State-of-the-Art in Automatic Rice Quality Grading System
6 Pages Posted: 1 Apr 2020
Date Written: March 30, 2020
Rice is regarded as main food for approximately 80% of the Southeast Asia population alone. As most countries attaining self-sufficiency in production of rice, consumer is more concerned for better quality rice. It is very cumbersome task for people to analyse the quality and grading of rice in the market. Quality inspection of rice grains is performed by human inspectors having a visual inspection manually which is neither objective in nature nor effective because many time the outcomes may not be trustworthy due to inexperienced inspectors or man-made errors. So an automatic rice quality grading system is required which can remove the shortcomings of manual quality grading process. In this paper, image processing techniques along with machine as well as computer vision are analysed to review the state-of-the art in automatic quality grading process. Various procedures and methods are considered for the review purpose to analyse the quality of rice grains on the basis of different parameters. The paper focuses on the recent research studies carried out for the development of automated rice quality grading systems using image processing, machine vision, computer vision and other techniques.
Keywords: image processing, neural networks, machine vision, geometrical features, discriminant analysis
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