Machine Vision Based Bacteria-Colony Counter

Abstract

Machine Vision is an emerging area related to real-time capturing, processing, and analyzing the images for various kinds of scientific and industrial applications. Bacteria counting are required in number of applications in the fields such as Biotechnology,Pathology etc. Manual counting of large number of Bacteria in any of these applications can be a tedious and time consuming process, prone to human errors. This can be automated using Machine Vision concepts. In my thesis, I propose a technique of “Machine Vision based Bacteria Colony Counter” which is based on particle analysis approach that enables to count bacterial colony on a Petri dish. Machine vision based bacteria colony counter allows each plate to be counted with equal efficiency. In the present work the image is captured by IEEE-1394 Digital Camera Prosilica 2.0.1 and processed by vision workstation Compact Vision System- 1450. Configuring the two and optimizing their performance for the above application is one of the major components of this work.