Video Object Segmentation Based On The Changing Area Detection

Video object segmentation is to segment video according to certainstandard in order to mark the important objects, which are called video object.General speaking, a video scene is composed of video objects (moving object)and it's background. It is easy for us to distinguish them, but it is difficult forcomputer to do this. It will be a great merit in many fields if these movingobjects can be divided from the background, for these objects are significantparts in video. In intelligent surveillance, the vehicles passing from the traffic across,highway and guard need to be registered and accounted, which could beaccomplished only when the vehicles are segmented firstly. In internet transfer,if the moving objects can be divided and assigned more resources, when thequality of the picture will decrease, observers interest center can be ensured sothat the subjective quality of video can be increased. In military field, picturesare carriers of important information. Taking successive pictures and dividingmoving objects from it can provide clue for scout. At the present, the researchof infrared sequential images and automatic tracking of objects have laid afoundation for the development of automatic armaments. In video coding, thecode standard MPEG－4 based on content was publicized in 1994.MPEG－4employed the code method based on objects and models, which can increasecompression efficiency and assign transfer resources more reasonably. Codingmethod based on objects requires the video object to be segmented in the firstplace. The instrument is not included in the standard and waits to be studiedfurther. Segmenting objects under any condition ideally can hardly be realized dueto the present capability of calculation and the complexity of images. Eachproject has its own applicability. The usual practice is to choose applicable ivmethod according to different application characteristics, and making use ofcertain characteristics of video. The video characteristic of traffic field is that moving objects are rigidbodies and the moving tracks are almost straight so that the segmentation inhigh density scenes can hardly be realized satisfactorily. Usually, in thesurveillance of guard and highway, the number of objects is few and the speedsare high. This paper intends to study in the field of traffic intelligentsurveillance how to segment single moving object or multi-objects of the samecharacteristics in a comparatively simple and stable background when thecamera doesn't move or change focus. When analyzing the existing projects ofvideo segmentation, it can be found that optical-flow estimation cannot beapplied in this paper for it demands a large amount of calculation and theresearch background of this paper isn't in accordance with the hypothesis oflight invariableness. Since the method of matching block regards gray-level asthe data resources of matching principle, in the region where light breaks, thismethod cannot follow object correctly. This paper searches the original positionof objects by the means of varying region detection, and then gets the accurateboundary of objects through the tracking method based on distortion template. In regard to the low-speed moving objects, variation regions can beextracted by the difference between two frames, and then be traced andmodified. But for the high-speed moving objects, the errors of differencebetween two frames will be great, and the difference image can hardly reflectthe figure and movement information. Under this circumstance, the differencebetween frame and background can be employed to detect the movementregion. When the no-object background cannot be achieved directly in time, orthe background is changing slowly, background rebuilding will have to beadded into steps of video segmentation. Through analyzing the common methods of background rebuilding, andtaking the requirement of intelligent surveillance...