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In the intelligent transportation system, the geometry for the street is an important factor in vehicle monitoring. It helps to point out areas of interest, reduce computing costs, increased accuracy in detecting and identifying objects and facilitate data collection. In this paper, a new robust method of extracting the geometric model of the road is presented. The method is based on vehicle motion...
Real-time lane detection and tracking is one of the most reliable approaches to prevent road accidents by alarming the driver of the excessive lane changes. This paper addresses the problem of correct lane detection and tracking of the current lane of a vehicle in real-time. We propose a solution that is computationally efficient and performs better than previous approaches. The proposed algorithm...
While current implementations of LIDAR-based autonomous driving systems are capable of road following and obstacle avoidance, they are still unable to detect road lane markings, which is required for lane keeping during autonomous driving sequences. In this paper, we present an implementation of semantic image segmentation to enhance a LIDAR-based autonomous ground vehicle for road and lane marking...
Lane detection is one important process in the vision-based vehicle assist system. The results of lane edge detection play an important role in feature-based lane detection. The complicated conditions of road make the correct edge detection of lane markings become very challenging. In order to get an ideal edge of lane markings in road image, a method of lane edge detection based on Canny algorithm...
Creating road maps is essential for applications such as autonomous driving and city planning. Most approaches in industry focus on leveraging expensive sensors mounted on top of a fleet of cars. This results in very accurate estimates when exploiting a user in the loop. However, these solutions are very expensive and have small coverage. In contrast, in this paper we propose an approach that directly...
This paper reports an image-based localization for automated vehicle. The proposed method utilizes a mono-camera and a low-cost velocity and inertial sensor to estimate the vehicle pose. Image template matching is applied to provide a correlation distribution between the captured image and a vector structured digital map. A probability of the vehicle pose is then updated using the obtained correlation...
Road markings are important information of transport systems for drivers or intelligent vehicle. Efficient road markings feature extraction is pre-requisite to road markings detection, recognition and visual localization. However, most of previous lane markings feature extractors are operating on conventional images, the feature extraction methods for omnidirectional images are rarely considered in...
This paper explores the feasibility of using a low-cost embedded ARM-based system for real-time vehicle recognition and identification through image processing. The main features of the system include: vehicle detection, speed measurement, and vehicle identification by license plate number recognition, the information obtained is then send to a database on a server in a local network. An ODROID-U3...
The demand of High Definition Maps (HD-Maps) has been increasing, especially for autonomous vehicle application. Usually, HD-Map is created by scanning the road using LiDAR sensor and reconstructing the road on 3D world to capture all aspects of road properties. One of the important properties of a road is its edge or boundary. In this paper, we propose end-to-end 3D Encoder-Decoder Convolutional...
The main objective of this working is to bring a novel resolution for the quadrilateral pattern fixing problem providing endless advantages to that including the capture of the strings on license areas at the all sorts of time zones in the all assorted states of ambience conditions involving foggy, snowy and darkness forms. Blender system of our technics applied a well-recognizing differentiation...
The modern era has witnessed huge spike in the number of road accidents and fatalities. The common origin of traffic accidents is driver error. This is not going to change anytime soon thanks to the immense number of cell-phone users, in-car entertainment audio and video systems, and finally abundant traffic. There's one death every four minutes due to road accident in India. Such severe situation...
The paper presents a new method of vehicle speed estimation using image data processing. The presented method employs conversion of greyscale input images into binary form. Image conversion into binary form is based on small gradients in the input images. Contents of the obtained binary images correspond with traffic scenes presented in the input images. Vehicle speed is estimated on the basis of...
In this paper, a new multi-resolution CMOS imager sensor with trapezoid pixel array, called TZOID, is presented. It was designed for traffic monitoring to detect the speed and location vehicles approaching a signized intersection. It composes of significantly less number of pixels than a comparable image sensor used in similar application. The unique trapezoid image sensor design eliminates computationally...
This paper proposes a novel suspected vehicle detection (SVD) system for detecting vehicles moving on roads without a license plate. To detect vehicles from a still image, a symmelet-based approach is derived to determine their ROIs without using any motion feature. A symmelet is a pair of an interest point and its corresponding symmetrical one. This paper modifies the non-symmetrical SURF descriptor...
Automatic image annotation is a technique by which computer systems automatically assigns appropriate Keywords to input digital image. Smart cities are characterized by large volume of data, one of the prominent data types are images. In present research, images of smart cities are collected and then using automatic image annotation, several relevant indexing terms are proposed for every image. Using...
In this paper, we propose a novel approach for road width measurement from high resolution satellite or aerial images. The proposed approach has three main steps. First, we extract line segments and road center lines on the given remote sensing images. Second, we could obtain many pairs of parallel lines with width information by computing the positional relationship between each other. Then K-means...
Massive traffic scene data for algorithm research and model training is the fundamental for self-driving car technology development. In the procedure of scene image labeling, the most accurate method is manual annotation, but with the increasing of the amount of image data, artificial annotation method becomes infeasible due to its disadvantages of vast cost, inefficiency and subjective deviation...
The lane marking detection task is an essential process in the field of semi-autonomous and autonomous navigation. This paper proposes a method that combines the color and edge information to robustly detect the lane marking within the image either located far on near to the vehicle. Firstly, the region of interest is extracted from the image. Secondly, the set of lane marking features are extracted...
Autonomous cars establish driving strategies using the positions of ego lanes. The previous methods detect lane points and select ego lanes with heuristic and complex postprocessing with strong geometric assumptions. We propose a sequential end-to-end transfer learning method to estimate left and right ego lanes directly and separately without any postprocessing. We redefined a point-detection problem...
In this works, a novel lane reference calculation approach is developed in order to define a safe and optimal trajectory to be tracked by a road vehicle. In a first step of the design, the lane boundaries are extracted using a vision based lane detection algorithm, which consists in an homography transformation that helps to extract features from the captured image frames in order to map a set of...
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