Traffic sign recognition method based on HOG-MBLBP fusion feature of PCA dimension reduction

A technology of traffic sign recognition and feature fusion, which is applied in the field of traffic sign recognition of HOG-MBLBP fusion features, can solve the problems of low recognition accuracy, difficulty in meeting vehicle real-time performance, and long computing time

Inactive Publication Date: 2018-12-25
NORTHEASTERN UNIV
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Problems solved by technology

[0004] At this stage, the recognition accuracy of the traffic sign recognition method is not high, and the calculation time is long, which is difficult to meet the real-time requirements of the vehicle.

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  • Traffic sign recognition method based on HOG-MBLBP fusion feature of PCA dimension reduction
  • Traffic sign recognition method based on HOG-MBLBP fusion feature of PCA dimension reduction
  • Traffic sign recognition method based on HOG-MBLBP fusion feature of PCA dimension reduction

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[0126] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is an embodiment of a part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0127]It should be noted that the terms "first" and "second" in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate c...

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Abstract

The invention provides a dimensionality-reducing HOG-MBLBP fusion feature based traffic sign recognition method based on PCA.. The method of the invention comprises the following steps of: training aclassifier model by using a training sample; constructing a training sample database; extracting a training sample image of the determined training set for graying, extracting HOG features and MBLBP features; serially connecting two eigenvectors of HOG and MBLBP to obtain a HOG-MBLBP fusion eigenvector; the obtained fusion eigenvector being dimensionally reduced by using a PCA algorithm; a linearsupport vector machine (SVM) algorithm being used to train the obtained dimension-reduced fusion eigenvector to obtain an SVM traffic sign classifier; obtaining a traffic sign image; traffic sign images being recognized by the classifier model. The technical proposal of the invention solves the problems that the traffic sign recognition method in the prior art has low recognition accuracy rate andlong operation time, and is difficult to meet the requirement of vehicle-mounted real-time performance.

Description

technical field [0001] The present invention relates to the technical fields of machine vision and image processing, in particular to a traffic sign recognition method based on PCA dimensionality reduction HOG-MBLBP fusion features. Background technique [0002] Nowadays, motor vehicles have gradually become people's means of transportation. With the increase in the number of motor vehicles and the aggravation of traffic congestion, traditional transportation technology has been difficult to meet the requirements of the rapid development of today's economy and society. Intelligent transportation systems have been highly valued by experts and scholars. Intelligent transportation system is an organic combination of various technologies such as information communication, automatic control, sensor technology and computer, and is used in transportation management. The establishment of intelligent transportation system improves the efficiency of transportation, thereby alleviatin...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V20/582G06V10/50G06F18/2411
Inventor 吴芮顾德英
Owner NORTHEASTERN UNIV
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