Method for measuring vehicle speed based on fuzzy image

A fuzzy image and vehicle speed technology, applied in image analysis, image data processing, devices using optical methods, etc., can solve the problems of inconvenient installation of speed measuring equipment, complicated installation, and complicated measurement process, and achieve simple and fast measurement and calculation of vehicle speed. The effect of fewer cameras and fewer parameters required

Active Publication Date: 2020-02-28
CHINA SCI INTELLICLOUD TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

There are many cameras used in binocular and multi-eye cameras, the installation is troublesome, and stereo matching is difficult
Based on the combination of panoramic cameras and close-up cameras, there are also shortcomings such as many cameras required and complicated installation.
At the same time, the traditional image speed measurement method generally needs to take multiple images, and then compare the multiple images to finally calculate the vehicle speed. The corresponding vehicle speed measurement process is complicated.
Therefore, aiming at the shortcomings of inconvenient installation of speed measurement equipment and complicated measurement process in the traditional vehicle speed measurement method, the present invention discloses a method for measuring vehicle speed based on fuzzy images

Method used

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  • Method for measuring vehicle speed based on fuzzy image
  • Method for measuring vehicle speed based on fuzzy image
  • Method for measuring vehicle speed based on fuzzy image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0037] A kind of method of measuring vehicle speed based on fuzzy image of the present embodiment, such as figure 1 As shown, a method for measuring vehicle speed based on fuzzy images includes the following steps:

[0038] Step 1. Shooting a single vehicle scene image in real time;

[0039] Step 2, calculating the calibration function between the road surface distance and the pixel distance according to the vehicle scene image;

[0040] Step 3, extracting the vehicle image in the current vehicle scene image;

[0041] Step 4. Carry out fuzziness calculation on the vehicle image and output the fuzzy pixel value;

[0042] Step 5. Calculate the driving speed of the vehicle according to the calibration function, the blurred pixel value, and the shooting exposure time.

[0043] The camera is used to capture the scene image of the vehicle, and the lens of the camera is installed facing the driveway to ensure that the lens of the camera can completely capture the license plate of ...

Embodiment 2

[0048] This embodiment is further optimized on the basis of Embodiment 1, and the following formula is used to calculate the vehicle speed:

[0049]

[0050] Where: v is the speed of the vehicle;

[0051] h(x) is a calibration function;

[0052] z is the minimum pixel distance between the vehicle image and the first calibration line segment;

[0053] △z is the fuzzy pixel value;

[0054] Δt is the shooting exposure time.

[0055] The sub-steps of calculating the calibration function in step 2 are as follows:

[0056] Step 2.1, if figure 2 As shown, two first calibration line segments and second calibration line segments that are perpendicular to the length direction of the road surface and parallel to each other are respectively selected in the vehicle scene image, and the actual lengths of the first calibration line segment and the second calibration line segment are measured as d 1 and d 2 ;

[0057] Step 2.2, calculate the pixel lengths of the first calibration l...

Embodiment 3

[0066] This embodiment is further optimized on the basis of the above-mentioned embodiment 1 or 2. In the step 1, a high-speed camera is used to shoot the vehicle image, and several groups of fixed shutter exposure times are set, and the fixed shutter exposure time is adjusted according to the ambient light intensity. .

[0067] In order to ensure the clarity of the captured vehicle scene images as much as possible, a high-speed camera is selected to capture vehicle images, which can capture high-speed vehicles in time. At the same time, several groups of fixed shutter exposure times are set according to the ambient light intensity. When the ambient light intensity is weak, the corresponding fixed shutter exposure time is longer; when the ambient light intensity is strong, the corresponding fixed shutter exposure time is shorter.

[0068] Other parts of this embodiment are the same as those of Embodiment 1 or 2 above, so details are not repeated here.

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Abstract

The invention discloses a method for measuring vehicle speed based on a fuzzy image. The method for measuring the vehicle speed based on the fuzzy image comprises the following steps that step 1, a single vehicle scene image is shot in real time; step 2, a calibration function between road surface distance and pixel distance is calculated according to the vehicle scene image; step 3, a vehicle image is extracted from the current vehicle scene image; step 4, fuzziness calculating is carried out on the vehicle image, and a fuzzy pixel value is output; and step 5, the vehicle speed is calculatedaccording to the calibration function, the fuzzy pixel value and shooting exposure time. According to the method for measuring the vehicle speed based on the fuzzy image, the single image is used forcalculating the vehicle speed in the image by a deep learning model evaluating the fuzziness, and the installation and measurement process of vehicle speed measuring equipment can be effectively simplified.

Description

technical field [0001] The invention belongs to the technical field of vehicle speed measurement, in particular to a method for measuring vehicle speed based on fuzzy images. Background technique [0002] At present, video-based speed measurement methods in traffic speed measurement mainly include large-scale speed measurement methods, binocular or multi-eye camera speed measurement methods, and speed measurement methods combining panoramic cameras and close-up cameras. Among them, in the large scene speed measurement method, the measurement accuracy is greatly affected by the light and the interference of other vehicles. There are many cameras used in binocular and multi-eye cameras, the installation is troublesome, and stereo matching is difficult. Based on the combination of panoramic cameras and close-up cameras, there are also shortcomings such as many cameras required and complicated installation. At the same time, the traditional image speed measurement method gener...

Claims

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Application Information

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IPC IPC(8): G01P3/38G06K9/00G06T7/00
CPCG01P3/38G06T7/97G06V20/54
Inventor 王飞
Owner CHINA SCI INTELLICLOUD TECH CO LTD
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