抄録
This research is concerned with a fish tracking system. which employs the raw-image (unprocessed gray-scale image) of a scene. a global/local search of a genetic algorithm (GA) in combination with a models shaping the target of known shape. This GA is used in order to improve the real-time tracking performance of a manipulator directed toward the target of unpredictable movement. The raw-image is used since it does not increase the original noise. and moreover does not require any filtering processing time. The global search feature of the (GA) is used as a pre-processor for the search of a target together with a GA-based local search technique that focuses on interesting points find by the pre-processor in order to perform an intensive local search. The local GA search relies on a mutation technique of positional and orientational bit-strings in order to improve the GA-based scene recognition performance in terms of fast and reliable recognition of a target so as to increase the tracking performance. In order to evaluate the effectiveness of the proposed fish tracking strategy experiments have been performed using a 6-DOF manipulator and a fish in its natural scene. The results have shown the effectiveness of the proposed method.
