Visual detecting and counting method for vehicle flow rate under complex road condition

Abstract

The invention discloses a visual detecting and counting method for the vehicle flow rate under a complex road condition, belongs to the technical field of machine vision, and solves the problems that a visual detection method for counting the vehicle flow rate by counting the area of moving objects is extremely low in the counting accuracy and greatly influenced by the image quality under complex roads in which vehicles, pedestrians and non-motor vehicles are mixed. The method comprises that initial information is set; video images are read in a cyclic way, and an MSRCR algorithm is used to realize illumination equalization and color balance at the same time; an AdaptiveMedian algorithm is used for background modeling, and a movement foreground is extracted; opening operation is carried out on the foreground, and bonded moving objects are separated while noises are removed; a contour is searched, the area is calculated, and the contour is filled if the area is lower than a threshold; vehicles in the foreground are identified by utilizing Haar characteristics and an AdaBoost classifer; and vehicles in each frame of foreground are identified, and positions of the vehicles are recorded. Thus, the method is used to extract moving objects under the complex road condition accurately, identify the vehicles specifically, and counting the vehicles in the real-time collection video.

Description

technical field [0001] A visual detection and counting method for traffic flow under complex road conditions, which is used to accurately extract moving targets under complex road conditions, specifically identify vehicles in them, and count the number of vehicles in real-time collected videos, belongs to the technical field of machine vision. Background technique [0002] "Machine vision" is a rapidly developing branch of artificial intelligence. Simply put, machine vision is the use of machines instead of human eyes for measurement and judgment. The machine vision system converts the captured target into an image signal through the machine vision product (that is, the image capture device, which is divided into CMOS and CCD), and transmits it to a dedicated image processing system to obtain the shape information of the captured target. According to the pixel distribution and Information such as brightness and color is converted into digital signals; the image system perfo...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to solve the problem of counting the area of ​​moving objects in the prior art based on the visual detection method for counting the traffic flow. On complex roads where cars, pedestrians and non-motor vehicles are mixed, the counting accuracy is extremely low and is affected by image quality. For larger problems, the present invention provides a method for visual detection and counting of traffic flow in complex road conditions

Images