Investigating the correlation of the dominant color on a music album cover with the genre of music contained in the album using machine learning methods
In the presented master's thesis, a detailed examination of the relationship between the dominant color on the cover of a musical album and the music genre was conducted, using machine learning methods. The aim of the study was to identify potential correlations and understand how visual aspect...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/420312 |
| Acceso en línea: | https://hdl.handle.net/2117/420312 |
| Access Level: | acceso abierto |
| Palabra clave: | Machine learning Style, Musical aprenentatge automàtic classificació color portada d'àlbum de música gènere musical machine learning classification music album cover music genre Aprenentatge automàtic Estil musical Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic |
| Sumario: | In the presented master's thesis, a detailed examination of the relationship between the dominant color on the cover of a musical album and the music genre was conducted, using machine learning methods. The aim of the study was to identify potential correlations and understand how visual aspects of covers can affect the perception and classification of music. In this paper it's being evaluated if this information ¿ and more specifically the color information ¿ is sufficient to differentiate music genres. The theoretical part of the thesis presents an extensive review of literature and databases on color analysis in the context of graphics on music album covers. Various methods of color feature extraction were discussed, taking into account their advantages and limitations. Particular attention was paid to color theory, analyzing its basic concepts and the relationships between colors, emotions, and perception. The phenomenon of synesthesia, which involves perceiving music through colors, was also examined, as it may be relevant in analyzing album covers. Preparations for the practical part began with the design and implementation of a dataset, essential for conducting the analysis. Challenges related to data collection and processing were discussed, including issues of quality, representativeness, and methods of preparing them to achieve the set goals. The practical part of the thesis focused on the process of extracting the dominant color from album covers and analyzing these data. Various image processing and machine learning techniques were used to create models capable of classifying music genres based on color analysis. A series of experiments were conducted to determine whether and to what extent the dominant color on a cover can be an indicator of the music genre, and the results were carefully analyzed. The results obtained from the model were confronted with the responses obtained in a survey conducted among respondents. |
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