Automatic identification method of aircraft number

Abstract

The invention provides an automatic plane number recognition method. The automatic plane number recognition method includes collecting original plane number images of a current frame of planes; adopting a plane number recognition algorithm to perform plane number recognition on the original plane number images to acquire current plane number information; making statistical analysis on plane number information of the planes whose current airport appearance probability exceeds a threshold value; based on a BP (back propagation) neural network algorithm, calculating similarity of any two characters in the plane number information; accurately matching the current plane number information with the plane number information acquired through statistical analysis, judging whether the current plane number information exists in the plane number information acquired through statistical analysis or not according to the similarity, if not, matching through a fuzzy matching algorithm, and if yes, correcting matched plane number information by combining detection results of multiple frames. The automatic plane number recognition method can meet plane number recognition requirements in different environments and has the advantage of high plane number detection accuracy.

Description

technical field [0001] The invention belongs to the technical field of license plate number recognition, and in particular relates to an automatic recognition method for aircraft machine numbers. Background technique [0002] With the rapid development of the national economy and frequent take-offs and landings at civil airports, the airport operation department needs to accurately and quickly identify the aircraft number during the taxiing process, so as to effectively improve the overall operation of the airport, especially the management efficiency of the runway. Punctuality provides technical support. [0003] In the prior art, the Otsu (maximum class variance method) binarization method is mainly used to process the aircraft tail number image, and then the aircraft tail number is recognized based on the optimal parameters of the support vector machine. [0004] This method has the disadvantages of poor robustness to interference such as illumination changes, aircraft s...

AI Technical Summary

Problems solved by technology

[0004] This method has the disadvantages of poor robustness to interference such as illumination changes, aircraft size, and complex fuselage patterns, and it is difficult to adapt to the identification requirements of aircraft numbers in different environments. Therefore, it has the problems of low accuracy of aircraft number detection and limited practical value.

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