DocumentCode :
2507257
Title :
Automatic Building Detection in Aerial Images Using a Hierarchical Feature Based Image Segmentation
Author :
Izadi, Mohammad ; Saeedi, Parvaneh
Author_Institution :
Sch. of Eng. Sci., Simon Fraser Univ., Burnaby, BC, Canada
fYear :
2010
fDate :
23-26 Aug. 2010
Firstpage :
472
Lastpage :
475
Abstract :
This paper introduces a novel automatic building detection method for aerial images. The proposed method incorporates a hierarchical multilayer feature based image segmentation technique using color. A number of geometrical/regional attributes are defined to identify potential regions in multiple layers of segmented images. A tree-based mechanism is utilized to inspect segmented regions using their spatial relationships with each other and their regional/geometrical characteristics. This process allows the creation of a set of candidate regions that are validated as rooftops based on the overlap between existing and predicted shadows of each region according to the image acquisition information. Experimental results show an overall shape accuracy and completeness of 96%.
Keywords :
feature extraction; image colour analysis; image segmentation; object detection; trees (mathematics); aerial images; automatic building detection; geometrical attributes; hierarchical multilayer feature; image acquisition information; image color; image segmentation; regional attributes; rooftops; spatial relationship; tree-based mechanism; Accuracy; Buildings; Feature extraction; Image segmentation; Pixel; Satellites; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
ISSN :
1051-4651
Print_ISBN :
978-1-4244-7542-1
Type :
conf
DOI :
10.1109/ICPR.2010.123
Filename :
5597414
Link To Document :
بازگشت