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Proceedings Paper

Using shape to correct for observed nonuniform color in automated egg grading
Author(s): Filip Feyaerts; Peter Vanroose; Rik Fransens; Luc J. Van Gool
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Paper 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.

Paper Details

Date Published: 4 April 2001
PDF: 9 pages
Proc. SPIE 4301, Machine Vision Applications in Industrial Inspection IX, (4 April 2001); doi: 10.1117/12.420901
Show Author Affiliations
Filip Feyaerts, Katholieke Univ. Leuven (Belgium)
Peter Vanroose, Katholieke Univ. Leuven (Belgium)
Rik Fransens, Katholieke Univ. Leuven (Belgium)
Luc J. Van Gool, ETH Zurich (Belgium)


Published in SPIE Proceedings Vol. 4301:
Machine Vision Applications in Industrial Inspection IX
Martin A. Hunt, Editor(s)

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