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Traffic sign recognition method based on shape feature invariant subspace

A technology of traffic sign recognition and feature subspace, which is applied in character and pattern recognition, instruments, computer parts, etc., and can solve problems such as image noise and inaccurate recognition methods

Inactive Publication Date: 2014-04-30
SHENYANG POLYTECHNIC UNIV
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AI Technical Summary

Problems solved by technology

[0004] Traffic signs have the characteristics of bright colors and obvious shape features. Under normal circumstances, the image information of traffic signs is relatively clear, but the images of traffic signs collected under natural conditions are easily affected by external conditions, resulting in noise in the collected images. Causes inaccurate recognition methods based on color information

Method used

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  • Traffic sign recognition method based on shape feature invariant subspace
  • Traffic sign recognition method based on shape feature invariant subspace
  • Traffic sign recognition method based on shape feature invariant subspace

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Embodiment

[0085] Embodiment: refer to document 1~file 3, Figure 1 to Figure 6 , Table 1, Table 2, an invariant subspace recognition method based on traffic sign shape features, the steps are as follows:

[0086] (1) Download standard traffic sign images, and establish color image databases of indicator signs, warning signs, and prohibition signs, as shown in file 1.

[0087] (2) Normalize the color image of file 1 to a size of 75*67, and convert it into a grayscale image, add Gaussian white noise, Poisson noise, salt and pepper noise and speckle noise respectively, and establish a grayscale image database of traffic signs, As shown in file 2.

[0088] (3) Perform equalization processing on part of the traffic sign images, and then binarize all the images to establish a binary image library of traffic signs, as shown in file 3.

[0089](4) Use principal component analysis (PCA) and principal component linear discriminant analysis (PLA) to extract and identify features from the traffic...

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Abstract

The invention relates to a traffic sign recognition method based on shape feature invariant subspace. A binary image of a traffic sign is used as a feature extraction object, the principal component analysis method and the linear discriminant analysis method are combined, and firstly the principal component analysis method is used for conducting feature extraction on the image of the traffic sign so as to obtain a feature matrix with the optimal description effect; then, the linear discriminant analysis method is used for conducting secondary feature extraction on the matrix so as to obtain a feature matrix with the optimal classification effect, and therefore features extracted in the traffic sign recognition method have the optimal description performance and the optimal discrimination performance; finally, the minimum distance classification method is adopted for identifying the extracted features, and tests verify that the traffic sign can be recognized accurately.

Description

Technical field: [0001] The invention relates to a traffic sign recognition method, in particular to a traffic sign recognition method based on a shape feature invariant subspace. Background technique: [0002] The intelligent transportation system is a comprehensive and comprehensive system that effectively integrates advanced information technology, communication technology, sensor technology, control technology and computer technology into the entire transportation management system. , a real-time, accurate and efficient comprehensive transportation and management system, which improves transportation efficiency, alleviates traffic congestion, improves road capacity, reduces traffic accidents, reduces energy consumption, and reduces environmental pollution through the harmonious and close cooperation of people, vehicles, and roads. Pollution. As an important part of intelligent transportation system, traffic sign recognition system plays an important role in enhancing th...

Claims

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Application Information

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IPC IPC(8): G06K9/64G06K9/46
Inventor 张志佳何纯静李雅红崔世昊
Owner SHENYANG POLYTECHNIC UNIV
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