Method for identifying traffic sign

A technology for traffic sign recognition and direction designation, which is applied in the fields of computer vision, pattern recognition, and image processing, and can solve problems such as multiple false detection rates, inability to guarantee system real-time performance, and inability of recognition systems to detect and recognize correctly.

Inactive Publication Date: 2012-11-28
BEIJING JIAOTONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the SIFT feature matching of the entire image will increase the amount of calculation and cannot guarantee the real-time performance of the system
In complex environments, it will lead to more false detection rates
[0005] Defects in the existing technology: due to environmental lighting changes, fading of signal boards, etc., in complex environments, color-based traffic sign recognition systems often cannot detect and recognize correctly. For example, traffic signs with a blue background cannot pass through blue. filter detects
Therefore, it is difficult to deal with environmental lighting changes, occlusion and geometric deformation by classification methods based on color or outline shape.
In addition, the traffic sign recognition method based only on local edge information (SIFT, etc.) is powerless for the recognition of traffic signs with the same geometric pattern but different colors.

Method used

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  • Method for identifying traffic sign
  • Method for identifying traffic sign

Examples

Experimental program
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Embodiment 1

[0050] Such as figure 1 As shown, a kind of traffic sign recognition method that the present invention proposes, comprises the following steps:

[0051] Step S1: Obtain the input image to be matched;

[0052] Step S2: Extract key points from the image in the template image library and the image to be matched according to the SIFT algorithm, and specify the direction for the key points;

[0053] The SIFT algorithm has the following steps:

[0054] 1. Detect extreme points in the scale space;

[0055] 2. Extract stable key points;

[0056] 3. Specify the direction for each key point;

[0057] 4. Generate feature point descriptors.

[0058] In this embodiment, step S2 determines the key point according to the SIFT algorithm. The specific method is the same as the content disclosed in the SIFT algorithm recorded in the non-patent literature 2 mentioned in the background art body. The specified direction for the key point is specifically the sampling histogram method as the ke...

Embodiment 2

[0068] In this embodiment, the collected traffic signs are used as images stored in the template image library, and based on this, the method for performing traffic sign recognition on the image to be matched is as follows:

[0069] 1. Extract key points from the image in the template image library and the image to be matched

[0070] In step 101, a difference of Gaussian scale space (DoG) is established to find extreme points.

[0071] The purpose of scale space theory is to simulate the multi-scale characteristics of image data. For a two-dimensional image, the scale space representation at different scales can be obtained by convolving the image with a Gaussian function: L(x,y,σ)=G(x,y,σ)*I(x,y) . In the formula, (x, y) represents the pixel position of the image; L represents the scale space of the image; σ is the scale space factor, the smaller the value, the less the image is smoothed, and the smaller the corresponding scale; the symbol * represents volume product; G(x...

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Abstract

The invention discloses a method for identifying a traffic sign and belongs to the field of image processing. The method comprises the following steps of: extracting key points from an acquired image to be matched, establishing local feature descriptors, color feature descriptors and position feature descriptors respectively, extracting key points from the image to be matched and a template image in a template image library respectively to form feature point pairs to be matched, and finding a template image with most feature point pairs to be matched by judging whether position feature descriptors, color feature descriptors and local feature descriptors of the feature point pairs to be matched meet certain conditions, wherein the template image with most feature point pairs to be matched is taken as a finally identified traffic sign image for the image to be matched. By the method, the advantage that scale invariant feature transform (SIFT) features are invariant for the scale change and rotation of images is retained, and color and spatial position features of extracted feature quantities can be conveniently distinguished; and the method is extremely effective to the identification of traffic signs with rich colors and different spatial position distribution changes.

Description

technical field [0001] The invention relates to a traffic sign recognition method, which belongs to the fields of image processing, pattern recognition and computer vision. Background technique [0002] At present, the intelligent transportation system is developing rapidly in our country, and the problems of driving safety, urban traffic congestion, and transportation efficiency are all expected to be improved through the transformation of vehicle informatization and intelligence. As an important subsystem of the intelligent transportation system, the traffic sign recognition system based on image detection and processing technology has gradually become a hot spot in the research of intelligent transportation systems at home and abroad. [0003] The traffic sign recognition system is generally completed by capturing the traffic sign image in the outdoor natural scene through the camera installed on the vehicle, and inputting it into the computer for processing. Due to the i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/64
Inventor 袁雪张晖郝晓丽陈后金魏学业
Owner BEIJING JIAOTONG UNIV
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