Fast image matching method and system based on feature state and global consistency

Abstract

The invention provides a method and a system for quickly matching images on the basis of feature states and global consistency. The method includes utilizing detection angular points as to-be-matched feature points and identifying feature neighborhood states of the feature points by the aid of state templates; utilizing the feature points as centers and computing main directions of descriptors; turning the main directions, describing feature neighborhoods of the feature points, combining binary texture features and statistic features with one another and creating RBT-OGMH feature descriptors; matching the images for two types of different descriptors by the aid of different types of similarity measurement; quickly determining transformation matrixes by the aid of consistent features of spatial domains on the basis of error fluctuation amplitude minimization clustering, and eliminating error matching point pairs to obtain ultimate correct matching point pairs. According to the technical scheme, the method and the system have the advantages that the method and the system have rotational invariance and certain scale invariance, and problems of image blurring, illumination change, low contrast and image deformation can be effectively solved; the method and the system are high in matching speed and precision as compared with the prior art.

Description

technical field [0001] The invention relates to the technical field of digital image processing, in particular to a fast and robust image matching technical solution. Background technique [0002] Image matching plays a pivotal role in image stitching, image retrieval, scene recognition and other application fields, and is the basis of image processing and computer vision. With the development of science and technology, about 40% of machine vision applications currently use image matching technology, and the application fields involved include industry, agriculture, military, and medical treatment. In the video surveillance system, its basic part is to use image matching technology to detect, track, classify and identify moving targets, which is the key to ensure the entire system to realize its functions. Specifically, image matching is to search for similar features in two or more images, and use matching criteria to search optimally according to similar conditions. [0...

AI Technical Summary

Problems solved by technology

The steepest descent method also needs continuous iterations to accurately affine transform coefficients. When there are many matching point pairs and wrong matching points in the image, these two algorithms for eliminating wrong matching point pairs will take more time.

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