Accurate and efficient curve detection in images: the importance sampling Hough transform

DOI10.1016/S0031-3203(01)00114-5zbMath1016.68085OpenAlexW2135532567MaRDI QIDQ1601558

R. Smith

Publication date: 27 June 2002

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0031-3203(01)00114-5

zbMATH Keywords

clusteringHough transformtarget distribution

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)

Related Items (3)

Speed up the computation of randomized algorithms for detecting lines, circles, and ellipses using novel tuning- and LUT-based voting platform ⋮ Closed form line-segment extraction using the Hough transform ⋮ Real-time accurate circle fitting with occlusions

Cites Work

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• Use of the Hough transformation to detect lines and curves in pictures
• Printer graphics for clustering
• Randomized Hough Transform: Improved ellipse detection with comparison
• How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis
• Model-Based Gaussian and Non-Gaussian Clustering
• A new curve detection method: Randomized Hough transform (RHT)

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