP LAMBERT Academic Publishing
- Publication year
- 2017
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 3330062746
- ISBN 13
- 9783330062740
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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About the Author
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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