On the development of moving object detection from traditional to fuzzy based techniques

Moving object detection or background subtraction is considered to be one of the active area of research in the field of computer vision. Background subtraction is a key module in moving object detection. It is the process of separating background from the captured frame. The fundamental method of detecting a moving object is to segregate the background from the frames. During object detection, background can be treated either as static or dynamic. However, it is difficult to detect an object in dynamic background due to certain factors like varying in illumination, sudden change in a scene, occlusion, shadow, etc. So keeping this in mind, this paper reviews some of the background subtraction methods in context to moving object detection. Both traditional as well as fuzzy based approaches are reviewed. In most of the observations the traditional based approaches fail to produce a better object detection accuracy in dynamic environment. So fuzzy based approaches are the better alternatives over traditional one. So, a comparative analysis is presented using fuzzy based approach to give a clear insight to the readers about the state of the art of the techniques with respect to moving object detection.