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Road Sign Recognition Method Based on Generalized Hough Transform and Wavelet Transform

A generalized Hough transform and wavelet transform technology, applied in character and pattern recognition, instruments, calculations, etc., can solve problems such as unguaranteed, high accuracy, and limited use, and achieve improved recognition effects and high accuracy Effect

Active Publication Date: 2022-03-01
WUHAN UNIV OF TECH
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  • Application Information

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Problems solved by technology

However, these methods cannot always guarantee a high accuracy rate, and their use is limited

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  • Road Sign Recognition Method Based on Generalized Hough Transform and Wavelet Transform
  • Road Sign Recognition Method Based on Generalized Hough Transform and Wavelet Transform
  • Road Sign Recognition Method Based on Generalized Hough Transform and Wavelet Transform

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Embodiment Construction

[0052] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0053] The embodiment of the present invention is based on the generalized Hough transform and wavelet transform algorithm for road sign recognition, such as figure 1 shown, including the following steps:

[0054] Step 1: Select a standard image to build a feature image library;

[0055] Step 2: Perform denoising operation on the collected image;

[0056]Step 3: use the generalized Hough transform to perform edge extraction on the image after denoising;

[0057] Step 4: Use wavelet decomposition to extract the low-frequency information of the image from the extracted image;

[0058] Step 5: Est...

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Abstract

The invention discloses a road sign recognition method based on generalized Hough transform and wavelet transform, comprising the following steps: step 1: selecting standard images to construct a feature image library; step 2: performing denoising operations on the collected images; step 3: Use the generalized Hough transform to extract the edge of the denoised image; step 4: use wavelet decomposition to extract the low-frequency information of the image; step 5: establish the corresponding feature image according to the low-frequency information of the image; step 6: use the Euclidean distance Match and identify the established feature image and feature image library. This paper invented the use of wavelet decomposition to obtain low-frequency information of the image, thereby constructing the feature image library, which retains the most essential feature information in the image and has the best recognition effect. Compared with the traditional recognition method, its accuracy is higher.

Description

technical field [0001] The invention relates to the technical field of unmanned driving, in particular to a road sign recognition method based on generalized Hough transform and wavelet transform. Background technique [0002] In recent years, Advanced Driver Assistance Systems (ADAS) and unmanned driving technologies have developed rapidly, among which road sign recognition is one of the research hotspots. Common road signs are slow down, stop, speed limit, etc. Accurate detection and recognition of road signs can reduce the possibility of accidents and increase driving safety. For humans, after visual information is transmitted to the brain, the brain can process the information based on the existing knowledge, and then recognize and judge. [0003] For machines, it is difficult to accurately identify road signs in complex scenes due to the many types of road signs and the low degree of discrimination, as well as the influence of illumination, acquisition, occlusion and ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V20/56G06V10/48G06V10/52
CPCG06V20/588G06V10/48G06V10/52
Inventor 邹斌王磊董富颜伏伍
Owner WUHAN UNIV OF TECH