Colour image segmentation of tuberculosis bacilli in Ziehl-Neelsen-stained tissue images using moving k-mean clustering procedure

• Published in: AMS2010: Asia Modelling Symposium 2010 - 4th International Conference on Mathematical Modelling and Computer Simulation
• Main Author: Osman M.K.; Saad Z.; Mashor M.Y.; Jaafar H.
• Format: Conference paper
• Language: English
• Published: 2010
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-77955212658&doi=10.1109%2fAMS.2010.51&partnerID=40&md5=72d1225f9e3b11be52cc06aa2e40ad9d

Segmentation of tuberculosis bacilli in Zeihl-Neelsen tissue slide images is a crucial step in computerassisted tuberculosis bacilli detection. In this paper, an automatic colour image segmentation using moving k-mean clustering was proposed. First, initial filter is used to remove the tissues images which remain blue after counterstaining process. After that, moving k-mean clustering using green component of RGB colour model and Rycomponent of C-Y colour model are used to segment the TB bacilli from its undesirable background which also remains red even after decolourization process. Then a 5×5 median filter and region growing was used to eliminate small regions and noises. The proposed methods have been analysed for several TB slide images under various conditions. Experimental results indicate that the proposed techniques were successfully segment TB bacilli from its background. © 2010 IEEE.