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Non-invasive Health Status Detection System Using Gabor Filters Based on Facial Block Texture Features
Shu T.; Zhang B.
2015
Source PublicationJournal of Medical Systems
ISSN1573689X 01485598
Volume39Issue:4Pages:1-8
AbstractBlood 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.
KeywordGabor filter Health status detection Non-invasive Support vector machine Texture feature
DOI10.1007/s10916-015-0227-1
URLView the original
Language英語
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Cited Times [WOS]:5   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
AffiliationUniversidade de Macau
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GB/T 7714
Shu T.,Zhang B.. Non-invasive Health Status Detection System Using Gabor Filters Based on Facial Block Texture Features[J]. Journal of Medical Systems,2015,39(4):1-8.
APA Shu T.,&Zhang B..(2015).Non-invasive Health Status Detection System Using Gabor Filters Based on Facial Block Texture Features.Journal of Medical Systems,39(4),1-8.
MLA Shu T.,et al."Non-invasive Health Status Detection System Using Gabor Filters Based on Facial Block Texture Features".Journal of Medical Systems 39.4(2015):1-8.
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