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
Um grande número de técnicas tem sido proposto para aceleração da Transformada de Hough, porque a transformação é computacionalmente muito cara em geral. Sabe-se que o intervalo de amostragem no espaço paramétrico está fortemente relacionado ao custo de cálculo. A precisão da transformação e a velocidade de processamento estão numa relação de compromisso. Nenhuma comparação justa da velocidade de processamento entre os vários métodos foi realizada em todos os trabalhos anteriores, porque nenhum critério foi fornecido para o intervalo de amostragem do parâmetro e porque a precisão do parâmetro não era igual entre os métodos. No início de nossa pesquisa, derivamos a relação entre o intervalo de amostragem e a precisão do parâmetro. Em seguida, derivamos uma estrutura para comparar o custo de cálculo sob condições iguais de precisão do parâmetro, considerando o número total de pontos de amostragem de um parâmetro como o custo de cálculo. Definimos o erro de transformação na Transformada de Hough, e o erro é considerado como ruído de transformação. Neste artigo também propomos um método de projeto chamado "Noise-level Shaping", pelo qual podemos definir o ruído de transformação em um nível arbitrário. O nível do ruído varia de acordo com o valor de um parâmetro. O Noise-level Shaping nos permite encontrar a parametrização eficiente e o intervalo de amostragem eficiente em uma aplicação específica da Transformada 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 -