Scale Invariant Sillhouette Features

Date

2013-01-01

Author

Akagündüz, Erdem

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In this study, a feature extractor and a global descriptor for closed planar curves, i.e. silhouettes, are proposed. Initially, the closed curve is arc-length sampled and the Gaussian scale-space is constructed. Using the absolute curvature values and orientations of the curves within the higher scale levels, scale invariant features are obtained. These features are transformed into a global descriptor, namely the feature images, and shape recognition is performed. The proposed method is evaluated using a ship silhouette image set and the results show good success rates with low computation burden.

URI

https://hdl.handle.net/11511/94418

Conference Name

21st Signal Processing and Communications Applications Conference (SIU)

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Graduate School of Informatics, Conference / Seminar

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Citation Formats

E. Akagündüz, “Scale Invariant Sillhouette Features,” presented at the 21st Signal Processing and Communications Applications Conference (SIU), CYPRUS, 2013, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/94418.