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In this paper we present a new lane markers detection and estimation algorithm aiming to improve lane detection methods. We first estimate the area of lane marking using the profile of the lane estimation in a confidence map. After that a fitting method is applied to improve the lane marker detection accuracy. To track our lane markers over time and make the association between two iteration, we use...
This contribution describes a system for accurate, robust and fast six degrees-of-freedom object pose estimation based on multi-feature models and a recursive filtering approach in the context of autonomous vehicle recharging. Feature measurements are integrated sequentially to allow full control over the feature detection algorithms and the influence on the estimate. This makes the system able to...
Nowadays, electronic toll collection (ETC) is used extensively in many countries and places, but many drivers evade detection by covering, altering or otherwise obscuring their license plates. In order to detect vehicles attempting to evade paying tolls, this study aims to identify vehicles without requiring the license plate information. Unlike traditional vehicle license plate recognition, in this...
In this paper, a robust traffic sign recognition system is introduced for driver assistance applications and/or autonomous cars. The system incorporates two major operations, traffic sign detection and classification. The sign detection is based on color segmentation and incorporates hue detection, morphological filter and labeling. A nearest neighbor classifier is introduced for sign classification...
The recent trend of proliferation of road accidents and fatalities, calls for a methodology that can appease the burden on the drivers during certain crucial moments, requiring fast response and decision making. This paper expatiates a novel and effective procedure for determining the steering angle required to keep the vehicle in the middle of the lane. The procedure used is divided in multiple stages...
Lane detection plays an important role in intelligent vehicle systems. Therefore, this paper presents a robust road lane marker detection algorithm to detect the left and right lane markers. The algorithm consists of optimization of Canny edge detection and Hough Transform. The system captures images from a front viewing vision sensor placed facing the road behind the windscreen as input. Then a series...
This paper presents a method for estimating the current lane number in which the vehicle is traveling. An important component of visual automobile safety systems rely on knowledge of the lane number to know how far the vehicle is from the exit lane. The method uses taking the Inverse Perspective Map of an image to get a top view of the road and then detects multiple lanes using Hough transform line...
The current vehicle tracking algorithms cannot meet the requirements of high robustness in engineering application. A co-training algorithm based on on-line boosting for vehicle tracking is proposed. In this algorithm, first the vehicle region of interest is detected by vehicle-shadow feature and vehicle horizontal edge feature. Then the vehicle region of interest is verified by off-line classifiers...
Vehicle detection with a monocular video sensor offers significant potential in a wide area of promising automotive applications. In this work the shadows in daylight scenes are used to detect vehicles in low-quality camera images and determine their positions and velocities in relation to the own vehicle. We propose a new algorithm that segments shadows in a top-down-view. In contrast to other works...
Lane detection is an important component of many intelligent transportation systems. This paper proposes a novel lane departure algorithm for detecting lane markers in images acquired from a forward-looking vehicle-mounted camera. The interested targets of the algorithm are always the nearest two lanes to the automobile, and it can detect the left and right lane separately, which would generate the...
Visual feature-based tracking systems need to adapt to variations in the appearance of an object and in the scene for robust performance. Though these variations may be small for short time steps, they can accumulate over time and deteriorate the quality of the matching process across longer intervals. Tracking in aerial imagery can be challenging as viewing geometry, calibration inaccuracies, complex...
Multi-megapixel cameras are transforming airborne video surveillance by enabling persistent imaging of extremely large areas while providing sufficient pixel density to resolve both vehicles and pedestrians. The sheer spatial and temporal volume of data has rendered human scanning of expansive images for miniscule moving objects intractable, underscoring the importance of automated detection and tracking...
Frequently, there is a need to identify vehicle license plates (VLP) in images taken from a camera that is far away from the vehicle for security. The extracted information from vehicle license plates is used for enforcement, access-control, and flow management, e.g. to keep a time record for automatic payment calculations or to fight against crime. That's make license plates detection crucial and...
For improving the performance of lane detection in complicated road environment, a novel detection method of structured lane based on gradient-pairs constraint is proposed. After image preprocessing and edge detection, the parametric equation about the mid-line of the road is obtained via Hough Transform with the assumption that a pair of edge pixels on both sides of lane usually has opposite gradient...
In this paper, we present an effective and robust visual vehicle tracking algorithm using particle filter and multiple cues. A stable histogram-based framework is extended to evaluate color, edge, texture and motion cues in structured environments. This framework is suitable for practical conditions since in many applications the object motions are limited by structure of the surveillance scene. We...
In vision navigation tasks, lane marks on roads are very important vision cues. Usually, these lane marks can be detected using Hough transform or vanishing point detection. However such methods always need great computing power, and they are difficult to be realized on board processors in real-time. In this paper, a vanishing point like reference point is set as a support vector. The points on the...
In this paper, we present a computationally efficient and robust lane detection algorithm based on Hough transform. The proposed method first extracts lane markings by applying 1D ridge detector to each row of an image. Given the extracted ridge points, the lane is then detected by applying Hough transform. Unlike the conventional methods, we consider only small set of line candidates which pass through...
An improved monocular vision method is studied for intelligent vehicle to detect the preceding car in the structural road environment. Through identifying the edges of the car, the object is detected; the false object is eliminated and the eligible object expressed as a 2-D model is acquired. Then the location of object in the next frame is predicted by Kalman filter, and the object is detected near...
In this paper, a LIDAR-based road and road-edge detection method is proposed to identify road regions and road-edges, which is an essential component of autonomous vehicles. LIDAR range data is decomposed into signals in elevation and signals projected on the ground plane. First, the elevation-based signals are processed by filtering techniques to identify the road candidate region, and by pattern...
Newly emerging, highly complex Advanced Driver Assistance Systems (ADAS) fuse the output of various system modules (e.g., lane detection, object classification). Such knowledge fusion is realized in order to gain additional information of the environment allowing for complex system tasks as path planning, the active search for specific objects and task-specific analysis of the environment. As part...
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