Vehicle logo feature extraction and recognition method based on feature quantization of gradient direction division

A gradient direction and feature extraction technology, applied in the field of target recognition, to achieve high recognition rate, increase feature description information, and reduce dimensionality

Active Publication Date: 2019-03-08
INTELLIGENT MFG INST OF HFUT
View PDF5 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In actual situations, due to factors such as illumination, size, and orientation, many bayonet images are not idealized car logo images

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Vehicle logo feature extraction and recognition method based on feature quantization of gradient direction division
  • Vehicle logo feature extraction and recognition method based on feature quantization of gradient direction division

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0037] Such as figure 1 As shown, a feature extraction method based on gradient direction division includes the following steps:

[0038] (1) Extract the gradient size and gradient direction information of the car logo image:

[0039] The collected car logo samples are divided into two categories, training samples and test samples. Normalize and grayscale the training samples, calculate the gradient size Gv and gradient direction Go of each pixel in the sample image, and store the gradient size and gradient direction information in the gradient matrix.

[0040] (2) Gradient direction division and gradient size matrix generation:

[0041] The gradient direction is divided into k ranges, and for each pixel, the pixels belonging to the same range in its neighborhood are stored in a matrix (called a gradient size matrix). Then each car logo sample has k gradient size matrices, and then calculate the gradient size matrix of each car logo sample.

[0042] (3) Feature extraction ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a vehicle logo feature extraction and recognition method based on feature quantization of gradient direction division. The method comprises firstly preprocessing the vehicle logo image captured by the bayonet system, calculating the gradient magnitude and direction of each pixel, and storing the gradient information of all pixels in a corresponding gradient matrix; dividingk gradient directions in advance, counting the gradient magnitudes of all pixels around each pixel corresponding to k gradient directions, and accumulating the gradient magnitudes into k different gradient magnitude matrices; respectively extracting the LTP features of k gradient size matrices, and obtaining the pixel features of the original vehicle logo image by splicing the extracted k LTP features; through K-Means, classifying all the features in the sample to get offline codebook, and then using SVM to classify and recognize the logo image. The method of the invention puts forward a specific recognition scheme for the vehicle mark recognition in the bayonet image, and the recognition result has high accuracy rate, which can meet the requirements of the actual intelligent transportation system.

Description

technical field [0001] The invention relates to the technical field of target recognition, in particular to a method for extracting and recognizing vehicle logo features based on feature quantization of gradient direction division. Background technique [0002] In the application of computer vision, vehicle logo recognition has always been an important part of the intelligent transportation system. It is widely used in the fields of collecting vehicle information, analyzing traffic flow, identifying vehicles that violate regulations and causing accidents, and regulating traffic order. In the intelligent transportation system, the high-definition bayonet system uses advanced photoelectric technology, image processing technology, and pattern recognition technology to take pictures of every passing car. The vehicle logo feature extraction and recognition method in the present invention is aimed at bayonet high-definition images, and uses the existing car logo positioning techno...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V20/584G06V10/473G06V10/462G06F18/23213G06F18/214
Inventor 余烨徐京涛路强薛峰
Owner INTELLIGENT MFG INST OF HFUT
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap