Fish Movement Tracking Menggunakan Metode Gaussian Mixture Models (GMM) dan Kalman Filter

Indonesia Fish industries is one of the large in the world for market capital which covers for both natural growing and intensive culture. One part of the most challenging problem for intensive culture is related to counting when harvesting which been done by hand all this time. In order to be more efficient, we propose this task can be done through automation with Gussian Mixture Model. The proposed system proven been able with low error rate that also resulting close estimate of fish object counting giiven various background videos.