Circular Target Detection Algorithm on Satellite Images based on Radial Transformation

Date

2014-04-25

Author

Zerman, Emin
Bati, Emrecan
Akar, Gözde
Baseski, Emre
Duzgun, Sebnem

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Remote sensing is used in a spreading manner by many governmental and industrial institutions worldwide in recent years. Target detection has an important place among the applications developed using satellite imagery. In this paper, an original circular target detection algorithm has been proposed based on a radial transformation. The algorithm consists of three stages such as pre-processing, target detection, and post-processing. In the pre-processing stage, bilateral noise reduction filtering and vegetation detection operations are completed which they are required by target detection step. The target detection stage finds the circular target by a radial transformation algorithm and variables obtained from the training, and post-processing stage carries out the elimination of falsely detected targets by utilizing the vegetation information. The Petroleum Oil Lubricants (POL) depots in the industrial areas and harbors have been chosen as an application area of the proposed algorithm. The algorithm has been trained and tested on a data set which includes 4-band images with Near-Infrared band. Proposed algorithm is able to detect many circular targets with different types and sizes as a consequence of using a full radial transformation search as well as it gives rewarding results on industrial areas and harbors in the experiments conducted.

Subject Keywords

Target detection, Remote sensing, High resolution satellite images, POL detection

URI

https://hdl.handle.net/11511/52682

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

E. Zerman, E. Bati, G. Akar, E. Baseski, and S. Duzgun, “Circular Target Detection Algorithm on Satellite Images based on Radial Transformation,” 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/52682.