Abstract-Users are often not only interested in the current web page contents but also in changes in it. In this paper we describes web page change detection system based on Signature of Node corresponds to HTML pages. In this proposal first HTML document is filtered into XML structure document and then transforms XML pages to trees using DOM. The node signature comparison algorithm is developed to compare the trees of old web page and modified web page to find the changes in the web page. This system highlights changes of content i.e. deletion and addition of text and attribute changes i.e. font change, caption change, color change etc. and highlight the changed part in red color and displays to the user. This algorithm gets result faster as it does not search the sub tree if that sub tree does not have any changes.

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1 Identifying moving objects from a video sequence is a fundamental and critical task in many computer-vision applications. Such automatic object detection soft wares have many applications in surveillance, auto navigation, traffic monitoring and robotics. While identifying the objects it is some time essential to identify the objects individually. Individual object detection is very critical in many applications in the areas of surveillance, military, traffic monitoring and medical. The object separation is difficult because of clutter of the objects in the given image frame. Cluttering of the objects is due to overlapping of objects or their shadows making them merge into each other. In videos when multiple moving objects are to be detected its shadow creates clutter in detection phase. Shadows appear in the detection as objects itself if not paid separate attention. In this paper we have demonstrated how shadow affects the separation of the objects in multiple objects detection and method to avoid this object clutter. Here we have separated foreground pixel from background pixel using Gaussian mixture model. These separated pixel forms the mask for next stage of object detection. In cluttered frame the only masked pixels are compared for colour intensity test to detect the cast shadow. This technique reduces the processing time as compared to total pixel testing. Such shadow pixels are removed from the frame and then frame is passed to object detection stage.Shadow removal before object detection stage gives good segmentation of individual object in video having multiple moving objects.

ABSTRACT: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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