Audio classification using acoustic images for retrieval from multimedia databases
Ioannis Paraskevas, E. Chilton · 2004
With the increasing use of audio-visual databases, the need for automatic content-based classification has grown in importance. In this paper, a novel method for the automatic recognition of acoustic utterances is presented using acoustic images as the basis for the feature extraction. This method effectively employs the spectrogram, the Wigner-Ville distribution and co-occurrence matrices. The images are then compressed, using statistical methods, before being combined into a single feature matrix to be presented to a classifier. Initial results obtained from the classification of a database of sport sounds and gunshots indicate that the method is capable of accurate discrimination for coarse and fine classification respectively.