Research Of Edge-based Moving Object Detection Technique In Static Background Image

Moving objects detection is one of the most important issues in image processing and computer vision. It belongs to bottom video information detection. Valid acquiring of moving region is important in object classifying, object tracking and behavior understanding because the pixels of the moving region are processed mainly. It is used widely in many fields, such as military reconnaissance, video surveillance and monitoring, traffic detection. Image sequences in moving objects detection can be divided into two types by which background is static or moving. The thesis is based on static background.First, some common approaches in the field of detecting moving objects are introduced, including optical flow method, two consecutive frame subtraction method and background modeling method. Their advantages and disadvantages are compared and pointed out in this thesis. Then, an edge-based moving object detection algorithm is proposed. In the algorithm, the threshold of the difference images is calculated from the two consecutive frame images. Then the rough position of the moving object is decided by using morphological filter for binary image. Edge detection is carried for the current frame at the same time. For getting the edge of the moving object, the "and" operation is done between the results of rough position and the edge detection. At last, the area of the moving object is obtained through filtering and region filling.Compared with traditional two consecutive from subtraction method, It solves the problem of not exactly detecting the size of moving objects, keeps the advantages of not sensitive for gradual changing background for the detection. The algorithm is valid, steady in object detection. It has obtained a better effect for not only single object detection but also multi-moving objects detection.