Aiming at the problem that the position of skeleton obtained by the method based on topology refinement is not accurate enough, and the connectivity of the skeleton obtained by distance transform cannot be guaranteed, this paper combines the advantages of the topology refinement algorithm and distance transformation algorithm to propose an improved skeleton extraction algorithm. This method first obtains the skeleton points through distance transform, and then obtains the initial skeleton through the refinement method; last uses the skeleton points obtained by distance transformation to screen each branch obtained through the refinement method to ensure the accuracy of the skeleton in the later applications. Experiments on the MPEG7 dataset demonstrate the effectiveness of the algorithm.
Aiming at the problem that frame difference method will deal with the moving target incorrectly when the target moves slowly or stops for some times, a novel method based on frame difference for moving object detection is proposed. Firstly, the algorithm confirms the number of frames used to generate background by comparing the binary frame difference of the current frame with the initial binary frame difference and establishes the background model using the determined frame; Then the background subtraction method is utilized to detect the moving object through the established background. Relevant experiments show that the algorithm can better deal with the detection of slow-moving targets.
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