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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
변환은 일반적으로 계산적으로 매우 비용이 많이 들기 때문에 Hough 변환을 가속화하기 위해 많은 기술이 제안되었습니다. 매개변수 공간의 샘플링 간격은 계산 비용과 밀접한 관련이 있는 것으로 알려져 있습니다. 변환의 정밀도와 처리 속도는 트레이드오프 관계에 있습니다. 이전의 모든 연구에서는 매개변수의 샘플링 간격에 대한 기준이 제공되지 않았고 매개변수의 정밀도가 방법 간 동일하지 않았기 때문에 다양한 방법 간의 처리 속도에 대한 공정한 비교가 수행되지 않았습니다. 연구 초기에 우리는 샘플링 간격과 매개변수의 정밀도 사이의 관계를 도출했습니다. 그런 다음 매개변수의 전체 샘플링 포인트 수를 계산 비용으로 간주하여 매개변수의 정밀도에 대한 동일한 조건에서 계산 비용을 비교하는 프레임워크를 도출합니다. Hough Transform에서 변환 오류를 정의하고 해당 오류를 변환 노이즈로 간주합니다. 본 논문에서는 변환 노이즈를 임의의 수준으로 설정할 수 있는 "Noise-level Shaping"이라는 설계 방법도 제안합니다. 노이즈의 레벨은 매개변수 값에 따라 달라집니다. Noise-level Shaping을 사용하면 Hough Transform의 특정 응용 분야에서 효율적인 매개변수화를 찾고 효율적인 샘플링 간격을 찾을 수 있습니다.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
부
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
부
@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},}
부
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 -