A multiple-subarea matching method constraint by a space relation

Abstract

The invention discloses a multiple-subarea matching method constraint by a space relation. A plurality of subareas are selected in a matching template as sub-templates, and the sub-templates are separately and simultaneously matched with to-be-matched images. Space position relations among the sub-templates are utilized to realize the accurate matching of the images. The method comprises the following steps: the plurality of subareas are selected in the matching template respectively as the sub-templates; the space relations among the sub-templates are determined; the plurality of sub-templates keep the space position relations unchanged to form combined templates; matching is carried out by utilizing the mobile searching performed by the combined templates on the to-be-matched images, and a plurality of similarity values of the combined templates are obtained; the plurality of similarity values are compared, and a position where a maximum similarity value exists is regarded as an optimum matching position to complete the matching. The method of the invention utilizes the mutual space relations among the plurality of sub-templates to reach the requirements for accuracy and precision of matching. The object identifying performance of the method is substantially improved in real-time performance compared with the conventional large-template gray scale or contour matching algorithms.

Description

technical field [0001] The invention belongs to the technical field of digital image matching, and in particular relates to an image multi-subregion matching method. Background technique [0002] With the rapid development of science and technology, especially computer technology, image processing technology that directly obtains information from images has developed rapidly. Image matching is one of the very important technologies in computer vision and image processing. [0003] Image matching is the process of finding subimages corresponding to known patterns through matching calculations in one or more unknown images. At present, image matching technology is widely used in various fields such as military, industry, remote sensing, medicine and machine vision. [0004] In an actual image matching application, it is necessary to select a template with an appropriate size. However, in the matching calculation, if the template graph is enlarged, the calculation amount of t...

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Problems solved by technology

However, in the case of high real-time requirements, this method will be lacking, and it cannot make full use of the important information of the template in a short calculation time to achieve the effect of fast calculation

[0006] Existing methods for improving matching speed are difficult to guarantee better matching performance, either because the accuracy and accuracy of matching are significantly different from matching algorithms that have not been accelerated, or because the stability of improving matching speed is poor, and in some In some cases, it can reduce the amount of calculation and increase the matching speed, but in some cases it can hardly reduce the amount of calculation, that is, the calculation speed of the matching algorithm after speed-up is basically the same as that of the matching algorithm without speed-up

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