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