Automated Road Extraction From High Resolution Satellite Images. (2016)

• Record Type: Journal Article
• Authors: Hormese, Jose; Saravanan, C.
• Is Part Of: Procedia technology. Volume 24(2016)
• Page Start: 1460
• Page End: 1467
• Publication Date: 2016
• Subjects: Remote Sensed Images -- Vectorization -- Geographic Information System; Technology -- Congresses; Technology -- Periodicals; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Technology; Conference proceedings; Periodicals; 605
• DOI: 10.1016/j.protcy.2016.05.180
• Languages: English
• ISSNs: 2212-0173

Abstract

Abstract: The importance of road extraction from satellite images arises from the fact that it greatly enhances the efficiency of map generation and thus can be a big help in car navigations systems or any emergency (rescue) system that needs instant maps. Therefore, increasing research is being dedicated and focused on the development of efficient methods to extract topographical meaningful features (like roads) from digital remote sensed images. The work deals with extraction of roads from satellite images. This is a challenging domain compared to extraction from aerial images as satellite images are noisy and of lower resolution. In this method, a Vectorization Approach for the automatic method of road extraction is being used where the image is segmented to identify the road network regions followed by a decision making and continuity procedure to correctly detect the roads and the Vectorization step to identify the line segments or curved segments which represents the road. This method may be employed for obtaining information for feeding large-scale Geographic Information System. In the automatic method of road extraction the extracted roads are converted into road vectors in order to use these vector road maps in GIS. A semi-automated scheme is used for scenarios where fully automated system fails. A combination of both methods can be devised for a full fledged real business scenario