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

Road vehicle shadow feature extraction method

A technology of shadow feature and extraction method, applied in image data processing, instrument, calculation, etc., can solve the problems of affecting vehicle detection performance, missed detection, less obvious, etc., to achieve good extraction effect, less time-consuming, and improved detection rate Effect

Active Publication Date: 2015-07-08
HANGZHOU DIANZI UNIV
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This type of method has a high accuracy rate for the shadow detection of close-range vehicles. However, for the less obvious shadows of distant vehicles, the above-mentioned fixed threshold shadow area segmentation extraction and area screening algorithms are prone to miss detection, which seriously affects the vehicle detection performance.

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
  • Road vehicle shadow feature extraction method
  • Road vehicle shadow feature extraction method
  • Road vehicle shadow feature extraction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0047] The specific embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0048] Such as figure 1 As shown, a road vehicle shadow feature extraction method, the specific steps are as follows:

[0049] Step 1: Extraction and preprocessing of video data:

[0050] 1-1. Read the video data of the vehicle in front from the camera, and perform geometric constraints on each frame of image in the video data.

[0051] Suppose the width and height of the original image A in the video data are Aw and Ah respectively, and the original image A is intercepted through geometric constraints to obtain the intercepted image B; the width of the image B is [Aw / 4,3×Aw / 4], the height of B is [Ah / 2-Ah / 10, Ah-Ah / 10].

[0052] 1-2. Extract the V component in the HSV channel as a single-channel image VImg.

[0053] 1-3. Extract the binarized edge map SImg of the single-channel image VImg.

[0054] Step 2: Shadow Threshold C...

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 road vehicle shadow feature extraction method. Firstly, data needing to be processed are reduced and road surface areas of an image are extracted through a geometric constraint method, gauss convolution is conducted on the road surface areas, gray level upper limit threshold values of shadows are obtained, the image is scanned in lines through the threshold values, collection of shadow lines is acquired, and location information of the shadow lines is recorded. The shadow lines are divided into standard shadow lines and ordinary shadow lines according to difference value between an upper neighborhood and a lower neighborhood, the standard shadow lines are stored in a result set, shadow features of vehicles are simulated according to location relation fusion between the standard shadow lines and the ordinary shadow lines, and areas which may include the vehicles are extracted. By means of the shadow lines extracting and fusing to simulate existing feature extraction method based on the areas, the extraction effect of most of the vehicles is good. The consuming time is small, the rate of missing detection is low, the detection effect is good for distant vehicles particularly, and the detection rate of a system is improved.

Description

technical field [0001] The invention belongs to the technical field of feature extraction, in particular to a road vehicle shadow feature extraction method, in particular to a vehicle shadow feature extraction method based on shadow line fusion. Background technique [0002] With the rapid development of transportation, traffic safety is becoming more and more important. Detection of vehicles ahead in advanced driver assistance systems is a central problem of the system. Vehicle feature extraction technology (Hypothesis Generation) is a key part of the front vehicle detection technology. It can realize efficient vehicle detection by extracting the feature area that may contain vehicles in the image. The shadow feature of the vehicle is a continuous and large shadow area at the bottom of the vehicle in front. The average gray level of the shadow feature of the vehicle in the image is always lower than its neighbors and corresponds to the vehicle one by one. It is located at ...

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): G06T7/00
Inventor 徐向华周士杰吴月菲
Owner HANGZHOU DIANZI UNIV
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