Line Segment Detectionalgorithms Towards High-resolution Color Image

LUO Wu-yang; CHENG Yue; LI Ya-hui; WEN Peng-cheng

Chinese

您当前的位置：

首页 >

文章列表页 >

Line Segment Detectionalgorithms Towards High-resolution Color Image

更新时间：2026-09-04

- Line Segment Detectionalgorithms Towards High-resolution Color Image
- Vol. 34, Issue 12, Pages: 19-24(2017)
- 作者机构：
  
  1. 中航工业西安航空计算技术研究所,陕西,西安,710068
  2. 机载弹载计算机航空科技重点实验室,陕西,西安,710068
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2017
- 稿件说明：
移动端阅览
罗午阳, 程岳, 李亚晖, 文鹏程. 面向高分辨率彩色图像的线段检测算法[J]. 微电子学与计算机, 2017, 34(12): 19-24.

LUO Wu-yang, CHENG Yue, LI Ya-hui, et al. Line Segment Detectionalgorithms Towards High-resolution Color Image[J]. 2017, 34(12): 19-24.
罗午阳, 程岳, 李亚晖, 文鹏程. 面向高分辨率彩色图像的线段检测算法[J]. 微电子学与计算机, 2017, 34(12): 19-24. DOI：

LUO Wu-yang, CHENG Yue, LI Ya-hui, et al. Line Segment Detectionalgorithms Towards High-resolution Color Image[J]. 2017, 34(12): 19-24. DOI：

摘要

当前主流的线段检测算法大多利用了像素点的梯度方向特征

但它们普遍存在过分段(over-segmentation)、长线段与低对比度线段容易被漏检的问题

面对高分辨率彩色图像时此类问题尤其严重.本文提出了一种基于目前性能最为突出的线段检测器LSD(Line segment detector)的扩展改进算法.该算法充分利用了原始图像的多通道、多尺度特性

并结合具有鲁棒性的基于尺度特征的线段筛选方法以及多通道多尺度线段融合方法

得到了更符合视觉认知的检测结果.实验结果表明

本文算法显著降低了长线段和低对比度线段被漏检的可能

明显消除了过分段现象.

Abstract

Currently

the mainstream of line segment detection algorithm mostly utilizes the pixels gradient orientations feature

but these algorithms exist problems of over-segmentation and being prone to miss long segment and low contrast segment commonly

especially confronting high-resolution color image. In order to solve these problems

this paper proposed a modified extending algorithm based on LSD

the current excellent method. This algorithm makes the best of original high-resolution color images multichannels and multiscale characteristics. Then it combines robust line segments filtering method based on scale features and multichannels-multiscale merging method. Our algorithm obtains the detection results closer to vision perceptually. Experimental results show that our algorithm substantially descending the miss rate of long segment and low contrast segment

and obviously eliminating the over-segmentation phenomenon.

关键词

Keywords

references

Akinlar C, Topal C. EDLines: A real-time line segment detector with a false detection control[J]. Pattern Recognition Letters, 2011, 32(13): 1633-1642. DOI: 1633

Grompone V G R, Jakubowicz J, Morel J M, et al. LSD: a fast line segment detector with a false detection control[J]. IEEE Transactions on Pattern Analysis % Machine Intelligence, 2010, 32(4): 722-732. DOI: 722

Desolneux A, Moisan L, Morel J M. Meaningful alignments[J]. International Journal of Computer Vision, 2000, 40(1): 7-23. DOI: 7

Chan T S, Yip R K. Line detection algorithm[C]// International Conference on Pattern Recognition. Beijing, China, IEEEXplore, 1996: 126-130.

Hamid N, Khan N. LSM: perceptually accurate line segment merging[J]. Journal of Electronic Imaging, 2016, 25(6): 61-62. DOI: 61

New York Desolneux A, Moisan L, Morel J M. From gestalt theory to image analysis[M]. New York, Springer, 2008.

Ballard D H. Generalising the hough transform to detect arbitrary shapes[J]. Recognition Pattern, 1981, 13(2): 111-122. DOI: 111

李树全, 房冬丽. 一种基于Amold变换的彩色图像水印算法[J]. 微电子学与计算机, 2017, 34(1): 53-57. DOI: 53

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Aerial small object detection algorithm based on improved RT-DETR

High gain stability high temperature operational amplifier based on reverse body bias

A review of large model development: technological evolution from BERT to Deepseek

Design of ultra-low power real-time clock circuits

Research on the design of blockchain-based AI-generated content traceability framework

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰