Method and system for processing traffic monitoring video image in foggy day

A traffic monitoring and video image technology, applied in the field of intelligent transportation, can solve the problems of restricting wide application, difficult image recognition, affecting the accuracy of defogging, etc., and achieve the effect of accurate depth estimation, simple installation and debugging, and saving processing time

Inactive Publication Date: 2013-04-03
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

But today's video surveillance in the field of intelligent transportation is still not perfect
Therefore, even with the most advanced image acquisition equipment, it may not be effective due to the interference of various environmental factors during the shooting process, and image recognition problems in foggy conditions are one of them.
The problems of traffic video surveillance in foggy weather mainly include: (1) In foggy weather, blurred image information is not conducive to the monitoring personnel’s recognition of the required traffic information. Control and evidence collection of traffic violations, accidents, etc. will also be extremely disadvantageous
(2) When computer monitor

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  • Method and system for processing traffic monitoring video image in foggy day
  • Method and system for processing traffic monitoring video image in foggy day
  • Method and system for processing traffic monitoring video image in foggy day

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Embodiment Construction

[0023] The specific implementation process of the present invention will be described in detail below with reference to the accompanying drawings.

[0024] 1. Vehicle detection and tracking in traffic monitoring scenarios

[0025] The process of vehicle detection and tracking such as image 3 As shown, 1) collect vehicle images in the traffic monitoring scene, establish an image library, extract features from the vehicle images, and obtain the vehicle classifier in the traffic monitoring scene by training the machine learning method. 2) Initialize the background of the collected traffic monitoring images, and perform feature extraction on the traffic monitoring images. 3) Combine the classifier trained by the machine learning method in step 1) to perform vehicle detection and vehicle tracking.

[0026] 2. Create a region of interest

[0027] According to the detected vehicle driving area, and using the prior information of the traffic scene image, such as lane lines, traffi...

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Abstract

A method for processing a traffic monitoring video image in a foggy day includes: 1, detecting vehicles in traffic monitoring scene; 2, building area-of-interest, namely a driving area according to detected vehicle and pedestrian movement areas; 3, estimating road area depth ratio, and generating a depth image: estimating the road area depth ratio according to detected sizes, positions and moving directions of vehicles, building a traffic monitoring scene model, and generating a traffic monitoring scene depth image automatically; 4, building a traffic monitoring scene foggy day image degradation model: using the traffic monitoring scene depth image as an important parameter of foggy day image degradation, and building the traffic monitoring scene foggy day image degradation model; and 5, solving the traffic monitoring scene foggy day image degradation model, and recovering an image.

Description

technical field [0001] The invention relates to the field of intelligent transportation, in particular to a method and a system for processing video images of traffic monitoring in foggy days, which perform defogging processing on traffic monitoring videos in foggy days. Background technique [0002] Intelligent transportation has high requirements on the quality of image information collection and processing. However, video surveillance in the field of intelligent transportation is still not perfect. Therefore, even with the most advanced image acquisition equipment, it may not really be effective due to the interference of various environmental factors during the shooting process. The problem of image recognition in foggy weather is one of them. The problems of traffic video surveillance in foggy conditions mainly include: (1) In foggy conditions, the blurred image information is not conducive to the identification of the required traffic information by the monitoring per...

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Application Information

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IPC IPC(8): G08G1/01G06T7/00
Inventor 谭华春朱湧赵亚男谢湘陈涛章毓晋夏红卫王武宏
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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