DocumentCode :
1925250
Title :
Eggplant classification using artificial neural network
Author :
Saito, Yasuo ; Hatanaka, Teruyoshi ; Uosaki, K. ; Shigeto, K.
Author_Institution :
Sanda Factory, Mitsubishi Electr., Hyogo, Japan
Volume :
2
fYear :
2003
fDate :
20-24 July 2003
Firstpage :
1013
Abstract :
Recently there have been developed automatic grading and sorting systems for fruits and vegetables. In this paper, eggplant grading system using image processing and artificial neural network is considered. The lighting conditions are discussed for taking color components of the eggplant image effectively. The shape parameters such as length, girth, etc. are measured using image processing. On the other hand, bruises of the eggplants are detected and classified based on the color information by using artificial neural network. Some experimental results are presented for illustration.
Keywords :
agriculture; crops; food processing industry; image classification; image colour analysis; neural nets; object detection; artificial neural network; color information; eggplant classification; eggplant grading system; image processing; lighting conditions; shape parameters; Artificial neural networks; Belts; Computer vision; Data acquisition; Image processing; Length measurement; Performance evaluation; Production facilities; Shape measurement; Sorting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2003. Proceedings of the International Joint Conference on
ISSN :
1098-7576
Print_ISBN :
0-7803-7898-9
Type :
conf
DOI :
10.1109/IJCNN.2003.1223829
Filename :
1223829
Link To Document :
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