Building recognition from aerial images combining segmentation and shadow

We propose a novel building detection algorithm for processing high-resolution aerial images. Our algorithm exploits the building-shadow geometric relationship according to lighting models, making it suitable to detect buildings in a more general setting, possibly with irregular shapes. We use image...

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Bibliographic Details
Main Authors: Keyan Ren, Hanxu Sun, Qingxuan Jia, Jianbo Shi
Format: Conference Proceeding
Language:English
Subjects:
aerial image
Automation
Buildings
builing detection
Data mining
Detection algorithms
Image edge detection
Image recognition
Image segmentation
segmentation
shadow
Shape
Solid modeling
Testing
Online Access:Request full text
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Summary:We propose a novel building detection algorithm for processing high-resolution aerial images. Our algorithm exploits the building-shadow geometric relationship according to lighting models, making it suitable to detect buildings in a more general setting, possibly with irregular shapes. We use image segmentation to provide spatial support for both building and shadow detections. A novel confidence method is developed to label building and shadow segments by jointly reasoning: 1) the likelihood of shadows; 2) building-shadow configuration, and 3) building-building similarity. Our method is tested on a wide range of aerial images. Qualitative and quantitative results demonstrate its effectiveness on detecting and extracting buildings from background clutter.
DOI:10.1109/ICICISYS.2009.5357616