TY - GEN
T1 - Fast polar harmonic transforms
AU - Yang, Zhuo
AU - Kamata, Sei Ichiro
PY - 2010
Y1 - 2010
N2 - Polar Harmonic Transform (PHT) is termed to represent a set of transforms those kernels are basic waves and harmonic in nature. PHTs consist of Polar Complex Exponential Transform (PCET), Polar Cosine Transform (PCT) and Polar Sine Transform (PST). They are proposed to represent invariant image patterns for two dimensional image retrieval and pattern recognition tasks. They are demonstrated to show superiorities comparing with other methods on describing rotation invariant patterns for images. Kernel computation of PHTs is also simple and has no numerical stability issue. However in order to increase the computation speed, fast computation method is needed especially for real world applications like limited computing environments, large image databases and realtime systems. This paper presents Fast Polar Harmonic Transforms (FPHTs) including Fast Polar Complex Exponential Transform (FPCET), Fast Polar Cosine Transform (FPCT) and Fast Polar Sine Transform (FPST) that are deduced based on mathematical properties of trigonometric functions. The proposed FPHTs are averagely over 6 ∼ 8 times faster than PHTs that significantly boost computation process. The experimental results on both synthetic and real data are given to illustrate the effectiveness of the proposed fast transforms.
AB - Polar Harmonic Transform (PHT) is termed to represent a set of transforms those kernels are basic waves and harmonic in nature. PHTs consist of Polar Complex Exponential Transform (PCET), Polar Cosine Transform (PCT) and Polar Sine Transform (PST). They are proposed to represent invariant image patterns for two dimensional image retrieval and pattern recognition tasks. They are demonstrated to show superiorities comparing with other methods on describing rotation invariant patterns for images. Kernel computation of PHTs is also simple and has no numerical stability issue. However in order to increase the computation speed, fast computation method is needed especially for real world applications like limited computing environments, large image databases and realtime systems. This paper presents Fast Polar Harmonic Transforms (FPHTs) including Fast Polar Complex Exponential Transform (FPCET), Fast Polar Cosine Transform (FPCT) and Fast Polar Sine Transform (FPST) that are deduced based on mathematical properties of trigonometric functions. The proposed FPHTs are averagely over 6 ∼ 8 times faster than PHTs that significantly boost computation process. The experimental results on both synthetic and real data are given to illustrate the effectiveness of the proposed fast transforms.
KW - Fast polar complex exponential transform
KW - Fast polar cosine transform
KW - Fast polar harmonic transform
KW - Fast polar sine transform
KW - Image retrieval
KW - Pattern recognition
UR - http://www.scopus.com/inward/record.url?scp=79952425606&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952425606&partnerID=8YFLogxK
U2 - 10.1109/ICARCV.2010.5707939
DO - 10.1109/ICARCV.2010.5707939
M3 - Conference contribution
AN - SCOPUS:79952425606
SN - 9781424478132
T3 - 11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010
SP - 673
EP - 677
BT - 11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010
T2 - 11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010
Y2 - 7 December 2010 through 10 December 2010
ER -