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Road sign identification method based on generalized Hough transform and wavelet transform

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

Active Publication Date: 2018-09-11
WUHAN UNIV OF TECH
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Problems solved by technology

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

Method used

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  • Road sign identification method based on generalized Hough transform and wavelet transform
  • Road sign identification method based on generalized Hough transform and wavelet transform
  • Road sign identification method based on generalized Hough transform and wavelet transform

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[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 identification method based on generalized Hough transform and wavelet transform. The method includes the following steps: step one, selecting standard images to construct a feature image library; step two, denoising the collected images; step three, conducting generalized Hough transform on the denoised images to perform edge extraction; step four, extracting low frequency information of the extracted images through wavelet decomposition; step five, establishing corresponding feature images on the basis of the low frequency information of the images; and step six, utilizing Euclidean distance to carry out matching identification on the established feature images and the feature image library. According to the invention, the low frequency information ofthe images is obtained through wavelet decomposition so that the feature image library is established, and the most essential feature information having the best identification effect in the images iskept. Compared with a conventional identification method, the method is higher in accuracy.

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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IPC IPC(8): G06K9/00G06K9/46G06K9/52
CPCG06V20/588G06V10/48G06V10/52
Inventor 邹斌王磊董富颜伏伍
Owner WUHAN UNIV OF TECH
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