Traffic sign target detection method based on multilevel divide-and-conquer network

Abstract

The invention discloses a traffic sign target detection method based on a multilevel divide-and-conquer network, which is used for solving the technical problems of low traffic sign detection precision and low recall rate in the prior art. The method comprises the following specific steps: generating a training set and a test set; training a target detection network; extracting a background category of a sample of a traffic sign-free target in the test set; enhancing the data in the training set; generating a training set of label categories and a training set of label and background categories; training a classification network; positioning and roughly classifying a to-be-detected target; and carrying out fine classification on the pictures after rough classification. The multi-level divide-and-conquer network constructed by the invention overcomes the defect that excellent results cannot be obtained on the aspects of positioning and classification of the traffic sign targets in the prior art, so the positioning and classification accuracy of the traffic sign targets is effectively improved by the multi-level divide-and-conquer network.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a traffic sign target detection method based on a multi-level divide-and-conquer network in the technical field of image target detection. The invention can be used to detect objects of stationary traffic signs in natural images. Background technique [0002] Traffic sign detection refers to locating the position of traffic signs according to the color, shape and other characteristics of traffic signs in the image, and classifying and recognizing the traffic signs in the image, obtaining the meaning of traffic signs, and regulating the driving of vehicles. In recent years, a large number of target detection methods have begun to be applied to traffic sign detection, but there are still many challenges in target traffic sign detection in real tasks, such as poor classification of traffic sign targets. This is due to the uneven distribution of traffic signs caused b...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to address the deficiencies of the above-mentioned prior art, and propose a traffic sign target detection method based on a multi-level divide-and-conquer network, which is used to solve the shortage of some category samples in the traffic sign image data set in the prior art, and the category The number of samples is unbalanced, and the problem of too many distractors is solved to solve the technical problems of low traffic sign detection accuracy and recall rate in the existing target detection network technology

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