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2012 (Vol. 4, Issue: 24)
Article Information:

Machine Vision Application for Food Quality: A Review

K. Vijayarekha
Corresponding Author:  K. Vijayarekha 

Key words:  Apples, biscuits, corn, cucumber, mushrooms, nuts, oranges, potatoes, rice, strawberries, wheat
Vol. 4 , (24): 5453-5458
Submitted Accepted Published
March 18, 2012 April 23, 2012 December 15, 2012

This study aims at discussing various methods of machine vision approaches incorporated for finding the food quality. Automatic grading and sorting of food materials like fruits, vegetables and food grains is gaining importance with the advent of machine vision technology which is a Non Destructive Testing method. It incorporates image processing techniques. The image processing steps for machine vision applications for determining the quality of food products include image acquisition, image preprocessing, image segmentation, image feature extraction and defect classification. Even though images can be taken in all the bands of the electromagnetic spectrum, only a few are used for defect classification using the captured images. If the external surface defects are the main concern, then images captured with Charge Coupled Device (CCD) cameras taken in the visible regions like images taken with monochrome cameras and images taken with color cameras are made use of. If the main concern is on the internal defects, then images taken in Near Infra Red range and X-ray imaging is preferred. Improved results are obtained for multispectral imaging and hyperspectral imaging.
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  Cite this Reference:
K. Vijayarekha, 2012. Machine Vision Application for Food Quality: A Review.  Research Journal of Applied Sciences, Engineering and Technology, 4(24): 5453-5458.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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