IJEEDC Automated Feature Extraction In Cotton Leaf Images By Graph Cut Approach

Journal Paper

Paper Title :Automated Feature Extraction In Cotton Leaf Images By Graph Cut Approach

Author :Prashant R. Rothe, Ravindra. V. Kshirsagar

Article Citation :Prashant R. Rothe ,Ravindra. V. Kshirsagar , (2014 ) " Automated Feature Extraction In Cotton Leaf Images By Graph Cut Approach " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 44-48, Volume-2,Issue-12

Abstract : Feature extraction and representation is a decisive step for pattern recognition system. How to extract ideal features that can reflect the inherent content of the images as complete as possible is still a challenging problem in computer vision. Therefore goal of feature extraction is to improve the effectiveness and efficiency of analysis and classification.In this work we present a graph cut based approach for the segmentation of images of diseased cotton leaves.We extract color layout descriptors which can be used for classiﬁcation. The diseases that have been considered are Bacterial Blight, Myrothecium and Alternaria. The testing samples of the images are gathered from CICR Nagpur, cotton fields in Buldhana and Nagpur district. Keywords- Cotton Leaf Diseases, Gaussian Filter, Graph Cut, Color Layout Descriptors.

Type : Research paper

Published : Volume-2,Issue-12


	\|		PDF	\|	Viewed - 83	\|	Published on 2014-12-01

Jan. 2025
Submitted Papers	:	80
Accepted Papers	:	10
Rejected Papers	:	70
Acc. Perc	:	12%
Issue Published	:	141
Paper Published	:	1771
No. of Authors	:	4924

Published : Volume-2,Issue-12

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