DocumentCode
133387
Title
Non-destructive identification of breeder rice Seed using transparent image analysis
Author
Auttawaitkul, Yingrak ; Buochareon, Sermsuk ; Maneechukate, Thongchai ; Dussadee, Natthawud
Author_Institution
Sch. of Renewable Energy, Maejo Univ., Sansai, Thailand
fYear
2014
fDate
5-8 March 2014
Firstpage
1
Lastpage
4
Abstract
In this paper, The transparent digital image analysis is applied for non-destructive identification of breeder seed class. The Rice Research Center and Development, Thailand difficult task is a classification breeder rice seed because of the similar shape and surface color. This paper presents the appropriate frequency light shines through to the grain that is analyzed for the histogram RGB and the separation by color property categories automatically. The rule of RGB histogram classification in `Jasmine´ rice seed and sticky rice seed are almost 97% and in “Red Sukhothai 1” red colored rice seed and dark-red colored rice seed almost 88% of rice seeds are identified correctly. In the light shines frequency appropriate to the grain that is analyzed the histogram RGB can be isolated red, white or yellow rice seeds are identified correctly 91%.
Keywords
agricultural products; image classification; image colour analysis; Jasmine rice seed; RGB histogram classification; Thailand; breeder rice seed classification; dark-red colored rice seed; nondestructive identification; red colored rice seed; red sukhothai 1; rice research center and development; shape similarity; sticky rice seed; surface color; transparent digital image analysis; white rice seeds; yellow rice seeds; Digital images; Histograms; Image analysis; Image color analysis; Image edge detection; Light sources; Shape; RGB color model; breeder rice seed; digital image processing; light frequency; non-destructive;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Communication Technology, Electronic and Electrical Engineering (JICTEE), 2014 4th Joint International Conference on
Conference_Location
Chiang Rai
Print_ISBN
978-1-4799-3854-4
Type
conf
DOI
10.1109/JICTEE.2014.6804100
Filename
6804100
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