Mobile application for automatic bacterial density estimation - Taithong, Phongsatorn; Wichai, Siriwan; Waranusast, Rattapoom; Riyamongkol, Panomkhawn (Asian Health, Science and Technology Reports, 2023)
The traditional method for calculating the concentration of viable bacteria in a pure source is to use serial dilutions. This conventional method takes more than 72 hr and involves a series of complex steps that must be done by a microbiologist, including culturing the colonies. In contrast, this study utilizes a combination of image processing and machine learning developed into a mobile application that can estimate the concentration of viable bacteria by simply taking a picture, substantially reducing the time required. To create this new estimation model, a series of image processing techniques optimize and standardize a dataset of photographed test tubes containing pure bacterial suspension, culminating in the delimiting of the Turbidity Testing Zone (TTZ), which is uniform across all the test tube photos. Bacterial concentration is correlated with suspension turbidity, so statistical data from the pixels within the TTZ is analyzed using four machine learning algorithms to find the optimal estimating model. The finished model becomes the foundation of the Viable Bacteria Image Estimating System (VBIES) android application, which enables any user to easily and conveniently determine the concentration of viable bacteria in a test tube with an accuracy of 97.57%. In contrast to the several days required by the traditional methods, the VBIES application estimates the concentration of viable bacteria in only 3-5 seconds.