Tuberculosis Disease Detection Using Image Processing

Authors(1) :-Rajkumar. M

Tuberculosis is one of the deadliest disease in this world especially in developing countries. Sputum smear microscopy is the main diagnostic tool in developing countries and high burden countries for the detection of tuberculosis. Previous studies shows that the manual screening for sputum smear microscopic images lead to misdiagnosis and false result. Image processing techniques are applied in this research to enhance, segment and classify the sputum smear images for computerized process of tuberculosis bacilli identification. Image processing algorithm which used for sputum smear image include a series of enhancement techniques, segmentation methods and morphological operation. As the non-bacillus objects in sputum smear image can bias the detection, it should be suppressed from the smear image. This paper employs color image segmentation technique for segmenting the tuberculosis bacillus objects from the background. Tuberculosis bacillus objects are segmented from the background in two stages based on color space conversion and k-means clustering to identify the tuberculosis bacilli. The proposed method uses thirteen texture feature extraction and makes the judgement using multi-support vector machine. The experiment result confirmed the superior performance of the proposed method.

Authors and Affiliations

Rajkumar. M
Department of Computer Science, Pondicherry University, Puducherry, India

Image Acquisition, Preprocessing, Segmentation, Feature Extraction, Classification

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Publication Details

Published in : Volume 3 | Issue 3 | March-April 2018
Date of Publication : 2018-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 1012-1020
Manuscript Number : CSEIT1833344
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Rajkumar. M, "Tuberculosis Disease Detection Using Image Processing", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.1012-1020, March-April-2018.
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