Shape matching locating method and device based on yin-yang discrete point sampling model

Abstract

The invention discloses a shape matching locating method based on a yin-yang discrete point sampling model. The method comprises the steps that first, shape contour templates are extracted from yin discrete point sampling images or yang discrete point sampling images in sample images; second, the extracted shape contour templates are subjected to optimization, and the best shape contour template is obtained; and third, yin discrete point sampling images or yang discrete point sampling images of practical images are obtained and are matched with the corresponding best shape contour template, so that images are recognized. In the third step, matching is achieved through a matching ratio operator for computing density estimation of the yin discrete point sampling images or the yang discrete point sampling images of the practical images and the corresponding best shape contour template. The invention further discloses a corresponding shape matching locating device. According to the method and device, the shape contour templates are extracted from the yin discrete point sampling images or the yang discrete point sampling images in the sample images, matching of the detected images is achieved, a shape to be detected is recognized, and quick extracting and accurate distinguishing of line-face combination shapes under a complex background in current image recognition are achieved.

Description

technical field [0001] The invention relates to the field of image matching and recognition, in particular to a method and device for shape matching and positioning in digital images. Background technique [0002] Using the area and boundary information of the target to realize the shape matching of identifying and locating the target from complex images is most in line with the general law of human cognition and distinguishing targets, so it has been extensively studied by a large number of scholars in the fields of image processing and computer vision for a long time. A shape matching model includes three elements: the intermediate representation of the scene graph, the shape template and the matching method. In applications that hope to quickly detect objects through shape matching, the main requirement for the intermediate representation of the scene graph is stability, that is, the intermediate representation should be as free as possible from the effects of illuminatio...

AI Technical Summary

Problems solved by technology

[0006] In view of the above defects or improvement needs of the prior art, the present invention provides a shape matching positioning method based on the Yin-Yang discrete point sampling model, which extracts the shape contour from the Yin-Yang discrete-point sampling map or Yang discrete-point sampling map of the sample image Template, realize the matching of the detection image to identify the shape to be detected, solve the problem of rapid extraction and accurate distinction of the combined shape of line and surface under the complex background in the current image recognition detection

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