DocumentCode :
179776
Title :
Silkworm eggs detection and classification using image analysis
Author :
Kiratiratanapruk, K. ; Methasate, I. ; Watcharapinchai, N. ; Sinthupinyo, W.
Author_Institution :
Nat. Electron. & Comput. Technol. Center, Nat. Sci. & Technol. Dev. Agency, Pathumthani, Thailand
fYear :
2014
fDate :
July 30 2014-Aug. 1 2014
Firstpage :
340
Lastpage :
345
Abstract :
Machine vision has been applied to various material inspection processes in agricultural industry in order to achieve fast and accurate operation. In this paper, we propose an image processing technique for silkworm eggs analysis. The proposed technique is able to identify individual egg objects and their types. The proposed technique was implemented and developed into software interface. The software was installed at the Thailand Sericulture center and it is going to be used in the real practical scenario. To evaluate our proposed technique, the approach was evaluated on 60 sample images from 7 shade groups of silkworm´s egg sample. The obtained accuracies are nearly to 90% for various kinds of eggs types in both detection and classification. The results of this study are useful and they are served as an important base for future development of practical quality control technique.
Keywords :
agricultural engineering; automatic optical inspection; image classification; object detection; quality control; Thailand Sericulture center; agricultural industry; egg objects; image analysis; image processing technique; machine vision; material inspection processes; quality control technique; silkworm egg classification; silkworm egg detection; software interface; Accuracy; Color; Computer science; Image color analysis; Object detection; Software; classification; counting; detection; image processing; silkworm egg;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Engineering Conference (ICSEC), 2014 International
Conference_Location :
Khon Kaen
Print_ISBN :
978-1-4799-4965-6
Type :
conf
DOI :
10.1109/ICSEC.2014.6978219
Filename :
6978219
Link To Document :
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