Identification of the object motion trajectory in a digital image using the Kalman filter

Abstract

The paper concerns identification of the object motion trajectories in a digital image. An image analysis procedure was used consisting of two methods: BLOB identification and Kalman filter. BLOB identification is the superior method, and the Kalman filter is an alternative one, used to determine the motion trajectories only in the event of incorrect BLOB identification. Data from the correct BLOB identification are used on an ongoing basis in the process of training the Kalman filter. In this way, the filter becomes a model of a physical object that allows predicting the future state based on the object's current behaviour. The use of two complementary image analysis methods allows to determine the motion trajectories of the object's characteristic points in conditions of uneven scene lighting. The effectiveness of the method was confirmed in experimental rests.