Front car identification method based on monocular vision

A recognition method and monocular vision technology, applied in the field of intelligent transportation, can solve problems such as rear-end collision accidents

Active Publication Date: 2014-01-29
YANGZHOU RUI KONG AUTOMOTIVE ELECTRONICS
View PDF2 Cites 17 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] Real-time perception and recognition of the driving environment is one of the core issues of autonomous driving and active safety. There are often vehicles that are closer to the vehicle on the road ahead, which may easily cause rear-end collisions.

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
  • Front car identification method based on monocular vision
  • Front car identification method based on monocular vision
  • Front car identification method based on monocular vision

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0066] Create template databases for multiple vehicle types and non-vehicle types. Grayscale each vehicle image in the template library and normalize it to a 64×64 image with bilinear interpolation. Then use the filter coefficient as h 0 ,h 1 , g 0 , g 1 , h 0o ,h 1o Binary tree complex wavelet transform, filter the row and column of the image respectively, obtain the real part and imaginary part of the binary tree wavelet transform of the image, and calculate its amplitude, and form the image set of the binary tree complex wavelet transform of the image, After normalization and vectorization, it is used as the features of the template image. Use the two-dimensional independent component analysis method in step (4) to reduce the dimensionality of the feature sample set of the template library to obtain the feature with the maximum discrimination s is the vehicle area and non-vehicle area, i=1,2,...300 is the number of samples of each type of template library. The samp...

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 provides a front car identification method based on monocular vision. The method includes the steps that (1), an original image is collected from a vehicle-mounted camera, the edge of the image is extracted according to a Canny edge extraction method, influence of noise points is eliminated through morphological filter, projection is carried out in the horizontal direction, and an area of interest of a front car is obtained according to projection characteristics; (2), a shadow area at the car bottom is extracted and judged according to the geometrical shape of the shadow at the car bottom, edge characteristics are overlaid, and a car area is judged; (3), graying, normalization and binary tree complex wavelet transformation are carried out on small color images of candidate car areas of different shapes, and characteristic vectors are obtained; (4), the number of dimensions of the characteristic vectors is decreased through a two-dimension independent component analysis algorithm, the characteristic vectors are fed into a support vector machine based on a radial basis function kernel to be classified, and it is judged that whether the candidate car areas are the car area. Cars on the road ahead are detected accurately, and real-time and reliable road condition information can be supplied for unmanned cars.

Description

technical field [0001] The invention belongs to the field of intelligent transportation, and in particular relates to a method for judging whether there is a vehicle ahead. Background technique [0002] Real-time perception and recognition of the driving environment is one of the core issues of autonomous driving and active safety. There are often vehicles that are closer to the vehicle on the road ahead, which may easily cause rear-end collisions. The invention studies the fast positioning and judging method of the vehicle ahead in the dynamic scene, detects and analyzes the vehicle information appearing in front during the vehicle driving process, and can provide timely road environment information for the unmanned vehicle or the driver to comply with traffic conditions. rule. By referring to the latest research results of human visual cognition mechanism, computer vision and pattern recognition theory, research and design a fast, automatic and robust front vehicle judgme...

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): G06K9/00G06K9/60G06K9/34
Inventor 陈军
Owner YANGZHOU RUI KONG AUTOMOTIVE ELECTRONICS
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