Document Type

Conference Paper

Publication Date

6-2015

Publication Source

2015 National Aerospace and Electronics Conference

Abstract

We present an automated mechanism that can detect and characterize the building changes by analyzing airborne or satellite imagery.

The proposed framework can be categorized into three stages: building detection, boundary extraction and change identification. To detect the buildings, we utilize local phase and local amplitude from monogenic signal to extract building features for addressing issues of varying illumination. Then a support vector machine with Radial basis kernel is used for classification. In the boundary extraction stage, a level-set function with self-organizing map based segmentation method is used to find the building boundary and compute physical area of the building segments. In the last stage, the change of the detected building is identified by computing the area differences of the same building that captured at different times.

The experiments are conducted on a set of real-life aerial imagery to show the effectiveness of the proposed method.

Inclusive pages

1-4

ISBN/ISSN

2379-2027

Document Version

Postprint

Comments

The document available for download is the authors' accepted manuscript, provided in compliance with the publisher's policy on self-archiving. Permission documentation is on file.

Some differences may exist between this version and the published version; as such, researchers wishing to quote directly from this source are advised to consult the version of record.

Publisher

IEEE

Place of Publication

Dayton, OH

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