Classification of Beneficial and non-Beneficial Bacteria using Random Forest Algorithm

Contaminated water released from factories and other sources leads to the production of harmful bacteria, which at a later stage could lead to dangerous diseases. Classification and detection of bacteria should be carried out. It is known from the literature review that this can be done by using test tube testing, microscope model, spectrum light using spectroscope, but it is more costly, not affordable everywhere, complex and takes longer to achieve results. So, unlike other models, by using an efficient algorithm suitable for the system, an image processing system can be efficient and successful in producing results very quickly, with not much of a hassle in the process. By extracting its multiple features such as scale, shape, texture, color, size and other characteristics such as arrangement of the hair around her body, classification will be performed over images. The framework extracts the characteristics and categorizes the type of bacteria that can be understood whether or not it is a beneficial bacterium for humans and nature.