文件名称:Line-detection-in-a-noisy-environment-with-weight
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One of the most popular approaches to detect lines is based on the Radon transform (RT). But in real-world applications
RT-based approach suffers the noise and clutter, because they decrease the sharpness of the local maximums.
In this paper we suggest a new approach to computational effective line detection using the Weighted Radon Transform
(WRT). The suggested WRT-based approach uses gradient direction information, so only the differences that are
perpendicular to the line direction are integrated to make a local maximum corresponding to the line.
The theoretical and experimental studies show the effectiveness of the WRT-based line detection. The suggested WRTbased algorithm can be effectively implemented in real-time systems using parallelization and FFT-based techniques.
Keywords: Radon transform, line detection, object detection.-One of the most popular approaches to detect lines is based on the Radon transform (RT). But in real-world applications
RT-based approach suffers the noise and clutter, because they decrease the sharpness of the local maximums.
In this paper we suggest a new approach to computational effective line detection using the Weighted Radon Transform
(WRT). The suggested WRT-based approach uses gradient direction information, so only the differences that are
perpendicular to the line direction are integrated to make a local maximum corresponding to the line.
The theoretical and experimental studies show the effectiveness of the WRT-based line detection. The suggested WRTbased algorithm can be effectively implemented in real-time systems using parallelization and FFT-based techniques.
Keywords: Radon transform, line detection, object detection.
RT-based approach suffers the noise and clutter, because they decrease the sharpness of the local maximums.
In this paper we suggest a new approach to computational effective line detection using the Weighted Radon Transform
(WRT). The suggested WRT-based approach uses gradient direction information, so only the differences that are
perpendicular to the line direction are integrated to make a local maximum corresponding to the line.
The theoretical and experimental studies show the effectiveness of the WRT-based line detection. The suggested WRTbased algorithm can be effectively implemented in real-time systems using parallelization and FFT-based techniques.
Keywords: Radon transform, line detection, object detection.-One of the most popular approaches to detect lines is based on the Radon transform (RT). But in real-world applications
RT-based approach suffers the noise and clutter, because they decrease the sharpness of the local maximums.
In this paper we suggest a new approach to computational effective line detection using the Weighted Radon Transform
(WRT). The suggested WRT-based approach uses gradient direction information, so only the differences that are
perpendicular to the line direction are integrated to make a local maximum corresponding to the line.
The theoretical and experimental studies show the effectiveness of the WRT-based line detection. The suggested WRTbased algorithm can be effectively implemented in real-time systems using parallelization and FFT-based techniques.
Keywords: Radon transform, line detection, object detection.
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Line detection in a noisy environment with weighted Radon transform.pdf
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