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An Efficient Method for Quality Analysis of Rice Using Machine Vision System

Rahul Birla and Ajay Pal Singh Chauhan
Electronics and Communication Engineering Department, Sant Longowal Institute of Engineering and Technology Longowal-148106, Punjab, India
Abstract—Agricultural industry is the oldest industry in the world. There are numerous challenges faced by this industry in proper quality analysis. Quality assessment of grains is a very big challenge for a long time. This paper presents a solution for quality assessment and grading of Indian basmati Oryza sativa L variety rice using machine vision and image processing. Basic problem of rice industry for quality assessment is addressed which is traditionally done manually by human inspectors. Machine vision provides an alternative with automated, non-destructive, cost-effective, and fast approach method. Quality analysis is done using computer vision, image analysis and processing as compared to human vision inspection. This paper presents an efficient method for calculating the size of Oryza sativa L rice using machine vision along with detection of chalky and broken rice with improved accuracy compared with human inspectors.

Index Terms—machine vision, quality, image processing, image analysis, Oryza sativa L

Cite: Rahul Birla and Ajay Pal Singh Chauhan, "An Efficient Method for Quality Analysis of Rice Using Machine Vision System," Vol. 6, No. 3, pp. 140-145, August, 2015. doi: 10.12720/jait.6.3.140-145
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