Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

License plate positioning algorithm fusing affine invariant corner feature and visual color feature

A technology of corner feature and positioning algorithm, which is applied in computing, computer components, instruments, etc., can solve the problems of lack of robust positioning and achieve strong positioning effect, accurate robustness, and efficient positioning effect

Active Publication Date: 2015-12-09
CHONGQING UNIV OF TECH
View PDF0 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method lacks robust positioning for license plate images with complex backgrounds, illumination changes, and affine transformations.

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
  • License plate positioning algorithm fusing affine invariant corner feature and visual color feature
  • License plate positioning algorithm fusing affine invariant corner feature and visual color feature
  • License plate positioning algorithm fusing affine invariant corner feature and visual color feature

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0047] The license plate location algorithm of the present invention which combines affine invariant corner features and visual color features is mainly divided into three parts: license plate image preprocessing, license plate feature extraction and feature fusion, and license plate image positioning. The specific process of the algorithm is as follows figure 2 shown.

[0048] Most of the license plate images collected in practical applications belong to the RGB color space, but this color space cannot well fit the human eye's perception of color. On the other hand, if the color image is directly processed in the corner detection, the computational complexity of the algorithm will be increased. Therefore the present invention does following preprocessing to obtaining license plate image:

[0049] (1) Before extracting corner features, the RGB color image is converted into a grayscale image and filtered to remove noise; the license plate image IMG1 after grayscale processin...

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 license plate positioning algorithm fusing an affine invariant corner feature and a visual color feature. A corner with a scale and affine invariant feature and a color feature are extracted in a Gaussian difference scale space. A rapid fusion method based on a multi-scale product is provided in multi-scale corner feature and multi-feature fusion. A license plate is accurately positioned through distance and intensive relationship between license plate region feature points. The test of a lot of vehicle images actually shot in a complex environment shows that the license plate positioning algorithm is rapid and efficient, and has a great robust performance in terms of rotational transforming, scaling and noise.

Description

technical field [0001] The invention relates to the field of license plate positioning, in particular to a license plate positioning algorithm that combines affine invariant corner features and visual color features. Background technique [0002] With the development of information technology and data communication technology, intelligent transportation has become the development direction of the future transportation system. License plate recognition is the main component of intelligent transportation, and has been widely used in many fields such as public security system law enforcement, highway toll system, monitoring system and road control. License plate recognition is mainly composed of four parts: image acquisition, license plate location, character segmentation and character recognition. From figure 1 It can be seen from the above that license plate location is one of the most critical steps in license plate recognition, and its quality is related to the success of...

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
IPC IPC(8): G06K9/46
CPCG06V10/56
Inventor 冯欣陈庄张杰张凌杨峰崔少国
Owner CHONGQING UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products