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Non-invasive Health Status Detection System Using Gabor Filters Based on Facial Block Texture Features

  • Non-invasive Diagnostic Systems
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Abstract

Blood tests allow doctors to check for certain diseases and conditions. However, using a syringe to extract the blood can be deemed invasive, slightly painful, and its analysis time consuming. In this paper, we propose a new non-invasive system to detect the health status (Healthy or Diseased) of an individual based on facial block texture features extracted using the Gabor filter. Our system first uses a non-invasive capture device to collect facial images. Next, four facial blocks are located on these images to represent them. Afterwards, each facial block is convolved with a Gabor filter bank to calculate its texture value. Classification is finally performed using K-Nearest Neighbor and Support Vector Machines via a Library for Support Vector Machines (with four kernel functions). The system was tested on a dataset consisting of 100 Healthy and 100 Diseased (with 13 forms of illnesses) samples. Experimental results show that the proposed system can detect the health status with an accuracy of 93 %, a sensitivity of 94 %, a specificity of 92 %, using a combination of the Gabor filters and facial blocks.

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Abbreviations

SVM:

Support vector machine

LIBSVM:

A library for support vector machines

k-NN:

k-nearest neighbor

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Acknowledgments

This work is supported by the University of Macau (SRG2013-00048-FST) as well as the Science and Technology Development Fund (FDCT) of Macao SAR (FDCT/128/2013/A).

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Authors and Affiliations

  1. Department of Computer and Information Science, University of Macau, Taipa, Macau

    Ting Shu & Bob Zhang

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  1. Ting Shu
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  2. Bob Zhang
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Correspondence to Bob Zhang.

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This article is part of the Topical Collection on Mobile Systems

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Shu, T., Zhang, B. Non-invasive Health Status Detection System Using Gabor Filters Based on Facial Block Texture Features. J Med Syst 39, 41 (2015). https://doi.org/10.1007/s10916-015-0227-1

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  • DOI: https://doi.org/10.1007/s10916-015-0227-1

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