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