Cashew Kernels Classification using Texture Features

Narendra , V G and Hareesha , K S (2011) Cashew Kernels Classification using Texture Features. International Journal of Machine Intelligence, 3 (2). pp. 45-51. ISSN 0975–9166

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Abstract

Cashew is a commercial commodity that plays a major role in earning foreign currency among export commodities of India. The sub-sector is getting governmental and non-governmental attention due its significance in commercial activities. The brand patent creation of each cashew varies based on cashew kernels is an issue in current periods. 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 use of Cashew. Our objective is to develop a cost-effective way to identify the cashew kernels. Such a system would not only facilitate cashew grading but also serve as a quality control tool for processing facilities such as grading and sorting in export industries like cashew. This paper presents a methodology for identification and classification of cashew kernels white wholes. The texture features are extracted using gray level co-occurrence matrix method. The multilayer feed forward neural network is developed to classify cashew kernels white wholes. An analysis of the efficiency of methodology is found 90%.

Item Type: Article
Uncontrolled Keywords: Cashew kernel, Texture Features, Neural Network.
Subjects: Engineering > MIT Manipal > Computer Science and Engineering
Depositing User: MIT Library
Date Deposited: 04 Feb 2013 10:01
Last Modified: 04 Feb 2013 10:01
URI: http://eprints.manipal.edu/id/eprint/78166

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