Line Segment Detection Based on False Peak Suppression and Local Hough Transform and Application for Contact Point Detection

This paper mainly proposes a line segment detection method based on false peak suppression and local Hough transform. It can effectively suppress the impact of noise in binary images on line segment detection performance and solve the problems of short line false detection, missing detection and over-segmentation, and acquire line segment features in pantograph-catenary panoramic images robustly. In the actual pantograph-catenary panoramic images dataset test, the comparison results of the detection accuracy of the pantograph-catenary panoramic images line segments and contact points show that the proposed method is able to reduce the missing detection while improving the detection accuracy of the pantograph-catenary contact point. Moreover, the tests on the public YorkUrban dataset also show that the proposed method in this paper achieves the optimal results in the evaluation of accuracy and processing speed, which also has a strong generalization ability in high-quality natural images.

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Publication Details

Journal
IEICE Transactions on Information and Systems
Published
2025-04-13
DOI
https://doi.org/10.1587/transinf.2024edp7246
Primary Topic
Image and Object Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Line Segment Detection Based on False Peak Suppression and Local Hough Transform and Application for Contact Point Detection

Jinyi Zhang, Mei Han, Ye Tian
IEICE Transactions on Information and Systems
Image and Object Detection Techniques
article

Line Segment Detection Based on False Peak Suppression and Local Hough Transform and Application for Contact Point Detection

Jinyi Zhang, Mei Han, Ye Tian
article en

Abstract

This paper mainly proposes a line segment detection method based on false peak suppression and local Hough transform. It can effectively suppress the impact of noise in binary images on line segment detection performance and solve the problems of short line false detection, missing detection and over-segmentation, and acquire line segment features in pantograph-catenary panoramic images robustly. In the actual pantograph-catenary panoramic images dataset test, the comparison results of the detection accuracy of the pantograph-catenary panoramic images line segments and contact points show that the proposed method is able to reduce the missing detection while improving the detection accuracy of the pantograph-catenary contact point. Moreover, the tests on the public YorkUrban dataset also show that the proposed method in this paper achieves the optimal results in the evaluation of accuracy and processing speed, which also has a strong generalization ability in high-quality natural images.

IEICE Transactions on Information and SystemsVol. E108.D(10)
Shenyang Ligong University (CN), Gifu University (JP), Hunan University of Technology (CN)
China Scholarship Council
Climate action
Openalex Percentile: Top 94%
Image and Object Detection Techniques
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