Robust Audio Fingerprinting Based on Local Spectral Luminance Maxima Scheme

This paper proposes a robust audio fingerprinting system based on local spectral luminance maxima (LSLM) scheme using image processing approaches. Our approach treats spectrogram of an audio clip as a 2-D image and extracts the local luminance maxima of spectrum image as the discriminative characteristics. LSLM are selected due to resilience against quantization, compression, and noise addition, etc. Experimental results show that the proposed binary audio fingerprints outperform some of the state-of-the-art in the context of both robustness and reliability, especially in the noisy environment.