• Randomized Hough transform (RH...

Treffer: Randomized Hough transform (RHT) : basic mechanisms, algorithms, and computational complexities

Title:
Randomized Hough transform (RHT) : basic mechanisms, algorithms, and computational complexities
Authors:
LEI XU, OJA, E
Source:
CVGIP. Image understanding. 57(2):131-154
Publisher Information:
Boston, MA; New York, NY; San Diego, CA: Academic Press, 1993.
Publication Year:
1993
Physical Description:
print, 23 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Reconnaissance des formes. Traitement numérique des images. Géométrie algorithmique, Pattern recognition. Digital image processing. Computational geometry, Analyse qualitative, Qualitative analysis, Análisis cualitativo, Complexité calcul, Computing complexity, Complejidad cálculo, Image bruitée, Noisy image, Imagen sonora, Traitement image, Image processing, Procesamiento imagen, Transformation Hough, Hough transformation, Transformación Hough, Analyse probabilité, Probability analysis, Détection courbe, Curve detection, Processus Bernoulli généralisé, Generalized Bernoulli process
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Lappeenranta univ. technology, dep. information technology, 53851 Lappeenranta, Finland
ISSN:
1049-9660
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=4902562
Rights:
Copyright 1993 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.4902562
Database:
PASCAL Archive

Weitere Informationen

Recently, a new curve detection approach called the randomized Hough transform (RHT) was heuristically proposed by the authors, inspired by the efforts of using neural computation learning techniques for curve detection. The preliminary experimental results and some qualitative analysis showed that in comparison with the Hough transform (HT) and its variants, the RHT has advantages of fast speed, small storage, infinite range of the parameter space, and high parameter resolution, and it can overcome several difficulties encountered with the HT methods. In this paper, the basic ideas of RHT are further developed into a more systematic and theoretically supported new method for curve detection. The fundamental framework and the main components of this method are elaborated.