Research on Road Sign Detection Method Based on Improved Canny Algorithm
With the rapid development of autonomous driving technology,road sign detection is becoming increasingly important.To address the issues of edge loss and poor environmental adaptability in current road sign detection,traditional road sign detection algorithms were im-proved and validated on the OpenCV platform.Firstly,in the image processing stage,an improved bilateral filter is used instead of Gaussian filtering to remove noise and preserve edge information;Then,use the Scharr operator to calculate the gradient amplitude of the image in four directions:x,y,45 °,and 135 °;Finally,to address the issues of poor threshold adaptation and difficulty in selecting thresholds for the Can-ny algorithm,the maximum inter class variance(Otsu)method is used for threshold segmentation.Experiments on road sign images have shown that the improved Canny algorithm performs better in single edge response compared to other traditional algorithms,with higher edge de-tection accuracy and robustness,and relatively shorter processing time.
国家科技期刊平台
NSTL
万方数据
