The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Un grand nombre de techniques ont été proposées pour accélérer la transformée de Hough, car la transformation est en général très coûteuse en termes de calcul. On sait que l’intervalle d’échantillonnage dans l’espace des paramètres est fortement lié au coût de calcul. La précision de la transformation et la vitesse de traitement sont dans une relation de compromis. Aucune comparaison équitable de la vitesse de traitement entre les différentes méthodes n'a été effectuée dans tous les travaux précédents, car aucun critère n'avait été donné pour l'intervalle d'échantillonnage du paramètre et parce que la précision du paramètre n'était pas égale entre les méthodes. Au début de nos recherches, nous dérivons la relation entre l'intervalle d'échantillonnage et la précision du paramètre. Ensuite, nous dérivons un cadre pour comparer le coût de calcul dans des conditions égales de précision du paramètre, en considérant le nombre total de points d'échantillonnage d'un paramètre comme coût de calcul. Nous définissons l'erreur de transformation dans la transformation de Hough, et l'erreur est considérée comme du bruit de transformation. Dans cet article, nous proposons également une méthode de conception appelée « Noise-level Shaping », grâce à laquelle nous pouvons définir le bruit de transformation à un niveau arbitraire. Le niveau du bruit varie en fonction de la valeur d'un paramètre. Le Noise-level Shaping nous permet de trouver le paramétrage efficace et de trouver l'intervalle d'échantillonnage efficace dans une application spécifique de la transformée de Hough.
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Hideaki GOTO, Hirotomo ASO, "Designing Efficient Hough Transform by Noise-Level Shaping" in IEICE TRANSACTIONS on Information,
vol. E83-D, no. 2, pp. 242-250, February 2000, doi: .
Abstract: A large number of techniques have been proposed for acceleration of the Hough Transform, because the transformation is computationally very expensive in general. It is known that the sampling interval in parameter space is strongly related to the computation cost. The precision of the transformation and the processing speed are in a trade-off relationship. No fair comparison of the processing speed between various methods was performed in all previous works, because no criterion had been given for the sampling interval of parameter, and because the precision of parameter was not equal between methods. At the beginning of our research, we derive the relationship between the sampling interval and the precision of parameter. Then we derive a framework for comparing computation cost under equal condition for precision of parameter, regarding the total number of sampling points of a parameter as the computation cost. We define the transformation error in the Hough Transform, and the error is regarded as transformation noise. In this paper we also propose a design method called "Noise-level Shaping," by which we can set the transformation noise to an arbitrarily level. The level of the noise is varied according to the value of a parameter. Noise-level Shaping makes it possible for us to find the efficient parameterization and to find the efficient sampling interval in a specific application of the Hough Transform.
URL: https://global.ieice.org/en_transactions/information/10.1587/e83-d_2_242/_p
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@ARTICLE{e83-d_2_242,
author={Hideaki GOTO, Hirotomo ASO, },
journal={IEICE TRANSACTIONS on Information},
title={Designing Efficient Hough Transform by Noise-Level Shaping},
year={2000},
volume={E83-D},
number={2},
pages={242-250},
abstract={A large number of techniques have been proposed for acceleration of the Hough Transform, because the transformation is computationally very expensive in general. It is known that the sampling interval in parameter space is strongly related to the computation cost. The precision of the transformation and the processing speed are in a trade-off relationship. No fair comparison of the processing speed between various methods was performed in all previous works, because no criterion had been given for the sampling interval of parameter, and because the precision of parameter was not equal between methods. At the beginning of our research, we derive the relationship between the sampling interval and the precision of parameter. Then we derive a framework for comparing computation cost under equal condition for precision of parameter, regarding the total number of sampling points of a parameter as the computation cost. We define the transformation error in the Hough Transform, and the error is regarded as transformation noise. In this paper we also propose a design method called "Noise-level Shaping," by which we can set the transformation noise to an arbitrarily level. The level of the noise is varied according to the value of a parameter. Noise-level Shaping makes it possible for us to find the efficient parameterization and to find the efficient sampling interval in a specific application of the Hough Transform.},
keywords={},
doi={},
ISSN={},
month={February},}
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TY - JOUR
TI - Designing Efficient Hough Transform by Noise-Level Shaping
T2 - IEICE TRANSACTIONS on Information
SP - 242
EP - 250
AU - Hideaki GOTO
AU - Hirotomo ASO
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E83-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2000
AB - A large number of techniques have been proposed for acceleration of the Hough Transform, because the transformation is computationally very expensive in general. It is known that the sampling interval in parameter space is strongly related to the computation cost. The precision of the transformation and the processing speed are in a trade-off relationship. No fair comparison of the processing speed between various methods was performed in all previous works, because no criterion had been given for the sampling interval of parameter, and because the precision of parameter was not equal between methods. At the beginning of our research, we derive the relationship between the sampling interval and the precision of parameter. Then we derive a framework for comparing computation cost under equal condition for precision of parameter, regarding the total number of sampling points of a parameter as the computation cost. We define the transformation error in the Hough Transform, and the error is regarded as transformation noise. In this paper we also propose a design method called "Noise-level Shaping," by which we can set the transformation noise to an arbitrarily level. The level of the noise is varied according to the value of a parameter. Noise-level Shaping makes it possible for us to find the efficient parameterization and to find the efficient sampling interval in a specific application of the Hough Transform.
ER -