Object Tracking Based on Active Contour Model by Neural Fuzzy Network

The computer image object tracking technologies are often applied to various kinds of research fields. It proposes real-time tracking object recognition by contour-based neural fuzzy network. It employs the active contour models and neural fuzzy network method to trace moving objects of the same kind and to record its paths simultaneously. To extract object’s feature vector, it uses contour-based model. The traditional background subtraction and object segmentation algorithms are modified to reduce operation complexity and achieve real-time performance. Finally, it uses the self-constructing neural fuzzy inference network to train and recognize moving objects. The experiment shows it can recognize four moving objects, including a pedestrian etc., exactly. The experiment result shows the precision of this system is more than 90% under objects tracking, and the frame rate is more than 25 frames per second.