Determination of physical rice composition using image processing technique

Physical rice grain composition is one of the components used for rice grading which involve the identification of head rice and broken rice. Rice grading is important to ensure only edible rice reaches the consumer standard. It also protects consumers from price manipulation. In this paper, a new approach of image processing technique has been developed to detect and identify head and broken rice based on its physical properties i.e. area, perimeter, minor axis length and major axis length. The rice images were first segmented automatically from its background by using Otsu’s method. Connected component analysis was later being applied to eliminate unwanted noise. Results from the statistical analysis have shown that area and perimeter give significant correlations with all of the other properties. Therefore, an area was later used as input parameter in developing a simple model of head and broken rice identification using a linear regression analysis. The model give promising results when tested with 0%, 1%, 5%, 10%, 15% and 20% of broken rice taken from 600 samples of rice images with the average percentage accuracy of 98%. This promising result provides an alternative way to grade rice. The method has an advantage on its simplicity, easy to be used and fast. It does not involve any step-by-step procedure to optimize the criterion and only takes four seconds to complete the operation.

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