TGGLinesPlus: A robust topological graph-guided computer vision algorithm for line detection from images

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Bibliografiske detaljer
Udgivet i:arXiv.org (Mar 26, 2024), p. n/a
Hovedforfatter: Yang, Liping
Andre forfattere: Driscol, Joshua, Gong, Ming, Wang, Shujie, Potts, Catherine G
Udgivet:
Cornell University Library, arXiv.org
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Online adgang:Citation/Abstract
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Beskrivelse
Resumen:Line detection is a classic and essential problem in image processing, computer vision and machine intelligence. Line detection has many important applications, including image vectorization (e.g., document recognition and art design), indoor mapping, and important societal challenges (e.g., sea ice fracture line extraction from satellite imagery). Many line detection algorithms and methods have been developed, but robust and intuitive methods are still lacking. In this paper, we proposed and implemented a topological graph-guided algorithm, named TGGLinesPlus, for line detection. Our experiments on images from a wide range of domains have demonstrated the flexibility of our TGGLinesPlus algorithm. We also benchmarked our algorithm with five classic and state-of-the-art line detection methods and the results demonstrate the robustness of TGGLinesPlus. We hope our open-source implementation of TGGLinesPlus will inspire and pave the way for many applications where spatial science matters.
ISSN:2331-8422
Fuente:Engineering Database