Paper
4 April 2001 Using shape to correct for observed nonuniform color in automated egg grading
Filip Feyaerts, Peter Vanroose, Rik Fransens, Luc J. Van Gool
Author Affiliations +
Proceedings Volume 4301, Machine Vision Applications in Industrial Inspection IX; (2001) https://doi.org/10.1117/12.420901
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States
Abstract
We report on algorithmic aspects for the automated visual quality control for grading of brown eggs. Using RGB color images of four different views of every egg enabled to analyze the entire eggshell. The scene was illuminated using a set of white fluorescent tubes placed in a rectangular grid. After detection and approximation of the egg contour (ellipse fitted), the color was corrected to compensate for the elliptical shape of the eggs. A second order polynomial was fitted through points taken from subsequent horizontal lines inside the egg. Iteration was used to reject outliers (most likely points with visual defects). The shape- corrected intensity was calculated as the signed difference between polynomial and measured value, increased with the average egg intensity. Based on the corrected color, dirt regions like yolk, manure, blood, and red mite spots were segmented from the egg-background. Features based on color and shapes were calculated for every segmented region as the combined space and color moments of zeroth, first and second order. A classifier identified most of the defective eggs. Elimination of false rejects due to mirror reflection of the light tubes on some eggs (segmented because of the different color) is currently under investigation.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Filip Feyaerts, Peter Vanroose, Rik Fransens, and Luc J. Van Gool "Using shape to correct for observed nonuniform color in automated egg grading", Proc. SPIE 4301, Machine Vision Applications in Industrial Inspection IX, (4 April 2001); https://doi.org/10.1117/12.420901
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Cited by 2 scholarly publications.
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KEYWORDS
Image segmentation

Cameras

Visualization

Image processing

Image processing algorithms and systems

Inspection

Data centers

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