TY - JOUR T1 - Moving object tracking in video by using fuzzy particle swarm optimization algorithm TT - ردیابی شی متحرک در ویدیو با استفاده از الگوریتم بهینه‎ سازی ازدحام ذرات به صورت فازی JF - joc-isice JO - joc-isice VL - 14 IS - 4 UR - http://joc.kntu.ac.ir/article-1-672-en.html Y1 - 2021 SP - 67 EP - 79 KW - Object tracking KW - Improved particle swarm optimization algorithm KW - Weighted color histogram feature. N2 - Nowadays, one of the most fundamental processes for realization video of contents is the object tracking, in which the process of location the moving object is performed in each video frame. In tracking process, the target must be described by a feature. In this paper, for the purpose of describing the target and removing the appearance sensitivity, the weighted color histogram is used as a target feature in order to reduce the effect of edge pixels on the target feature. This reduces the sensitivity of the algorithm to change deformation, scale variation and rotation, as well as the occlusion on the description of target feature. In the proposed method, particle swarm optimization algorithm has been used for search process. Maximization of the similarity function and calculating the minimum Bhattacharyya distance are used to determine target location. The fuzzy control parameters are used for the particle swarm optimization algorithm, which provides a novel method, which can regulate each control parameter and update according to the different states of each particle in each generation. The improved particle swarm algorithm is evaluated with 11 benchmark functions. The obtained results by improved algorithm show that appropriate convergence in a low number of iterations. The proposed method compared to state-of-the-art methods provides high performance in the success and precision rate on the OTB50 dataset. M3 10.52547/joc.14.4.67 ER -