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
PFD(Polar Fourier Descriptor) 및 SFD(Spherical Fourier Descriptor)는 2차원(3D) 및 2차원(3D) 이미지 검색 및 패턴 인식 작업을 위한 회전 불변 특징 설명자입니다. 이는 8D 및 16D 이미지의 회전 불변 특징을 설명하는 데 있어 다른 방법과 비교하여 우월성을 보여주는 것으로 입증되었습니다. 그러나 계산 속도를 높이려면 특히 실시간 시스템, 제한된 컴퓨팅 환경 및 대규모 이미지 데이터베이스와 같은 머신 비전 응용 프로그램의 경우 빠른 계산 방법이 필요합니다. 본 논문에서는 삼각함수와 관련 르장드르 다항식의 수학적 특성을 기반으로 추론된 PFD 및 SFD의 빠른 계산 방법을 제시합니다. 제안된 빠른 PFD 및 SFD는 직접 계산보다 XNUMX배 및 XNUMX배 빠르며 계산 프로세스를 크게 향상시킵니다. 또한 제안된 방법은 PFD 및 SFD 기반을 룩업 테이블에 저장하기 위한 메모리 요구 사항에도 적합합니다. 제안된 방법의 효율성을 설명하기 위해 합성 데이터와 실제 데이터에 대한 실험 결과가 제공됩니다.
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Zhuo YANG, Sei-ichiro KAMATA, "Fast Polar and Spherical Fourier Descriptors for Feature Extraction" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 7, pp. 1708-1715, July 2010, doi: 10.1587/transinf.E93.D.1708.
Abstract: Polar Fourier Descriptor(PFD) and Spherical Fourier Descriptor(SFD) are rotation invariant feature descriptors for two dimensional(2D) and three dimensional(3D) image retrieval and pattern recognition tasks. They are demonstrated to show superiorities compared with other methods on describing rotation invariant features of 2D and 3D images. However in order to increase the computation speed, fast computation method is needed especially for machine vision applications like realtime systems, limited computing environments and large image databases. This paper presents fast computation method for PFD and SFD that are deduced based on mathematical properties of trigonometric functions and associated Legendre polynomials. Proposed fast PFD and SFD are 8 and 16 times faster than direct calculation that significantly boost computation process. Furthermore, the proposed methods are also compact for memory requirements for storing PFD and SFD basis in lookup tables. The experimental results on both synthetic and real data are given to illustrate the efficiency of the proposed method.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.1708/_p
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@ARTICLE{e93-d_7_1708,
author={Zhuo YANG, Sei-ichiro KAMATA, },
journal={IEICE TRANSACTIONS on Information},
title={Fast Polar and Spherical Fourier Descriptors for Feature Extraction},
year={2010},
volume={E93-D},
number={7},
pages={1708-1715},
abstract={Polar Fourier Descriptor(PFD) and Spherical Fourier Descriptor(SFD) are rotation invariant feature descriptors for two dimensional(2D) and three dimensional(3D) image retrieval and pattern recognition tasks. They are demonstrated to show superiorities compared with other methods on describing rotation invariant features of 2D and 3D images. However in order to increase the computation speed, fast computation method is needed especially for machine vision applications like realtime systems, limited computing environments and large image databases. This paper presents fast computation method for PFD and SFD that are deduced based on mathematical properties of trigonometric functions and associated Legendre polynomials. Proposed fast PFD and SFD are 8 and 16 times faster than direct calculation that significantly boost computation process. Furthermore, the proposed methods are also compact for memory requirements for storing PFD and SFD basis in lookup tables. The experimental results on both synthetic and real data are given to illustrate the efficiency of the proposed method.},
keywords={},
doi={10.1587/transinf.E93.D.1708},
ISSN={1745-1361},
month={July},}
부
TY - JOUR
TI - Fast Polar and Spherical Fourier Descriptors for Feature Extraction
T2 - IEICE TRANSACTIONS on Information
SP - 1708
EP - 1715
AU - Zhuo YANG
AU - Sei-ichiro KAMATA
PY - 2010
DO - 10.1587/transinf.E93.D.1708
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2010
AB - Polar Fourier Descriptor(PFD) and Spherical Fourier Descriptor(SFD) are rotation invariant feature descriptors for two dimensional(2D) and three dimensional(3D) image retrieval and pattern recognition tasks. They are demonstrated to show superiorities compared with other methods on describing rotation invariant features of 2D and 3D images. However in order to increase the computation speed, fast computation method is needed especially for machine vision applications like realtime systems, limited computing environments and large image databases. This paper presents fast computation method for PFD and SFD that are deduced based on mathematical properties of trigonometric functions and associated Legendre polynomials. Proposed fast PFD and SFD are 8 and 16 times faster than direct calculation that significantly boost computation process. Furthermore, the proposed methods are also compact for memory requirements for storing PFD and SFD basis in lookup tables. The experimental results on both synthetic and real data are given to illustrate the efficiency of the proposed method.
ER -