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Seeing Structure: Measuring UML Diagram Density with Vision and Clustering Algorithms

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Tenbergen, Bastian
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2025
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Quest
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Quest2025_046.pdf
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http://hdl.handle.net/20.500.12648/16604
Abstract
This project explores what makes a UML diagram effective by analyzing diagram density using computer vision. Initial methods had a 22% failure rate, but integrating OCR, Voronoi tessellation, and Mean Shift Clustering reduced it to 0%. Future goals include improving code maintainability, bias correction, and creating a user-friendly CLI tool.
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