A real-time grading method of apples based on features extracted from defects

被引:157
作者
Leemans, V [1 ]
Destain, MF [1 ]
机构
[1] Gembloux Agr Univ, Unite Mecan & Construct, B-5030 Gembloux, Belgium
关键词
grading; classification; machine vision; apples;
D O I
10.1016/S0260-8774(03)00189-4
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
This paper presents a hierarchical grading method applied to Jonagold apples. Several images covering the whole surface of the fruits were acquired thanks to a prototype grading machine. These images were then segmented and the features of the defects were extracted. During a learning procedure, the objects were classified into clusters by k-mean clustering. The classification probabilities of the objects were summarised and on this basis the fruits were graded using quadratic discriminant analysis. The fruits were correctly graded with a rate of 73%. The errors were found having origins in the segmentation of the defects or for a particular wound, in a confusion with the calyx end. (C) 2003 Elsevier Ltd. All rights reserved.
引用
收藏
页码:83 / 89
页数:7
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