Traffic sign detecting method based on self-adaptation threshold value

Abstract

The invention discloses a traffic sign detecting method based on a self-adaptation threshold value. Firstly, a reddening and bluing method is adopted by the traffic sign detecting method to carry out image preprocessing, a red-blue grayscale image is obtained, and then multiple times of thresholding processing are carried out on the grayscale image. During each time of thresholding processing, contour detection is carried out on a binary image generated by the thresholding processing; and then, according to shape characteristics of a traffic sign, sign contour matching with geometric condition constraint and Hu invariant moment is carried out, and after filtering and screening are carried out, a suspected traffic sign regional set in a current threshold image is obtained; finally, results of the multiple times of thresholding processing are merged, and according to the frequency for detecting of contour regions of the sign, interest regions of the traffic sign are finally confirmed. According to the traffic sign detecting method, a better thresholding processing effect is provided for candidate areas of the traffic sign in the image, the feature of threshold value self-adaptation is provided, the efficient detecting efficiency and the time performance are provided, and the problem of adaptability under different illuminating conditions is excellently solved.

Description

technical field [0001] The invention belongs to the technical field of traffic sign recognition, and relates to an efficient traffic sign detection method in traffic sign recognition of vehicle-mounted video images, in particular to a traffic sign detection method based on an adaptive threshold. Background technique [0002] With the rapid development of transportation, traffic safety is becoming more and more important. Subsystems such as pedestrian detection and traffic sign recognition in Advanced Driver Assistance Systems are important methods to reduce vehicle traffic accidents, and traffic sign detection is a key part of the traffic sign recognition system, which affects traffic sign recognition. The system recognizes the important factors of efficiency and real-time performance. [0003] The traffic sign recognition system can be divided into two stages: detection and classification recognition. According to the different characteristics of traffic signs used, the de...

AI Technical Summary

Problems solved by technology

Most of the detection methods based on color features are based on fixed thresholds in some color spaces. Although these methods have good real-time performance, they are easily affected by lighting conditions, and the detection efficiency is very low, which cannot meet the detection rate requirements of the traffic sign recognition system.

The detection method based on shape features has better detection performance for some specific types of traffic signs, but it is not suitable for all types of traffic sign detection and lacks good adaptability; at the same time, because such methods do not consider color features, Will generate more interference, affecting the performance of the detection algorithm

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