A series of sensors on the pavements being used for traffic flow data detection have some disadvantages. With recent advances in high-resolution commercial remote sensing systems, detecting traffic flow data from remote sensing images over large regions is an attractive option in traffic information collection technology. The main goal of this research is exploring vehicle information from high-resolution satellite remote sensing images. A new method for vehicle detection based on object-oriented image analysis is developed and applied in this paper. Analyzing high-resolution satellite image characteristics, object-oriented segmentation is implemented here in order to generate image objects. Then feature space is created by extracting features of these objects, to be used for vehicle detection, classification, and traffic flow information analysis. Our experimental results as described and assessed here show how this method is effective. Our research provides a means of traffic flow information collection in ITS as compared to traditional approaches.
Research on Vehicle Information Extraction from High-Resolution Satellite Images
Ninth International Conference of Chinese Transportation Professionals (ICCTP) ; 2009 ; Harbin, China
ICCTP 2009 ; 1-7
2009-07-23
Conference paper
Electronic Resource
English
Research on Vehicle Information Extraction from High-Resolution Satellite Images
British Library Conference Proceedings | 2009
|Vehicle Detection and Classification from High Resolution Satellite Images
DOAJ | 2014
|Extraction of Main Urban Roads from High Resolution Satellite Images by Machine Learning
British Library Conference Proceedings | 2006
|British Library Online Contents | 2004
|