<i>TGGLinesPlus</i> : A Robust Topological Graph‐Guided Computer Vision Algorithm for Line Detection From Images

ABSTRACT 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 benchmarked our algorithm with five classic and state‐of‐the‐art line detection methods and evaluated the benchmark results qualitatively and quantitatively, the results demonstrate the robustness of TGGLinesPlus .

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Publication Details

Journal
Transactions in GIS
Published
2025-02-01
DOI
https://doi.org/10.1111/tgis.70015
Primary Topic
Digital Image Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

TGGLinesPlus : A Robust Topological Graph‐Guided Computer Vision Algorithm for Line Detection From Images

Joshua Driscol, Katie Slack, Catherine Potts, Shujie Wang et al.
Transactions in GIS
Digital Image Processing Techniques
article

TGGLinesPlus : A Robust Topological Graph‐Guided Computer Vision Algorithm for Line Detection From Images

Joshua Driscol, Katie Slack, Catherine Potts, Shujie Wang, Wenbin Zhang, Liping Yang, Ming Gong
article en

Abstract

ABSTRACT 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 benchmarked our algorithm with five classic and state‐of‐the‐art line detection methods and evaluated the benchmark results qualitatively and quantitatively, the results demonstrate the robustness of TGGLinesPlus .

Transactions in GISVol. 29(1)
University of Dayton (US), Pennsylvania State University (US), D-Wave Systems (Canada) (CA), Woodwell Climate Research Center (US), University of New Mexico (US), Florida International University (US)
National Aeronautics and Space Administration, University of Pennsylvania, Pennsylvania State University, Curtin University of Technology, Nuclear Safety and Security Commission
Openalex Percentile: Top 98%
Digital Image Processing Techniques
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