Target recognition method of unmanned aerial vehicle based on minimum circle-cover matching

Abstract

The invention relates to a target recognition method of an unmanned aerial vehicle based on minimum circle-cover matching. The target recognition method comprises the following five steps of: step 1, carrying out edge detection and communicated domain calibration to a target area and dividing the target area into a plurality of areas to be matched; step 2, creating a target model shape characteristic information base; step 3, carrying out minimum circle-cover detection to all the targets to be detected in the target area, and simultaneously recording the diameter orientation of the minimum circle-cover; step 4, matching the diameters of a target template and an outline to be matched so that the subsequent step can be implemented within a certain orientation; and step 5, matching the target template with the outline to be matched, carrying out the matching orderly to a plurality of communicated domain targets of the target area, and finally comparing and obtaining a sum-of-squared difference (SSD) measure of a minimum pixel gray difference, wherein the outline matching corresponding to the sum-of-squared difference (SSD) measure is the required result. The target recognition method utilizes the computational geometry technology, the optimization theory, the computer vision technology and other technologies, realizes the multi-target recognition of the unmanned aerial vehicle, greatly improves the speed and accuracy for recognizing the targets and has great practical value and application prospect.

Description

(1) Technical field [0001] The invention relates to an unmanned aerial vehicle target recognition method based on a minimum covering circle (Smallest Covering Circle, SCC) matching, and belongs to the cross technical field of aerospace and computer vision information processing. (2) Background technology [0002] Unmanned Air Vehicle (UAV) is a powered, controllable, capable of carrying a variety of mission equipment, performing a variety of tasks, and reusable unmanned aerial vehicles. With the continuous improvement of the performance of UAVs, and its advantages of small size, flexibility, and difficulty in being discovered, UAVs are used in reconnaissance and patrolling, building surveys, aerial map drawing, and clearing obstacles in dangerous environments. And other military and civilian special fields have shown huge application potential, so it has been generally valued by countries all over the world. Target tracking has always been a very important task for UAVs. ...

AI Technical Summary

Problems solved by technology

[0003] The color information in the image can fully represent the original information we obtained. In theory, we can extract all the information based on the color information, but it is difficult to achieve in practice.

The use of shape information can help people and machines to complete the target recognition process. In terms of target shape description, various concepts such as edge, invariant moment, Fourier descriptor, centroid, and rectangularity are introduced, but they are often followed. With the complexity of the actual situation, there are application difficulties, such as scaling and rotation caused by matching difficulties

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