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Vehicle license plate identification system is an image-processing technology used to identify vehicles by their license plates. This technology is used in various security and traffic applications. This data is also used for enforcement, data collection, and can be used to keep a time record on the entry or exit of vehicles for automatic payment calculations. The significant advantage of this system...
This paper proposes a new algorithm to make real time dispatching decisions in open-pit mines based on discrete position information. New methods are presented to estimate the probability density function for the position of each vehicle across the mine. New heuristic rules are then presented that use current local data gathered by peer to peer communication systems and vehicle position estimates...
The popularity of surveillance cameras used in traffic management systems have produced large quantities of video data that cannot be processed easily by humans. We present a method used on high resolution traffic surveillance videos to track and estimate vehicles' state when the cameras are mounted on moderate height structures typically less than 10 meters. This tracking method enables a number...
Tilt correction is a very crucial and inevitable task in the automatic recognition of the vehicle license plate (VLP). In this paper, according to the least square fitting with perpendicular offsets (LSFPO) the VLP region is fitted to a straight line. After the line slope is obtained, rotation angle of the VLP is estimated. Then the whole image is rotated for tilt correction in horizontal direction...
Occlusion is an important problem of the moving target detection. This paper proposed a new method of vehicle detection according to the deficiencies of common vehicle detection methods. Firstly, the background is modeled through the improved histogram-mean model to extract more accurate background model and update in real-time; then we obtained the background through background subtraction and supplement...
In this paper, we evaluate several low dimensional color features for object retrieval in surveillance video. Previous work in object retrieval in surveillance has been hampered by issues in low resolution, poor segmentation, pose and lighting variations and the cost of retrieval. To overcome these difficulties, we restrict our analysis to alarm-based vehicle detection and as a consequence, we restrict...
As an important feature of vehicle, vehicle color plays a significant role in Intelligent Transportation Systems. Traditional vehicle color recognition using experience-based artificial demarcation of threshold and voting method to identify, can't meet the requirements of the recognition rate in complex environments of video traffic and subdivision of vehicle color. In this paper, we present a method...
Automatic License Plate Recognition is useful for real time traffic management and surveillance. License plate recognition usually contains two steps, namely license plate detection/localization and character recognition. Recognizing characters in a license plate is a very difficult task due to poor illumination conditions and rapid motion of vehicles. When using an OCR for character recognition,...
As traffic surveillance technology continues to grow worldwide, computer vision-based vehicle tracking is becoming increasing important. One of the key challenges with vehicle tracking is dealing with high density traffic, where occlusion often leads to foreground splitting and merging errors. In order to help solve this problem, global features such as color or local features like corners can be...
When considering the need for an intelligent transportation mode based upon the fact that car travel is still the consumer's first choice, we decided to explore the idea of collective taxis. More precisely, we are seeking to provide an autonomous high quality door-to-door service, affordable by almost everyone, covering the entire urban area, simply by allocating in an optimal way more than one passenger...
We present and evaluate a novel scene descriptor for classifying urban traffic by object motion. Atomic 3D flow vectors are extracted and compensated for the vehicle's egomotion, using stereo video sequences. Votes cast by each flow vector are accumulated in a bird's eye view histogram grid. Since we are directly using low-level object flow, no prior object detection or tracking is needed. We demonstrate...
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...
In this paper algorithms are presented to extract lane markers and their properties from monoscopic camera images. A filter approach that takes into account the visual appearance of the markers is presented. Another contribution constitutes the measurement of physical marker width and length from perspectively distorted images using only the calibrated camera images. Also distances between markers...
In this work, a traffic surveillance system, which contains background subtraction, occlusion handling and tracking steps, is designed in order to extract traffic parameters from low resolution video sequences. In every step, utilized algorithms are improved and more accurate results than existing approaches are obtained. Additionally, a new automatic Region of Interest detection approach is proposed...
Very large format video or wide-area motion imagery (WAMI) acquired by an airborne camera sensor array is characterized by persistent observation over a large field-of-view with high spatial resolution but low frame rates (i.e. one to ten frames per second). Current WAMI sensors have sufficient coverage and resolution to track vehicles for many hours using just a single airborne platform. We have...
The support vector machine (SVM) provides a robust, accurate and effective technique for pattern recognition and classification. Although the SVM is essentially a binary classifier, it can be adopted to handle multi-class classification tasks. The conventional way to extent the SVM to multi-class scenarios is to decompose an m-class problem into a series of two-class problems, for which either the...
Application-oriented electronics methods for detection of parking traffic jams simplify the control systems and increase the efficiency. This paper explores the possibility of traffic jam forecast. Main target of this paper is to show possibility to forecast traffic jam before it starts and not only detect it. This paper proposes jam forecasting and detection technology using set of traffic flow data...
Vehicle license plate recognition (VLPR) is one of the most important topics of using computer vision and pattern recognition in intelligent transportation systems. In order to recognize a license plate (LP) efficiently, the location of the LP in most cases must be extracted in the initial step. In this proposed algorithm, initially, HSI color model is adopted to select automatically statistical threshold...
Against vertical Sobel operator that most license plate detection (LPD) algorithms adopt, this paper presents a robust and real-time preprocessing method to enhance both edge density and intensity of license plates under various outdoor and indoor environments. The proposed method applies HL subband feature of 2D discrete wavelet transform (DWT) twice to significantly highlight the vertical edges...
We present a new multi-stage algorithm for car and truck detection from a moving vehicle. The algorithm performs a search for pertinent features in three dimensions, guided by a ground plane and lane boundary estimation sub-system, and assembles these features into vehicle hypotheses. A number of classifiers are applied to the hypotheses in order to remove false detections. Quantitative analysis on...
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