Citation

Djeddou M, Touhami T. Arab. J. Sci. Eng. Part A 2013; 38(12): 3399-3406.

Copyright

(Copyright © 2013, King Fahd University of Petroleum and Minerals, Publisher Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s13369-013-0655-5

PMID

unavailable

Abstract

In this paper, we deal with the problem of gunshot classification according to its acoustic signature in a noisy environment. The precise selection of useful signal is essential for a significant features' extraction. For this purpose, we propose to use a preprocessing step to select accurately the gunshot signature related frames. In addition, the use of entire features set with the Gaussian mixture model (GMM) does not provide a high classification rate. Then, a hierarchical classification is proposed. This latter is based on cepstral features modeled by GMM algorithm and followed by a classification of two subclasses using temporal parameter. This contributes significantly in discriminating between close signature classes. Our experiments yielded a high correct classification rate up to 96.29 %. The used temporal parameter is related to muzzle blast signal. To generalize the use of this feature, an empirical equation is derived and validated with a real data set.

Language: en