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New Ordering-Based Pruning Metrics for Ensembles of Classifiers in Imbalanced Datasets Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Environmental Sounds Recognition Based on Image Processing Methods

Authors : Tomasz Maka, Paweł Forczmański

Published in: Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015

Publisher: Springer International Publishing

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Abstract

The article presents an approach to environmental sound recognition that uses selected methods from the field of digital image processing and recognition. The proposed technique adopts the assumption that an audio signal can be converted into a visual representation, and processed further, as an image. At the first stage the audio data are converted into rectangular matrices called feature maps. Then a two-step approach is applied: the construction of a representative database of reference samples and the identification of test samples. The process of building the database employs two-dimensional linear discriminant analysis. Then the recognition operation is carried out in a reduced feature space that has been obtained by two-dimensional Karhunen–Loeve projection. At the classification stage, a minimum distance classifier is applied to different features. As it is shown, the results are very encouraging and can be a base for many practical audio applications.

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previous chapter Rough Sets and Fuzzy Logic Approach for Handwritten Digits and Letters Recognition
next chapter Investigating Combinations of Visual Audio Features and Distance Metrics in the Problem of Audio Classification
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Metadata
Title
Environmental Sounds Recognition Based on Image Processing Methods
Authors
Tomasz Maka
Paweł Forczmański
Copyright Year
2016
Book
Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015

Print ISBN: 978-3-319-26225-3

Electronic ISBN: 978-3-319-26227-7

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-26227-7_68

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