Using Three Reassigned Spectrogram Patches and Log-Gabor Filter for Audio Surveillance Application

Abstract

In this paper, we propose a robust environmental sound spectrogram classification approach; its purpose is surveillance and security applications based on the reassignment method and log-Gabor filters. Besides, the reassignment method is applied to the spectrogram to improve the readability of the time-frequency representation, and to assure a better localization of the signal components. In this approach the reassigned spectrogram is passed through a bank of 12 log-Gabor filter concatenation applied to three spectrogram patches, and the outputs are averaged and underwent an optimal feature selection procedure based on a mutual information criterion. The proposed method is tested on a large database consists of 1000 environmental sounds belonging to ten classes. The averaged recognition accuracy is of order 90.87% which obtained using the multiclass support vector machines (SVM's).