Narendra, V G and Hareesha, K S (2011) Cashew Kernels Classification using Colour Features. International Journal of Machine Intelligence, 3 (2). pp. 52-57. ISSN 0975–9166

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Abstract

Cashew is a commercial commodity that plays a major role in earning foreign revenue among export commodities in India. The purpose of this research work is to explore image processing techniques and approaches on Indian cashew variety identification based on their kernels. Colour is an important quality factor for grading, marketing, and end users. Our primary objective is to develop a cost-effective intelligent model to identify the cashew kernels. Colour features in the RGB (red-green-blue) colour space are extracted and computed. A feed-forward neural network is trained to classify sample cashew kernels. An intelligent classification system based on computer vision system can be developed for automated grading and sorting to speed up the classification of cashew kernels. This will solve the major problems of many of the cashew export industries also, gives justice to the cashew growing farmers in accurate grading. The classification system is evaluated on cashew kernels of 6 different grades. The result of our study shows that, the system gives about 80% classification rate.

Item Type:	Article
Uncontrolled Keywords:	Image Processing, colour features, cashew kernel, grading, Neural Network.
Subjects:	Engineering > MIT Manipal > Computer Science and Engineering
Depositing User:	MIT Library
Date Deposited:	04 Feb 2013 11:27
Last Modified:	28 Sep 2015 11:41
URI:	http://eprints.manipal.edu/id/eprint/78167

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