An image-processing based automated bacteria colony counter

This paper presents an image processing based automated counting system to detect the number of bacteria colonies that develop in Petri dishes of microbiology laboratories. The visible colonies represent the initial number of bacteria present in the aqueous environment. The counting system contains shape based segmentation and classification algorithms. Colonies are considered as (possibly overlapping with some amount of amorphous deviations from) discs and classified as a cluster of bacteria with respect to their compactness ratio. The system is implemented using Matlab, and tested using ground truth data provided from Anadolu University, Dept. of Environmental Engineering microbiology laboratory. Results are presented.