Image Processing Based Bacterial Colony Counter

Abstract

Enumeration of Bacterial Colonies is required in many fields such as in clinical diagnosis, biomedical research for prevention of harmful diseases and pharmaceutical industry to avoid contamination of products. Existing Bacterial Colony counter systems count Bacterial Colony manually which is a time consuming, less efficient and tedious process. Hence, automation for counting of bacterial colony was required. The proposed method count these colonies automatically using image processing techniques. This method will provide a greater degree of accuracy in counting of bacterial colonies. Proposed technique takes an image of bacterial colony and converts it into grayscale. Otsu thresholding is applied for segmentation of the image further its conversion into binary image. After that, morphological operations are applied to clean up the image by removing noise and unnecessary pixels. Distance and watershed transformations are applied on the binary image to create partitions among overlapped and joint bacteria. Region properties and labeling information of segmented image is used for counting of bacterial colony.