NDLI: Recognize and analysis the healthy person's facial color diagnosis

Content Provider	IEEE Xplore Digital Library
Author	Zhifeng Zhang Jiatuo Xu Ming Li Jingbo Lu Hongchao Mao Meiyu Shi Liping Tu Fenglan Zhu
Copyright Year	2009
Description	Author affiliation: Shanghai University of Traditional Chinese Medicine, 201203, China (Zhifeng Zhang; Jiatuo Xu; Ming Li; Jingbo Lu; Meiyu Shi; Liping Tu; Fenglan Zhu) \|\| Xiamen University, 361005, China (Hongchao Mao)
Abstract	We fetch facial digital vision information from 98 healthy persons using digital camera. With functional help of NIKON CAPTURE NX's software point U key technology, we catch black, white and neutral color control points. We correct the color differences of facial digital vision with self-improved facial functional software. According to the principle of Adaboost objective category, we improve the software. Under Traditional Chinese Medicine (TCM), facial information was cut into 5 divisions which are forehead, nose, left malar, right malar and chin. We do the CIE1976Lab* color quantity analysis using after we take 8 color pieces with size 55 from each part. The experiment result shows that there are differences of value of L, a* and b* from different part of healthy persons face. That means there are color differences from different part of face. With the figures of L, a and b* from different face part, it generally follows the TCM clinic fact. This task technologically found the patients facial inspection in future.
Starting Page	66
Ending Page	69
File Size	132073
Page Count	4
File Format	PDF
ISBN	9781424439287
DOI	10.1109/ITIME.2009.5236459
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Forehead Image color analysis Face recognition Nose Software quality Inspection Digital cameras Medical diagnostic imaging Information analysis Biomedical imaging
Content Type	Text
Resource Type	Article

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