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The division of police patrol districts affects patrol performance, such as average response time and workload variation. However, the possible sample space is large and the corresponding graph-partitioning problem is NP-complete. Moreover, the resulting patrol beats must be contiguous and compact. We propose a heuristic based, clustering method to divide a given police district into optimal patrol...
This paper presents a detection method for estimation of vanishing point position with designed regression convolutional neural network. Due to the deep structures of convolutional networks, global high-level features are extracted from the whole image, which helps to locate the vanishing point. In this paper, we provide a new structure of regression neural network based on AlexNet. The structure...
Relief is one of the key components of the landscape. Therefore, its mapping and exploring has been done for centuries. Ways of examination the impact of the relief have been considerably extended by using geographic information systems. But until recently, it was difficult to study in detail the micro-relief components of relief. This was due to the fact that there were not sufficiently detailed...
Texture is an important feature in RS image classification of land-use, and its precision mainly depends on the scale parameters, which are strongly correlated with the geometry characteristics of the classified objects. However, there is no a recognized reliable method for texture scale extraction. So this paper proposes an new approach to indirectly extract them with the assistance of domain GIS...
A good traffic monitoring system should be able to detect, count and classify moving vehicles. Vehicle classification is an important task that can provide information about road users and implicitly take decisions that can reduce congestion for example. This paper presents a new classification approach for moving vehicles. First moving vehicles are detected using a background subtraction approach,...
In this paper, we have implemented and tested a system of detection and recognition of road signs. The approach taken in this work consists of two main modules: a sensor module, which is based on color segmentation and shape detection where we converted the images to the HSV color space, then labeled the detected regions and tested for their shape. A recognition module, Template Matching, whose role...
As Sensors are sensitive to weather conditions; video cameras could be used to record the traffic information at different weather conditions. We have sophisticated algorithms to analyze the traffic videos in real time and discover information of interest. Although some sensors could be more accurate, they could also be Intrusive and need a higher maintenance cost. We may need to embed weighing sensors...
The traffic sign detection and recognition is an integral part of Advanced Driver Assistance System (ADAS). Traffic signs provide information about the traffic rules, road conditions and route directions and assist the drivers for better and safe driving. Traffic sign detection and recognition system has two main stages: The first stage involves the traffic sign localization and the second stage classifies...
Paper presents the Shape Movement Pattern (ShaMP) algorithm, an algorithm for extracting Movement Patterns (MPs) from network data, and a prediction mechanism whereby the identified MPs can be used to predict the nature of movement in a previously unseen network. The principal advantage offered by ShaMP is that it lends itself to parallelisation. The reported evaluation was conducted using both Massage...
Traffic safety is an important problem for autonomous vehicles. The development of Traffic Sign Recognition (TSR) dedicated to reducing the number of fatalities and the severity of road accidents is an important and an active research area. Recently, most TSR approaches of machine learning and image processing have achieved advanced performance in traditional natural scenes. However, there exists...
These last decades have seen the application of automatic inspection in many fields thanks to advanced vision sensors and image analysis methods. However, the difficult nature of pavement images, the small size of defects (cracks) lead to the fact that inspection in this area is done mostly manually. Each year in Tunisia, the operator must view images of thousands of kilometers of roads to detect...
Traffic Sign Recognition (TSR) system is a significant component of Intelligent Transport System (ITS) as traffic signs assist the drivers to drive more safely and efficiently. This paper represents a new approach for TSR system using hybrid features formed by two robust features descriptors, named Histogram Oriented Gradient(HOG) features and Speeded Up Robust Features(SURF) and artificial neural...
Traffic Sign Recognition (TSR) system is a vital component of intelligent transport system. It plays an important role by enhancing the safety of the drivers, pedestrians and vehicles as traffic signs provide important information of the traffic environment of the road and assist the drivers to drive more safely and easily by guiding and warning. This paper represents road sign detection and recognition...
The current study seeks to advance in the direction of building a robust feature-based passive visual navigation system utilising unique characteristics of the features present in an image to obtain position of the aircraft. This is done by extracting, prioritising and associating such features as road centrelines, road intersections and using other natural landmarks as a context. It is shown that...
Traffic Sign Detection and Recognition is an important component of intelligent transportation systems. It has captured the attention of the computer vision community for several decades. In this paper, we propose a new traffic sign detection and recognition approach consisting of color segmentation, shape classification and recognition stages. In the first stage, the image is segmented using look-up...
This paper presents an agile approach to facilitate the rapid development of traffic sign classification algorithms in heavy vehicles under a wide range of visibility conditions. A vision-based traffic sign recognition system makes a significant contribution to improving the transportation safety by enhancing the driver's awareness on important road signs in an automotive cockpit environment. It has...
Speed-limit sign (SLS) recognition is an important function to realize automatic driving assistance systems (ADAS). This paper presents a novel design of an image-based SLS recognition algorithm, which can efficiently detect and recognize SLS in real-time. To improve the robustness of the proposed SLS algorithm, this paper also proposes a new shape description method to describe the detected SLS using...
This paper investigates the problem of controlling a heterogeneous group of vehicles with the aim of forming multilane convoys. We use a distributed, graph-based control law, implemented in a longitudinal coordinate system parallel to the road. Each vehicle maintains a local graph with information from only nearby vehicles, in which the desired distances between vehicles are calculated dynamically...
For on-road autonomous driving, path planner needs to generate a target path which is not only safe and smooth, but also stable under uncertainty propagated from sensing such as localization error and perception error. In this paper, we propose a path planning method which generates a target path in two steps: reference path planning and local path planning. The reference path planner keeps stability...
This article discusses a new method in detecting the road by using corner adjacent features. Corner is a vertices obtained from every part of vehicle moving from one point to the other, which will be the basic for the road boundary calculation process. The adoption of Lukas Kanade and Melkman algorithm [13] proofs to improve system responsiveness towards the motion of moving object. It is proven that...
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