Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/9183
Title: Agricultural produce sorting and grading using support vector machines and fuzzy logic
Authors: Mustafa, N.B.A. 
Ahmed, S.K. 
Ali, Z. 
Yit, W.B. 
Abidin, A.A.Z. 
Md Sharrif, Z.A. 
Issue Date: 2009
Abstract: Agriculture sector was accorded a very different treatment in the Ninth Malaysia Plan (9MP) where this sector is being revitalized to become a part of the economic growth engine. The Information and Communication Technology (ICT) application is going to be implemented as a solution in improving the status of the agriculture sector. The idea of integrating ICT with agriculture sector motivates the development of an automated system for sorting and grading of agriculture produce. Currently, the grading is done based on observations and through experience. The developed system starts the grading process by capturing the fruit's image using a regular digital camera or mobile phone camera. Then, the image is transmitted to the processing level where feature extraction, classification and grading is done using MATLAB. In this paper, the focus is more on agricultural produce Sorting and Grading technique. The agricultural produce is classified based on fruit shape and size using Support Vector Machines (SVMs) and its grade is determined using Fuzzy Logic (FL) approach. The results obtained are very promising.
URI: http://dspace.uniten.edu.my/jspui/handle/123456789/9183
Appears in Collections:COGS Scholarly Publication

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