In multiple objects tracking it become difficult to track the objects when they get cluttered due to proximity of the object. Such a cluttered environment leads to misleading target tracking in video analysis. This becomes important when video system is employed for security purpose or behavior analysis of the object. The object get merged and split due to occlusion or obstacles in viewing angle of the camera. In this paper we present the novel algorithm to handle issue of split and merge of the objects. To increase the robustness, association rules for object tracking are proposed. The algorithm tracks number of objects by keeping record of the split and merge of these objects with each other. Association rules are developed to track the multiple objects from frame to frame. Due to association rule application processing time increases when objects are merged or split, otherwise time required is same as normal object detection condition. In order to save the memory requirement for association of objects from frame to frame, linked list structure is implemented, which will expand and collapse as number of objects changes in given video frame. Object descriptors are stored as one node of the linked list along with object ID and flags indicating split and merge of objects. This list is updated as the video frames progresses for tracking of the objects. Such a system shows good result while tracking the multiple objects in cluttered environment due to shadow or occlusion or overlapping with in a frame.
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