Automatic Colony Segmentation on Agar Surface by Image Processing

Abstract

The Medium (Petri dish, media, agar plate, petri culture, agar culture) are environments that have been formulated for the growth of microorganisms. These structures which are formed by reproduced microorganisms and can be seen by eye are called colony. Colonies formed on the agar, creating images of different morphological characteristics depending on the microorganism and growth media. Colony counting which is required in many applications in areas such as biotechnology and pathology is boring, time consuming and prone to human error process when the large number of colonies counted by hand. In this article, the sample images collected from dairies in the Marmara region are studied on and segmentation methods for separating images of microorganism colonies which is used in the dairy industry for the determination of microbiological analysis of products, have been investigated by the computer-aided image processing techniques such as Otsu, Multi-Otsu, Color K-Means, Watershed, Gabor Filters, Graph Based, Lossy Compression, Random Walker, Texture Filters with proposed comparison method. It was concluded that existing segmentation methods with appropriate parameters can be used to solve this problem and in comparison to other algorithms, Watersheed segmentation algorithm has better performance values than others.