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Detecting roads using monocular vision is a very challenging task as the detection algorithm must be able to deal with complex real-road scenes. In this paper, we describe an algorithm for general path segmentation. There are three main technical contributions of the approach. First, a path segmentation framework is presented, which formulates road detection as a Bayesian posteriori estimation problem...
In the field of intelligent vehicle systems (IVS), color and edge of lane markings are important features for vision-based applications. This paper proposes a method to detect lane marking based on a fusion approach which combine color and edge lane marking information. Firstly, by knowing the vehicle speed the road surface region of interest is extracted using the typical stopping distance. Secondly,...
Road marking is a key visual cue for driving in structured environments like highways and urban roads. Road marking detection plays an important role in advanced driver assistant systems and autonomous driving. Robust road marking detection is challenging for the variation of road scenes, the degradation of the markings and the changes of the illumination. Traditional algorithms mainly use the grayscale...
We present a robust real-time vision-based system for vehicle tracking and categorization, developed for traffic flow surveillance. We propose a robust segmentation algorithm that detects foreground pixels corresponding to moving vehicles. Experimental results based on four large datasets show that our method can count and classify vehicles with a high level of performance (more than 98%).
Number plate recognition has been used widely for access control, congestion control, vehicle management, security control and vehicle behavior monitoring system. This study discusses the importance of number plate recognition and its corresponding application in different countries. Various methods for recognizing number plates are reviewed. Most of the systems are able to deliver good recognition...
Lane detection and tracking and departure warning systems are important components of Intelligent Transportation Systems. They have particularly attracted great interest from industry and academia. Many architectures and commercial systems have been proposed in the literature. In this paper, we discuss the design of such systems regarding the following stages: pre-processing, detection, and tracking...
When moving towards fully autonomous navigation, safety plays the most important role for both pedestrian and driver. This paper proposes a method to estimate the lane road region of interest based on the stopping typical distance of a vehicle required by the current speed of the vehicle. This was achieved by taking advantage of the difference in color of the road surface given by the lane marking...
For autonomous navigation the real-time processing is crucial. This paper proposes a method to detect the lane markings in real-time using the advantage of parallel processing. A region of interest is constrained by the current velocity of a vehicle. The segmentation was achieved by utilizing a difference in color between lane marking and road pavement. The overall process is divided into three steps...
The aim of the project is to detect and recognize traffic signs in video sequences recorded by an onboard vehicle camera. Traffic Sign Recognition (TSR) is used to regulate traffic signs, warn a driver, and command or prohibit certain actions. A fast real-time and robust automatic traffic sign detection and recognition can support and disburden the driver and significantly increase driving safety...
The paper aims at providing an intelligent driver assistance system on mobile devices, which is mainly composed of the two parts - off road warning and distance warning of front vehicles. In this application, the paper proposes an efficient lane and front vehicles detection and tracking method which has been experiments on mobile phones. The method is proved to be efficient and practical even though...
Prohibitory traffic signs play an important role in guiding, warning and regulating traffic system. As driving over the speed limit is often the major cause of accidents, detecting this group of prohibitory signs may reduce this danger. This paper presents an approach to detecting speed limit signs at night mode which is based on Multi-Scale Retinex Color Restoration and Hough Transform. Experiment...
We present a novel approach for vision-based road direction detection for autonomous Unmanned Ground Vehicles (UGVs). The proposed method utilizes only monocular vision information similar to human perception to detect road directions with respect to the vehicle. The algorithm searches for a global feature of the roads due to perspective projection (so-called vanishing point) to distinguish road directions...
Speed limit determination systems for cars based on vision are more and more developed. Roadsign detection is nowadays a well managed problem. However, in some situations this information is not sufficient to know the speed limitation. Restrictions are sometimes applicable and specified by subsigns. These small rectangles often provide essential information about the applicability scope (vehicle type,...
This paper presents a rear obstacle detection system based on depth information obtained from Kinect sensor. The proposed system can be used for parking assistance applications and backup aid. It improves the false detection rate in single view based algorithms by using depth information. In addition, real distance to obstacles can be calculated by depth information. It is possible to alarm to driver...
In this paper, we propose novel block-based techniques for robust extraction of lane marking edges in complex scenarios, such as in the presence of shadows, vehicles, other road markings etc. The techniques are based on the properties of lane markings and involve a two-stage processing: (1) generation of customized edge maps using histograms of gradient angles, and (2) directional signed edges in...
A method combines Top-hat Transformation, Morphological Gradient and Background Subtraction is presented in this paper to solve the question of cast shadows and split of vehicle. The method adopts top-hat transformation both on input image and background image to remove the shadows and detect road lines respectively. Then morphological gradient is obtained by multiple structuring elements. The final...
The idea of safe and smart vehicles has been thoroughly researched over the past decades to ensure drivers' safety from possibly dangerous situations. This paper presents a brief review of different applications of image processing and computer vision techniques in smart vehicles. To detect other on-road vehicles, researchers have approached the problem from various angles; with solutions ranging...
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...
In this paper, we proposed a robust lane detection method. This method uses the globalized probability of boundary (gPb) algorithm as boundary detector and non-unique B-spline (NUBS) as the road model. The gPb algorithm combines the local information, like brightness, color and texture features, with global information derived from spectral partitioning and is robust against shadow, and illumination...
This paper proposes an new algrithem framework for video based vehicle âtailgate' behavior detection in urban road junction. Based on the road traffic regualtion about the illegal parking behavior definition, the author proposes traffic lights signal monitor, vehicle tracking and road conjestion detection algrithems in the real time video analyse. The measured parameters including vehicles' trojactory,...
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