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This article presents a method for graffiti identification based on the analysis of its dominant colors using artificial intelligence. The method employs a K-Means clustering algorithm to group the pixels of a graffiti image according to their color values in the Red, Green, Blue or The Lab color space. From this clustering, the dominant colors of each group are extracted and ranked by their prevalence. This approach enables the characterization of the predominant colors in graffiti, facilitating their subsequent localization and analysis in a database.

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Graffiti Identification Using Color Analysis: An Approach Based on K-Means Clustering

  • 会议论文

  • 发表日期：

    2025年

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  • Miguel García García,
  • Guillermo Hernández,
  • Angélica González-Arrieta,
  • Sara Rodríguez González

摘要

This article presents a method for graffiti identification based on the analysis of its dominant colors using artificial intelligence. The method employs a K-Means clustering algorithm to group the pixels of a graffiti image according to their color values in the Red, Green, Blue or The Lab color space. From this clustering, the dominant colors of each group are extracted and ranked by their prevalence. This approach enables the characterization of the predominant colors in graffiti, facilitating their subsequent localization and analysis in a database.