Use of the Hough transformation to detect lines and curves in pictures

Richard O. Duda; Peter E. Hart

doi:10.1145/361237.361242

journal article Jan 01, 1972

Use of the Hough transformation to detect lines and curves in pictures

Richard O. Duda Peter E. Hart

Communications of the ACM Vol. 15 No. 1 pp. 11-15 · Association for Computing Machinery (ACM)

View at Publisher Save 10.1145/361237.361242

Abstract

Hough has proposed an interesting and computationally efficient procedure for detecting lines in pictures. This paper points out that the use of angle-radius rather than slope-intercept parameters simplifies the computation further. It also shows how the method can be used for more general curve fitting, and gives alternative interpretations that explain the source of its efficiency.

Topics

No keywords indexed for this article. Browse by subject →

References

3

[1]

10.1145/356551.356554

[2]

Hough, P.V.C. Method and means for recognizing complex patterns. U.S. Patent 3,069,654, Dec. 18, 1962.

[3]

Griffith, A.K. Computer recognition of prismatic solids. Ph.D. Th., Dep. of Math., MIT, June 1970.

Cited By

5,056

Automatic lining fabrication for shield tunnels: theoretical framework and full-scale test verification

Zeyuan Wang, Yeting Zhu · 2026

Tunnelling and Underground Space Te...

Stereo 3D tracker: a novel framework for real-time 3D point tracking in fisheye stereo photogrammetry

Ali Hosseininaveh · 2026

ISPRS Journal of Photogrammetry and...

Vision-Based 6D Pose Analytics Solution for High-Precision Industrial Robot Pick-and-Place Applications

Balamurugan Balasubramanian, Kamil Cetin · 2025

Sensors

End-to-end part quality classification for two-photon lithography using computer vision

Sixian Jia, Shichen Li · 2025

Manufacturing Letters

Attention-Based Deep Recurrent Neural Network for Semantic Segmentation of 4-D Radar Data Acquired During Landing Maneuver

Solène Vilfroy, Thierry Urruty · 2024

IEEE Transactions on Radar Systems

An Efficient Edge-Based System for Nucleated Oval-Shaped Red Blood Cell Counting

Carlo Centofanti, Daniele Lozzi · 2024

IEEE Access

Enhancement of Ambient Mass Spectrometry Imaging Data by Image Restoration

Yuchen Xiang, Martin Metodiev · 2023

Metabolites

Contact evolution of dry and hydrated fingertips at initial touch

Gokhan Serhat, Yasemin Vardar · 2022

PLoS ONE

Towards accurate prediction for ultra-low carbon tempered martensite property through the cross-correlated substructures

Xingqi Jia, Wei Li · 2021

Materials & Design

Deep learning assisted vision inspection of resistance spot welds

Wei Dai, Dayong Li · 2021

Journal of Manufacturing Processes

Intelligent Detection of Vegetation Encroachment of Power Lines With Advanced Stereovision

Shuaiang Rong, Lina He · 2021

IEEE Transactions on Power Delivery

Computer Vision, Machine Learning, and the Promise of Phenomics in Ecology and Evolutionary Biology

Moritz D. Lürig, Seth Donoughe · 2021

Frontiers in Ecology and Evolution

Computer-automated tuning procedures for semiconductor quantum dot arrays

A. R. Mills, M. M. Feldman · 2019

Applied Physics Letters

Kernel density approach to error estimation of MF-DFA measures on time series

Jesús A. Sosa-Herrera, Suemi Rodríguez-Romo · 2019

Physica A: Statistical Mechanics an...

Development of a deep residual learning algorithm to screen for glaucoma from fundus photography

Naoto Shibata, Masaki Tanito · 2018

Scientific Reports

Roof plane extraction from airborne lidar point clouds

Rujun Cao, Yongjun Zhang · 2017

International Journal of Remote Sen...

Application of gradient-based Hough transform to the detection of corrosion pits in optical images

Yafei Wang, Guangxu Cheng · 2016

Applied Surface Science

An automatic method for detecting sliding railway wheels and hot bearings using thermal imagery

Hanieh Deilamsalehy, Timothy C Havens · 2016

Proceedings of the Institution of M...

A far distance wideband geoacoustic parameter inversion method based on a modal dispersion curve

Guo Xiao-Le, Yang Kun-De · 2015

Acta Physica Sinica

The value of integrating Scan-to-BIM and Scan-vs-BIM techniques for construction monitoring using laser scanning and BIM: The case of cylindrical MEP components

Frédéric Bosché, Mahmoud Ahmed · 2015

Automation in Construction

Metrics

5,056

Citations

3

References

Details

Published: Jan 01, 1972
Vol/Issue: 15(1)
Pages: 11-15
License: View

Authors

R

Richard O. Duda

Stanford Research Institute, Menlo Park, CA

P

Peter E. Hart

Stanford Research Institute, Menlo Park, CA

Cite This Article

Richard O. Duda, Peter E. Hart (1972). Use of the Hough transformation to detect lines and curves in pictures. Communications of the ACM, 15(1), 11-15. https://doi.org/10.1145/361237.361242

Use of the Hough transformation to detect lines and curves in pictures

You May Also Like