Freshwater Microalage Image Identification and Classification Based on Machine Learning Technique

Abstract

Algae is an aquatic organism of an enormous and diverse group, which has the ability to conduct photosynthesis. The various sorts of microalgae play trivial roles in marine and fresh water environment. Microalgae are of various sizes and shapes, ranging from unicellular to multicellular forms. These algae were from the division of Anabaena, Oscillatoria, Microcystis Scenedesmus, Pediastrum and Cosmarium found in fresh water lake. In very high density these microalgae may discolor the water, outcompete, and become poisonous to other life forms. This is technically termed as harmful algal blooms. It is one of the most serious water pollution problems. Today, humans in many ways to use microalgae’s for example, as fertilizers, soil conditioners, and livestock feed. A hybrid method is apply to automatic detection and recognition of some selected freshwater algae genera by combining the image processing technique with ANN approaches. Thus, analysis and prediction of algae is significant, which can be achieved using machine learning processing.