Abstract:

To overcome corner clustering phenomenon of Harris operator feature point matching, we proposed a probability density\|based corner matching algorithm. This method sets the image distance between the corner as a basic reference coefficient of the main regional division, using the corner probability density of regional division to reduce the matching area, and judging the feature points outside the region as false corners and removing them. Experiments show that the matching results of improved algorithm effectively reduce interference points, improving the timeliness and accuracy of the algorithm.

Key words: corner detection, Harris operator, probability density, uniform, regional segmentation, target location