Line Detection Based on Hough Transform and its Application

Line detection is an important task in computer vision, which is widely used in fields such as automated driving and remote sensing image processing. As a classical image processing method, Hough transform has strong robustness and anti-interference ability in line detection. In this paper, line detection based on Hough transform is implemented and accelerated to hardware implementation on High-Level Synthesis (HLS) platform. By performing edge detection on the input image, the Hough transform maps the image from Cartesian space to parameter space to detect line features in the image. Experimental results show that the method can accurately detect lines in the image while exhibiting strong noise rejection. The implementation not only improves the efficiency of line detection, but also provides an effective solution for hardware acceleration applications based on the Hough transform.

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Publication Details

Published
2025-02-21
DOI
https://doi.org/10.1145/3728725.3728774
Citations
1
Primary Topic
Image and Object Detection Techniques
Type
article
Field-Weighted Citation Impact
1.28
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article

Line Detection Based on Hough Transform and its Application

Jianbing Ye, Qi Li, C.‐H. Lin
1 citations
Image and Object Detection Techniques
1.28
article

Line Detection Based on Hough Transform and its Application

Jianbing Ye, Qi Li, C.‐H. Lin
article en
1 citations

Abstract

Line detection is an important task in computer vision, which is widely used in fields such as automated driving and remote sensing image processing. As a classical image processing method, Hough transform has strong robustness and anti-interference ability in line detection. In this paper, line detection based on Hough transform is implemented and accelerated to hardware implementation on High-Level Synthesis (HLS) platform. By performing edge detection on the input image, the Hough transform maps the image from Cartesian space to parameter space to detect line features in the image. Experimental results show that the method can accurately detect lines in the image while exhibiting strong noise rejection. The implementation not only improves the efficiency of line detection, but also provides an effective solution for hardware acceleration applications based on the Hough transform.

Nanjing Tech University (CN)
Openalex Percentile: Top 20%
Image and Object Detection Techniques
1.28
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