Communication Dans Un Congrès Année : 2024

Mathematical Morphology Applied to Feature Extraction in Music Spectrograms

Résumé

Mathematical Morphology has proven to be a powerful tool for extracting geometric information from greyscale images. In this paper, we demonstrate its application to spectrograms (two-dimensional greyscale images of sound) of music excerpts. The sounds of musical instruments exhibit particular shapes when represented as a spectrogram. These shapes are determined by the sound characteristics. In general, musical sounds contain three different components: the attack component, appearing as vertical lines; the sustain component, appearing as horizontal lines; and the stochastic component, appearing as a landscape of hills and holes. In this paper we propose a pipeline of morphological operators to separate these three components. This separation allows us to build a new sound similar to the input one.
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Dates et versions

hal-04908142 , version 1 (27-01-2025)

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Gonzalo Romero-García, Isabelle Bloch, Carlos Agón. Mathematical Morphology Applied to Feature Extraction in Music Spectrograms. Discrete Geometry and Mathematical Morphology 2024, Apr 2024, Florence, Italy. pp.431-442, ⟨10.1007/978-3-031-57793-2_33⟩. ⟨hal-04908142⟩
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