Title :
Birdcall Retrieval from Environmental Acoustic Recordings Using Image Processing
Author :
Xueyan Dong;Phil Eichinski;Michael Towsey;Jinglan Zhang;Paul Roe
Author_Institution :
Sch. of Electr. Eng. &
Abstract :
Acoustic recordings of the environment provide an effective means to monitor bird species diversity. To facilitate exploration of acoustic recordings, we describe a content-based birdcall retrieval algorithm. A query birdcall is a region of spectrogram bounded by frequency and time. Retrieval depends on a similarity measure derived from the orientation and distribution of spectral ridges. The spectral ridge detection method caters for a broad range of birdcall structures. In this paper, we extend previous work by incorporating a spectrogram scaling step in order to improve the detection of spectral ridges. Compared to an existing approach based on MFCC features, our feature representation achieves better retrieval performance for multiple bird species in noisy recordings.
Keywords :
"Spectrogram","Feature extraction","Birds","Acoustics","Hidden Markov models","Histograms","Entropy"
Conference_Titel :
Digital Image Computing: Techniques and Applications (DICTA), 2015 International Conference on
DOI :
10.1109/DICTA.2015.7371242