Please use this identifier to cite or link to this item: https://doi.org/10.1117/12.974443
Title: A rooftop extraction method using color feature, height map information and road information
Authors: Xiang, Y.
Sun, Y. 
Li, C.
Keywords: Height map
Level-set
Rectangle fitting
Road orientation
Roof segmentation
Rooftop detection
Superpixels
Issue Date: 2012
Source: Xiang, Y., Sun, Y., Li, C. (2012). A rooftop extraction method using color feature, height map information and road information. Proceedings of SPIE - The International Society for Optical Engineering 8537 : -. ScholarBank@NUS Repository. https://doi.org/10.1117/12.974443
Abstract: This paper presents a new method for rooftop extraction that integrates color features, height map, and road information in a level set based segmentation framework. The proposed method consists of two steps: rooftop detection and rooftop segmentation. The first step requires the user to provide a few example rooftops from which the color distribution of rooftop pixels is estimated. For better robustness, we obtain superpixels of the input satellite image, and then classify each superpixel as rooftop or non-rooftop based on its color features. Using the height map, we can remove those detected rooftop candidates with small height values. Level set based segmentation of each detected rooftop is then performed based on color and height information, by incorporating a shape-prior term that allows the evolving contour to take on the desired rectangle shape. This requires performing rectangle fitting to the evolving contour, which can be guided by the road information to improve the fitting accuracy. The performance of the proposed method has been evaluated on a satellite image of 1 km×1 km in area, with a resolution of one meter per pixel. The method achieves detection rate of 88.0% and false alarm rate of 9.5%. The average Dice's coefficient over 433 detected rooftops is 73.4%. These results demonstrate that by integrating the height map in rooftop detection and by incorporating road information and rectangle fitting in a level set based segmentation framework, the proposed method provides an effective and useful tool for rooftop extraction from satellite images. © 2012 SPIE.
Source Title: Proceedings of SPIE - The International Society for Optical Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/83421
ISBN: 9780819492777
ISSN: 0277786X
DOI: 10.1117/12.974443
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

1
checked on Feb 13, 2018

WEB OF SCIENCETM
Citations

1
checked on Nov 20, 2017

Page view(s)

46
checked on Feb 17, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.