Abstract:

Because the existing methods fail to extract the neighborhood features of the fencing continuous action image， the image segmentation results are not ideal， the anti-noise performance is poor， and the segmentation operation time increases. A fencing continuous action image segmentation method based on spatial neighborhood information is proposed. The feature points of the body contour were extracted automatically， the adaptive neighborhood geometric feature covariance matrix about the feature points as feature point descriptors was set， the similarity of each descriptor was measured， and the neighborhood features of the continuous fencing action were extracted. Then， through the neighborhood feature， the spatial constraint term function was added to the objective function， the spatial neighborhood membership function was set using the prior probability of the pixel， and the kernel function was added at the same time to optimize the image characteristics of the fencing continuous action. A new weighted membership function was obtained through membership function modification， which strengthens the proportion of neighborhood information clustering and completes image segmentation. Finally， an experimental test was carried out. After testing， it is proved that the proposed method can obtain the ideal segmentation effect， and at the same time can improve the anti-noise performance and reduce the segmentation operation time.

Key words: spatial neighborhood information, continuous fencing action, image segmentation, kernel function