The automatic extraction of road features from remote sensed images has been a topic of great interest within the photogrammetric and remote sensing communities for over 3 decades. Although various techniques have been reported in the literature, it is still challenging to efficiently extract the road details with the increasing of image resolution as well as the requirement for accurate and up...

This paper presents a comprehensive approach to effectively extract cartographic urban data from high resolution satellite imagery. It consists of a sequence of image processing techniques, for image segmentation, based on RGB band separation, analysis and preprocessing, followed by a morphological-based approach for data segmentation. The chosen image objects for this study are roof-tile build...

--In this paper we propose an image segmentation method based on multi-scale analysis using wavelets, this method has been developed and adapted to detect road signs (road signs and traffic lights). It is an approach to highlight objects in a road scene especially objects corresponding to a road signs. It relies on the use of 2D histograms highlighting the different modes and based on operation...

This paper presents a novel method MGARS to automatic road area segmentation based on motion and gray feature for the purpose of urban traffic surveillance. The proposed method can locate road region by region growing algorithm with the fusion feature of motion information and grayscale of background image, which is independent to road marker information. An adaptive background subtraction appr...

In this paper, we discuss a vision based system for autonomous guidance of vehicles. An autonomous intelligent vehicle has to perform a number of functionalities. Segmentation of the road, determining the boundaries to drive in and recognizing the vehicles and obstacles around are the main tasks for vision guided vehicle navigation. In this article we propose a set of algorithms which lead to t...

Region-based analysis is fundamental and crucial in many geospatialrelated applications and research themes, such as trajectory analysis, human mobility study and urban planning. In this paper, we report on an image-processing-based approach to segment urban areas into regions by road networks. Here, each segmented region is bounded by the high-level road segments, covering some neighborhoods a...

Aiming at the problem of automatic identification and evaluation of road damage degree, the road damage identification and degree assessment algorithms based on unmanned vehicles experimental platform are studied. The road crack segmentation extraction method based on adaptive sliding window is studied. On this basis, the road damage crack classifies and identifies according to the crack geomet...

The road network is a key resource of enormous value for the nation. A satellite image is covering a large area instantaneously and can thereby be a source of road traffic information in a snapshot of time. Manual vehicle counting is not realistic, but automatic image analysis methodology based on pattern recognition is a promising alternative. The “Road Traffic Snapshot” project (2006‐2007) sh...

Road segmentation for synthetic aperture radar (SAR) images is of great practical significance. With the rapid development and wide application SAR imaging technology, this problem has attracted much attention. At present, there are numerous road methods. This paper analyzes summarizes methods over years. Firstly, traditional algorithms classified according to degree automation principle. Advan...

This paper deals with a problem of road tracking and vehicle positioning based on sequential images captured by a vehicle mounted monocular colour camera. The paper presents a new region‐based road tracking method, which is suitable for both structured and unstructured roads. The proposed method is based on our original road segmentation algorithm and estimates road model paramet...