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The bacteria called Mycobacterium tuberculosis causes the infectious disease Tuberculosis (TB), which affects the lungs most of the times. But it affects any part of the body. There are few diseases which can cause death in some countries, but TB is one among them. Even though several tools are used for TB detection, but most widely used tool is the sputum smear microscopy. The problem with the sputum smear microscopy is that it is a slow process taking more time for TB detection. In addition, most of the countries, including our country, have a shortage of well trained lab technicians, and sometimes the diagnosis may fail as this process requires eye strain and concentration. Automatic TB detection methods are the solution to this problem. In this paper, we will provide a detailed study and analysis on Tuberculosis detection using color image processing and statistical methods. This study infers that the accuracy of algorithms increases considerably for the detection of TB automatically.