Hi,i am dealing with a project in which i have to detect the defected Rice grains from a sample of rice.I want to do segmentation to seprate the defected rice grains and then find the ratio of defect in the sample.kindly help me.
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Image Analyst
le 24 Déc 2017
Which ones are defective?
What I'd do is to first take a "blank shot" of just the white background, then divide that out to remove any dependencies of the non-uniform background illumination and shading. See attached background correction demo.
Then I'd threshold to find the rice grains.
binaryImage = grayImage < someThreshold;
You might want to call bwareafilt() or bwareopen() to get rid of small noise pixels
binaryImage = bwareaopen(binaryImage, 30);
Then I'd get the mean intensity of each grain.
props = regionprops(binaryImage, 'MeanIntensity');
Histogram the mean intensities to see their distribution
allIntensities = [props.MeanIntensity];
histogram(allIntensities);
grid on;
xlabel('Mean Intensity');
ylabel('Count');
Presumably you can determine defective grains based on their mean intensity. Give that code a try and come back if you need any more help.
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Ankit Rathore
le 9 Fév 2022
Have you got the answer zeeshan Ahmed. I need your help and i am wirking in a similar project. Please let me know how can i reach you.
Image Analyst
le 9 Fév 2022
@Ankit Rathore, yes, he did. He accepted this code as the Answer: https://www.mathworks.com/matlabcentral/answers/374388-hi-i-am-dealing-with-a-project-in-which-i-have-to-detect-the-defected-rice-grains-from-a-sample-of-r#comment_519087
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