DocumentCode :
2263766
Title :
Diamond color grading based on machine vision
Author :
Ren, Zhiguo ; Liao, Jiarui ; Cai, Lilong
Author_Institution :
Dept. of Mech. Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, China
fYear :
2009
fDate :
Sept. 27 2009-Oct. 4 2009
Firstpage :
1970
Lastpage :
1976
Abstract :
This paper presents an effective method for diamond color grading based on machine vision. In order to acquire satisfactory diamond images, a special light source based on an integrating sphere is employed. After compensating the fluctuation of the light source, the compositive color features, including independent and joint distribution features of Hue and Saturation, are extracted in segmented uniform regions. Then, depending on a trained BP Neural Network, diamonds can be graded by color. Experiment results show that the proposed method can reach a satisfactory accuracy to replace manual grading for real diamonds. The proposed method can also be used to classify other objects by small color difference.
Keywords :
backpropagation; computer vision; feature extraction; image colour analysis; image segmentation; neural nets; compositive color features; diamond color grading; diamond images; independent distribution features; joint distribution features; machine vision; segmented uniform regions; special light source; trained BP neural network; Charge coupled devices; Fluctuations; Focusing; Image segmentation; Light sources; Machine vision; Mechanical engineering; Neural networks; Optical modulation; Optical refraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-4244-4442-7
Electronic_ISBN :
978-1-4244-4441-0
Type :
conf
DOI :
10.1109/ICCVW.2009.5457523
Filename :
5457523
Link To Document :
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