Automatic fish counting system for noisy deep-sea videos

In this paper, we present a non-invasive method of counting fish in their natural habitat using automated analysis of video data. Our approach uses three modular components to preprocess, detect, and track the fish. The preprocessing reduces noise present in the image while enhancing the fish using several different techniques. The fish detection is based on two background subtraction algorithms which are computed independently and later combined with logical operations. The tracking is then carried out by a heuristic blob tracking algorithm. The paper presents a description of the proposed counting method as well as its experimental validation.