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Abstract
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Article Information:
Machine Vision Application for Food Quality: A Review
K. Vijayarekha
Corresponding Author: K. Vijayarekha
Submitted: March 18, 2012
Accepted: April 23, 2012
Published: December 15, 2012 |
Abstract:
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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.
Key words: Apples, biscuits, corn, cucumber, mushrooms, nuts, oranges, potatoes, rice, strawberries, wheat
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Cite this Reference:
K. Vijayarekha, . Machine Vision Application for Food Quality: A Review. Research Journal of Applied Sciences, Engineering and Technology, (24): 5453-5458.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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