Underwater Marine Life Detection Using Image Processing

Marine life research and computer technology have been utilized in tandem for the study of aquatic ecosystems and the analysis of ocean floors throughout the last few decades. Few modern solutions have been offered in this field in recent years. The work in object detection and recognition based on machine learning models have given good information about the surroundings and behavior of marine ecosystems. These models are complex in usage, they often rely on the information source from multiple data forms. The major task is to remove the high impurities in underwater images as the noise removal process is difficult. The image extraction is carried out using darknet which helps in proper object detection. Due to this, the actual applications and study of marine life is realized easily. A suitable environment will be created so that machine learning algorithms such as YOLO will be used to detect and recognize the animals under the ocean with the help of image processing.