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Statistical Analysis of Tongue Images for Feature Extraction and Diagnostics

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机构: [1]Shenzhen Key Laboratory of Broadband Network and Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China [2]Department of Computer and Information Science, University of Macau, Taipa 853, Macau [3]Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou 510120, China [4]Shenzhen Graduate School, Harbin Institute of Technology, Harbin 150001, China [5]Biometrics Research Center, Department of Computing, The Hong Kong Polytechnic University, Hong Kong
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关键词: Color distribution characteristics tongue color space one-class SVM gamut descriptor color features extraction

摘要:
In this paper, an in-depth analysis on the statistical distribution characteristics of human tongue color that aims to propose a mathematically described tongue color space for diagnostic feature extraction is presented. Three characteristics of tongue color space, i.e., tongue color gamut that defines the range of colors, color centers of 12 tongue color categories, and color distribution of typical image features in the tongue color gamut, are elaborately investigated in this paper. Based on a large database, which contains over 9000 tongue images collected by a specially designed noncontact colorimetric imaging system using a digital camera, the tongue color gamut is established in the CIE chromaticity diagram by an innovatively proposed color gamut boundary descriptor using one-class SVM algorithm. Thereafter, centers of 12 tongue color categories are defined accordingly. Furthermore, color distributions of several typical tongue features, such as red points and petechial points, are obtained to build a relationship between the tongue color space and color distributions of various tongue features. With the obtained tongue color space, a new color feature extraction method is proposed for diagnostic classification purposes, with experimental results validating its effectiveness.

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出版当年[2012]版:
大类 | 2 区 工程技术
小类 | 2 区 计算机:人工智能 2 区 工程:电子与电气
最新[2025]版:
大类 | 1 区 计算机科学
小类 | 1 区 计算机:人工智能 1 区 工程:电子与电气
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出版当年[2011]版:
Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
最新[2023]版:
Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

影响因子: 最新[2023版] 最新五年平均 出版当年[2011版] 出版当年五年平均 出版前一年[2010版] 出版后一年[2012版]

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第一作者机构: [1]Shenzhen Key Laboratory of Broadband Network and Multimedia, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
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