A fast valley-based segmentation for detection of slowly moving objects

Moving object detection in a video sequence is the first and most important step in many computer vision applications. However, it is challenging for a machine to match with the human visual perception level. Motion information of slowly moving object is highly erroneous in comparison with fast moving object. Therefore, in real time, accurate segmentation of slowly moving objects is more challenging. In this paper, a fast and efficient segmentation algorithm is proposed for the detection of slowly moving object in a video sequence. The proposed method has three steps to extract the slowly moving object in a video. In the first step, an averaging frame difference method is proposed to extract the motion information. In the second step, a valley-based thresholding is proposed to segment all the frames of a video. In the final step, the motion information and spatial homogeneous region information are merged to extract the slowly moving object.

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