Author：
Lu, Yunxi
(Lu, Yunxi.)
|
Li, Xiaoguang
(Li, Xiaoguang.)
|
Zhuo, Li
(Zhuo, Li.)
|
Zhang, Jing
(Zhang, Jing.)
|
Zhang, Hui
(Zhang, Hui.)
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Abstract：
In Traditional Chinese Medicine (TCM), tongue inspection is one of the most important diagnostic means. Due to the limitations of capturing devices and variations in lighting conditions, there are color distortions between the captured tongue images and the actual human visual perceived. In this paper, we proposed a Deep Color Correction Network (DCCN) to learn the mapping model between the captured distorted color images and the target visually perceived color appearance under different lighting conditions and provides the color consistency across different cameras or capture deceives. Experimental results show that the DCCN model can achieve high accuracy and robustness in both of the objective and subjective tongue image color correction metrics. © 2018 IEEE.
Keyword：
Color
Color image processing
Diagnosis
Lighting
Reprint Author's Address：
Conference Name
2018 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2018
Place
San Diego, CA, United states
Classification
461.6 Medicine and Pharmacology - 741.1 Light/Optics
Type
_________________________ The work in this paper is supported by BJUT United Grand Scientific Research Program on Intelligent Manufacturing. The work in this paper is supported by the National Natural Science Foundation of China (No. 61471013, No. 61531006, No.61602018, and No.61701011), the Science and Technology Development Program of Beijing Education Committee (No. KM201510005004), the Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions (No.CIT&TCD20150311) and the RiXin＂ Talent Project of Beijing University of Technology.＂
Access Number
EI:20190306389794
Corresponding authors email
