文章基本信息

标题：Tuberculosis (TB) Identification In The Ziehl-Neelsen Sputum Sample In NTSC Channel And Support Vector Machine (SVM) Classification
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作者：KUSWORO ADI ; RAHMAD GERNOWO ; ARIS SUGIHARTO 等
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2013
卷号：2
期号：9
页码：5030
出版社：S&S Publications
摘要：Tuberculosis (TB) is an important public health issue in this world. In 1992, World Health Organization (WHO) has determined tuberculosis as Global Emergency. The cause of tuberculosis disease is Mycobacterium tuberculosis. This bacteria is bar shaped and has the quality of acid fast so that it's also kno wn as Acid Fast Bacilli (AFB). In this research, an algorithm to identifying and counting the number of tuberculosis bacteria has developed by microscope imagi ng. Color segmentation is done by way of extracting the Saturation channel of NTSC (Luminance, Hue, saturation) color model. Thresholding process is using Otsu Method. Feature extraction for bacteria shape identification process using two parameters i.e. eccentricity and compactness. The training and object recognition using Support Vector Machine algo rithm. The result of development counting is equal to the manual counting result. This is show that Support Vector Machine is good to be applied in detecting and counting the number of tuberculosis bacteria.
关键词：image processing; tuberculosis bacteria; microscopic; Support Vector Machine.