A Radon Transform Based Approach for Extraction of Blood Vessels in Conjunctival Images
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Fast curvilinear structure extraction and delineation using density estimation
Computer Vision and Image Understanding
Morphological thick line center detection
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part I
Extracting buildings by using the generalized multi directional discrete radon transform
ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
Iterative and localized radon transform for road centerline detection from classified imagery
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
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Centerline detection and line width estimation are important for many computer vision applications, e.g., road network extraction from high resolution remotely sensed imagery. Radon transform-based linear feature detection has many advantages over other approaches: for example, its robustness in noisy images. However, it usually fails to detect the centerline of a thick line due to the peak selection problem. In this paper, several key issues that affect the centerline detection using the radon transform are investigated. A mean filter is proposed to locate the true peak in the radon image and a profile analysis technique is used to further refine the line parameters. The thetas-boundary problem of the radon transform is also discussed and the erroneous line parameters are corrected. Intensive experiments have shown that the proposed methodology is effective in finding the centerline and estimating the line width of thick lines