Traffic sign detection and recognition method based on HDR technology

Abstract

The invention discloses a traffic sign detection and recognition method based on HDR technology. The method comprises: step (1), adopting seamless fusion technology to carry out processing, which is shown in the description, on N LDR images of different exposure values to generate a multi-exposure HDR image; step (2), carrying out joint color and shape detection, and obtaining three sign types bysegmentation; and step (3), utilizing an SURF (Speeded Up Robust Feature) operator to respectively extract features of to-be-recognized sign images and standard sign images of the types correspondingthereto, calculating Euclidean distances of feature vectors thereof, and using names of standard signs, which correspond to minimum Euclidean distances, as names of current to-be-recognized signs. Themethod can adapt to extreme weather such as dense fog and rainstorms, and overcome impacts of poor illumination conditions such as driving a vehicle at night; makes up for deficiency of missed detection and error detection caused by only relying on color detection, and achieves especially obvious detection effects for certain signs, such as ''no parking'' and ''traffic lights ahead'', with special colors; and is faster in a running speed, and is also higher in a recognition accuracy rate.

Description

technical field [0001] The invention relates to the technical field of image detection and recognition, in particular to a traffic sign detection and recognition method. Background technique [0002] As an important part of the automatic assisted driving system, the automatic detection and recognition of traffic signs provides effective information for safe driving and driving navigation, and plays a vital role in regulating driver behavior and ensuring smooth traffic and safe travel. , so it is also a hot research topic for experts and scholars in the field of image detection and recognition. [0003] Traditional traffic sign detection and recognition methods are based on LDR images. Merve Can Kus et al. proposed a method based on color segmentation and SIFT operator to extract features to realize sign recognition; Jafar Abukhait et al combined the shape and color information of signs to improve the detection efficiency of traffic signs ; JinZhao et al. proposed a method ...

AI Technical Summary

Problems solved by technology

The above detection and recognition methods based on LDR images are often susceptible to the limitation of the dynamic range of the camera and the influence of weather conditions. In the case of overexposure and weak exposure, the detailed information of the image cannot be obtained, which causes difficulties in the detection of signboards. even more difficult

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