The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Vehicle detection and recognition from aerial imagery provides useful information for local vehicle volume estimation and traffic monitoring. In this paper, we propose a method that accurately detects vehicles in urban environment using a probabilistic classification method followed by a refinement based on object segments. Both classification and segmentation methods make use of coregistered aerial...
To enhance the robustness of the vehicle detection system, an effective algorithm to identify the lighting conditions (daylight, night, lowlight (dawn, dusk)) based on histogram analysis is presented in this paper. The algorithm consists of two procedures: extracting and updating background image, and generating a lighting conditions classifier based on background image analysis. The algorithm is...
This paper proposes a method to track vehicle in highway using CAMShift-based method. The Continuously Adaptive Mean Shift (CAMShift) is a well-known algorithm in object tracking. However, the ordinary CAMShift works fairly well only for tracking object that can identify by hue, when the difference between object color and background is large. This is not the case in vehicle tracking. The objective...
This paper proposes a novel parking spaces detection algorithm which is based on image segmentation and local binary pattern. The vehicles are usually contains a lot of compositions, while the vacant parking spaces' composition is relatively small. According to this characteristic, we segment the parking image. To judge whether each parking area has a large number of small split or not, can achieve...
This paper proposes a vision based multiple vehicle detection and tracking system. Vehicle tail light information is used to localize vehicle potential region, then each candidate is verified by a back propagation neural network (BPNN) trained by Gabor feature set. In the multiple vehicle tracking stage, multiple scale vehicle tracking, same color vehicle occlusion and observation model updating problem...
In this paper, a clustering method of adjacent frames is proposed for vehicle flow statistics to overcome the fault of low robustness of video-based detection algorithms in complex environments. In the method, the boundaries of the abrupt or gradual visual content changing in consecutive video frames are described by color and intensity histogram method. The clustered frames containing different vehicles...
Among the diverse applications of computer and communication technologies, Intelligent Transport System aids in simplifying transport problems. Its aim is to gather data and provide timely feedback to traffic managers (traffic policemen) and road users. The various problems involved in processing real-time traffic data has been addressed in several areas of research that includes vehicle detection,...
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...
In computer vision-based Intelligent Transportation Systems (ITS), one of the key techniques is to exactly detect the vehicles. The common way for vehicle detection is the background difference method. In this paper, we introduce several background extraction and updating methods and develop a new background extraction and update method based on histogram in YCbCr color space. By using YCbCr color...
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...
Moving vehicle detection is an important part in intelligent transportation system applications. The purpose is to track each moving vehicle in the video frames. This paper analyzes the background generation and shadow removal methods in traditional background subtraction approach, and presents a simple algorithm to generate and update color background image based on statistical method at intersection...
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...
Delay of signalized intersection has been estimated not only by manual method but also some intersection models. Long queues of lanes will make it difficult for collecting data manually and delay calculated by signalized intersection models may not be perfect for a particular intersection. In this paper, we design a system that can calculate delay automatically based on image processing technology...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.