Share Email Print

Proceedings Paper

Color image processing for date quality evaluation
Author(s): Dah Jye Lee; James K. Archibald
Format Member Price Non-Member Price
PDF $17.00 $21.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Many agricultural non-contact visual inspection applications use color image processing techniques because color is often a good indicator of product quality. Color evaluation is an essential step in the processing and inventory control of fruits and vegetables that directly affects profitability. Most color spaces such as RGB and HSV represent colors with three-dimensional data, which makes using color image processing a challenging task. Since most agricultural applications only require analysis on a predefined set or range of colors, mapping these relevant colors to a small number of indexes allows simple and efficient color image processing for quality evaluation. This paper presents a simple but efficient color mapping and image processing technique that is designed specifically for real-time quality evaluation of Medjool dates. In contrast with more complex color image processing techniques, the proposed color mapping method makes it easy for a human operator to specify and adjust color-preference settings for different color groups representing distinct quality levels. Using this color mapping technique, the color image is first converted to a color map that has one color index represents a color value for each pixel. Fruit maturity level is evaluated based on these color indices. A skin lamination threshold is then determined based on the fruit surface characteristics. This adaptive threshold is used to detect delaminated fruit skin and hence determine the fruit quality. The performance of this robust color grading technique has been used for real-time Medjool date grading.

Paper Details

Date Published: 18 January 2010
PDF: 12 pages
Proc. SPIE 7539, Intelligent Robots and Computer Vision XXVII: Algorithms and Techniques, 75390V (18 January 2010); doi: 10.1117/12.841135
Show Author Affiliations
Dah Jye Lee, Brigham Young Univ. (United States)
James K. Archibald, Brigham Young Univ. (United States)

Published in SPIE Proceedings Vol. 7539:
Intelligent Robots and Computer Vision XXVII: Algorithms and Techniques
David P. Casasent; Ernest L. Hall; Juha Röning, Editor(s)

© SPIE. Terms of Use
Back to Top