Paper Info
Title
Improved Harris Feature Point Set for Orientation-Sensitive Urban-Area Detection in Aerial Images
Abstract
This letter addresses the automatic detection of urban area in remotely sensed images. As manual administration is time consuming and unfeasible, researchers have to focus on automated processing techniques, which can handle various image characteristics and huge amount of data. The applied method extracts feature points in the first step, which is followed by the construction of a voting map to represent urban areas. Finally, an adaptive decision making is performed to find urban areas. This letter presents methodological contributions in two key issues to the algorithm: 1) An automatically extracted Harris-based feature point set is introduced for the first step, which is able to represent urban areas more precisely. 2) An improved orientation-sensitive voting technique is proposed, exploiting the orientation information calculated in the local neighborhood of points. Evaluation results show that the proposed contributions increase the detection accuracy of urban areas.
Year
DOI
Venue
2013
10.1109/LGRS.2012.2224315
Geoscience and Remote Sensing Letters, IEEE
Keywords
Field
DocType
decision making,feature extraction,geophysical image processing,image representation,object detection,optical images,remote sensing,adaptive decision making,automated processing technique,automatic Harris feature point set extraction,optical aerial image,orientation sensitive urban area detection,remotely sensed image,urban area representation,voting map construction,Aerial images,modified Harris detector,orientation sensitivity,spatial voting,urban-area detection
Computer vision,Object detection,Voting,Remote sensing,Image representation,Feature extraction,Artificial intelligence,Point set,Urban area,Mathematics
Journal
Volume
Issue
ISSN
10
4
1545-598X
Citations 
PageRank 
References 
4
0.43
0
Authors
2
Name
Order
Citations
PageRank
Andrea Kovács1373.56
Tamás Szirányi215226.92