Target identification method based on multi-angle local feature matching

Abstract

The invention provides a target identification method based on multi-angle local feature matching. The method comprises the following steps of S1, acquiring a plurality of target object images at different angles to serve as templates, and extracting interest points in the template images; S2, computing local features of areas around the interest points in the templates images by using a feature description method; S3, extracting the local feature of a target image to be identified, and matching the extracted local feature with the local feature in each template image, thus acquiring roughly matched local feature pairs; S4, for the roughly matched local feature pairs, computing a basic matrix between the target image and the template images by using random sampling consistency algorithm, and building epipolar geometry restriction according to the basic matrix to filter the local feature pairs, thus acquiring exactly matched local feature point pairs; and S5, computing the number of the matched local feature points in the target image, if the number of the found feature points is more than a set threshold, determining that identification is successful, and otherwise, determining that the target object is not matched with the templates.

Description

technical field [0001] The invention relates to the field of object recognition. Background technique [0002] Object recognition methods based on local feature matching have been widely used in the fields of machine vision and artificial intelligence with real-time response, such as driverless cars, industrial robot positioning, and trademark image retrieval. It collects the image of the target object through the camera, recognizes and locates the target object in the image through the local feature matching method, converts the recognition signal into an operation signal, and feeds back to the user or terminal. This technology has broad application prospects and potential economic and social values ​​in the fields of intelligent monitoring, man-machine interface, content-based video retrieval and image compression. Because the target object changes greatly under different conditions, it is very difficult to realize real-time target recognition. [0003] Currently commonl...

AI Technical Summary

Problems solved by technology

[0011] The purpose of the present invention is to overcome the shortcomings of the existing target recognition method based on local feature matching, especially the problem that the local feature matching effect is not good when the rotation angle, size change, and illumination change of the target object to be recognized are too large.

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