apple defects; bi-colour fruit; colour vision; computer vision; image segmentation
Abstract :
[en] This paper shows how the information enclosed in a colour image of a bi-colour apple can be used to segment defects. A method to segment pixels, based on a Bayesian classification process, is proposed. The colour frequency distributions of the healthy tissue and of the defects were used to estimate the probability distribution of each class. The results showed that most defects, namely bitter pit, fungi attack, scar tissue, frost damages, bruises, insect attack and scab, are segmented. However, russet was sometimes confused with the transition area between ground and blush colour. (C) 1999 Elsevier Science B.V. All rights reserved.
Disciplines :
Agriculture & agronomy Computer science
Author, co-author :
Leemans, Vincent ; Université de Liège - ULiège > Gembloux Agro-Bio Tech > Gembloux Agro-Bio Tech
Magein, Hugo ; Université de Liège - ULiège > Gembloux Agro-Bio Tech > Gembloux Agro-Bio Tech
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