Fuzzy Fusion Approach for Object Tracking

In multi-target object tracking, for data fusion, data in presence of noise as input must be sent to fusion center to be filtered, associated, combined and made final decision as output. In the chain, association is very important processing. In this paper, an efficient fuzzy logic data association approach for object tracking is proposed. The proposed approach is developed based on the fuzzy clustering means algorithm, which differs from many other fuzzy logic data association algorithms. Performance evaluation and results are reported, and comparisons with other fuzzy logic approaches based on the results described in other reference are also presented. The efficiency of the new approach has been demonstrated by the fuzzy system performance evaluation.