An extensive analysis of various texture feature extractors to detect Diabetes Mellitus using facial specific regions.

Journal: Computers in biology and medicine

Published Date: Feb 22, 2017

Abstract

INTRODUCTION: Researchers have recently discovered that Diabetes Mellitus can be detected through non-invasive computerized method. However, the focus has been on facial block color features. In this paper, we extensively study the effects of texture features extracted from facial specific regions at detecting Diabetes Mellitus using eight texture extractors.

Authors

Ting Shu

Department of Computer and Information Science, University of Macau, Taipa, Macau, mb35455@umac.mo.
Bob Zhang
Yuan Yan Tang

Department of Computer and Information Science, Avenida da Universidade, University of Macau, Taipa, Macau, China. Electronic address: yytang@umac.mo.

Keywords

Algorithms Colorimetry Diabetes Mellitus Humans Image Interpretation, Computer-Assisted Pattern Recognition, Automated Photography Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted Support Vector Machine

External Resources

View on PubMed Access via DOI PubMed (28237906)

An extensive analysis of various texture feature extractors to detect Diabetes Mellitus using facial specific regions.

Abstract

Authors

Keywords

External Resources

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