Ground traffic sign real-time detection and recognition method based on space-time correlation

Abstract

The invention discloses a ground traffic sign real-time detection and recognition method based on space-time correlation, and belongs to the field of traffic information detection. An image Src of the road in front of an intelligent vehicle is obtained in real time through the frame rate of 20-50 frame/second, space correlation information is combined, cutting, grey level transformation, Gaussian filter, binarization processing and perspective transformation are performed on the obtained original image Src, and a perspective image Src_IP is obtained. A to-be-detected mark pattern diff_j is obtained through area filter and length-width ratio filter. Meanwhile, a processed ground traffic sign image temp_i is read in. Through image matching, the similarity between the diff_j and each standard image temp_i is calculated, and a set of most similar pictures is found. Subtraction is performed on the temp_i and the corresponding diff_j, statistics is performed on the number Sum_i_r of white pixel points in a new picture, and when the Sum_i_r is smaller than the set threshold value, it is considered that a ground traffic sign in the corresponding standard picture exists. The space-time correlation information is combined, logic judgment is performed on a recognition result, and the accuracy rate is improved. The method is suitable for intelligent driving in the complex city road environments.

Description

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AI Technical Summary

Benefits of technology

This patented method helps improve recognizing by analyzing temporal correlations between images captured from moving cars or other objects around them at speeds up to 10 mph (miles/second). By collectively capturing all relevant data over long periods while changing direction frequently throughout the car's movement, this approach provides improved ability to recognize road conditions accurately without relying solely upon visual observation alone.

Problems solved by technology

Technological Problem: Unmanned vehicles (UVs) face challenges during autonomous navigation due to their ability to detect and identify different types of objects like people, roads, etc., without being affected negatively affecting its performance. Ground Traffic Sign Recognition (GTSR), also known as radar systems used for collision avoidance control purposes, plays a crucial role in improving UAV's efficiency and reducing collisions between obstacles while navigating around complex urban environments. However, current GTSR methods suffer from limitations that limit their effectiveness at identifying ground traffic signals over time.

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