Chakrabarty, Dr. AmitabhaKamal, NahidIslam, SubrinaAsad, Al Faysal BinKhatun, Sumaiya2018-01-112018-01-1120172017ID 12201058ID 13301139ID-13101095ID-12201099http://hdl.handle.net/10361/9021Cataloged from PDF version of thesis report.Includes bibliographical references (pages 41-42).This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.Tuberculosis is most common contagious disease. Nowadays, millions of human beings of the world are suffering from it. We will use the most used worldwide method Ziehl-Neelsen stain (ZN-stain) to detect Tuberculosis which is based on sputum examination microscopically. This method needs expert human resources and implicit examination. The main constraints are expertise human,time and cost to implement our process. We will use Thresholding, multi-stage, color-based Bayesian segmentation identified possible ‘Tuberculosis objects’, removed artifacts by shape comparison and color-labeled objects as ‘definite’, ‘possible’ or ‘non-Tuberculosis’, bypassing photomicrographic calibration.In our work, we will use an algorithm based on image processing is developed for identification of Tuberculosis.42 pagesenBRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.TuberculosisInfectious diseaseImage processingAlgorithmZiehl-Neelsen stainThesis