Comparison of classification algorithms for various methods of preprocessing radar images of the MSTAR base

A. A. Borodinov; V. V. Myasnikov

doi:10.1117/12.2309469

13 April 2018 Comparison of classification algorithms for various methods of preprocessing radar images of the MSTAR base

A. A. Borodinov, V. V. Myasnikov

Author Affiliations +

Proceedings Volume 10696, Tenth International Conference on Machine Vision (ICMV 2017); 1069614 (2018) https://doi.org/10.1117/12.2309469
Event: Tenth International Conference on Machine Vision, 2017, Vienna, Austria

Abstract

The present work is devoted to comparing the accuracy of the known qualification algorithms in the task of recognizing local objects on radar images for various image preprocessing methods. Preprocessing involves speckle noise filtering and normalization of the object orientation in the image by the method of image moments and by a method based on the Hough transform. In comparison, the following classification algorithms are used: Decision tree; Support vector machine, AdaBoost, Random forest. The principal component analysis is used to reduce the dimension. The research is carried out on the objects from the base of radar images MSTAR. The paper presents the results of the conducted studies.

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A. A. Borodinov and V. V. Myasnikov "Comparison of classification algorithms for various methods of preprocessing radar images of the MSTAR base", Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 1069614 (13 April 2018); https://doi.org/10.1117/12.2309469

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