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In this paper an automated vehicle detection and traffic density estimation algorithm has been developed and validated for very high resolution satellite video data. The algorithm is based on an adaptive background estimation procedure followed by a background subtraction at every video frame. The vehicle detection is performed through a further mathematical morphology and statistical analysis on...
A stereo vision based road scene segment and vehicle detection method was proposed in this paper. In the method, First, dynamic programming was used for stereo matching, and then mismatching pixels were removed by left-right-consistency check; Second, V disparity was built by computing the disparity map, and a fast projection based line detection method was used to detect lines in V disparity map,...
Vehicle counting system has a wide range of applications, from visual surveillance to intelligent transportation. Due to the different lighting conditions during the day and night, there is not a unified method to capture vehicles. To address this problem, we present unified vehicle detection and counting algorithm based on a new multiple feature background models using morphology and color difference...
One of the most important methods to solve the traffic congestion is to detect the incident state in a roadway. This paper describes the development of segmentation methods for road traffic monitoring aims at the acquisition and analysis remote sensing imagery of traffic figures, such as presence and number of vehicles, incident detection and automatic driver warning systems. We propose a strategy...
To prevent moving shadows being false detected as moving vehicles, this paper presents a Hue-Saturation Histogram Difference (HSHD) method for vehicles detection. In the method, H-S histogram of each frame in the detection area is counted firstly. Then, comparing the differences between histograms of two adjacent frames, the peak of differences may stand for a car. Experiments on videos shot in daytime...
This paper presents a new vision-based vehicle detection method for Forward Collision Warning System (FCWS) at nighttime. Also, lane detection is performed for assistance. To effectively extract the bright objects of interest, an essential image preprocessing including the tone mapping, contrast enhancement and adaptive binaryzation is applied in the nighttime road scenes. The characteristics of taillights...
This paper presents a vehicle detection algorithm for driver assistance system based on embedded vision architecture. Before generating the hypothesis, we propose to delimiter the search area. The Hough transform is used to detect the lines that delimit the search area. By doing so we can reduce the computation time and the false detection rate during the hypothesis generation phase. The search area...
Traditional vision based vehicle detection methods are more successful in detecting front and rear vehicles. However, the problem of detecting vehicles under various poses still presents a great deal of difficulty. Pose variation leads to limit the use of vision based driver assistance systems. In this paper, we present a Conditional Random Fields (CRFs) based algorithm that can detect vehicles under...
We propose a new traffic analysis framework using existing traffic camera networks. The framework integrates vehicle detection and image-based matching methods with geographic context to match vehicles across different views and analyze traffic. This is a challenging problem due to the low frame-rate of traffic-cams and the large distance between views. A vehicle may not always appear in a camera...
Vital problems in transportation such as mobility and safety of transportation, especially in highways and road ways, are considered as very important nowadays. Road traffic monitoring aims at acquisition and analysis of traffic signs, such as presence and numbers of vehicles, and automatic driver warning systems developed mainly for localization and safety purposes. In the past some methods have...
Optical systems are well suited for traffic observation and management. The real-time requirements can be met by implementation of appropriate image processing algorithms in hardware. Being one of the most important applications of optical sensors, vision-based vehicle detection and shape recognition for collecting information about road congestion, for driver assistance and for providing information...
This paper describes a novel method for detecting vehicles on a highway using two visual features: color and texture. Our method consists of a segmentation process computed on the L*u*v* color space and a texture feature extraction procedure based on Dual-Tree Complex Wavelet Transform. We also apply a denoising process using morphological operations to build a background model and make possible the...
Real-time image processing is a difficult work for traffic video monitoring. This paper proposed a method to detect and track vehicles on highway based on airship video and therefore calculate traffic parameters in real-time. A blocking road extraction was performed to determine the ROI, and automatically calculate the tilt of the road which contributes to vehicles detection. A lane marks registration...
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