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Proceedings Paper

A new method of extracting shape features from IKONOS imagery based on Fourier Descriptor: an application to object-oriented classification
Author(s): Wei Wan; Xuezhi Feng; Pengfeng Xiao; Limin Zhao
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Paper Abstract

Shape is an important visual feature of very high-resolution satellite data. Fourier Descriptor (FDs) was introduced in this paper as a new method to extract and represent objects' shape features of IKONOS imagery and a 5-dimensional (5- D) feature-vector was proposed as a shape parameter. A classification model was established based on K-means clustering algorithm, the 5-D feature-vector was taken as discrimination variable together with the mean gray values. The results showed that when involving the shape feature-vector into the classification model, the overall classification accuracy was 82.4% with 84.6% producer accuracy of roads. So it was confirmed a feasible way to represent shape features of remotely sensed imagery based on FDs.

Paper Details

Date Published: 3 November 2010
PDF: 7 pages
Proc. SPIE 7840, Sixth International Symposium on Digital Earth: Models, Algorithms, and Virtual Reality, 78401I (3 November 2010); doi: 10.1117/12.872947
Show Author Affiliations
Wei Wan, Nanjing Univ. (China)
Xuezhi Feng, Nanjing Univ. (China)
Pengfeng Xiao, Nanjing Univ. (China)
Limin Zhao, Nanjing Univ. (China)

Published in SPIE Proceedings Vol. 7840:
Sixth International Symposium on Digital Earth: Models, Algorithms, and Virtual Reality
Huadong Guo; Changlin Wang, Editor(s)

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