Fast Polar Cosine Transform for image description

Zhuo Yang; Sei Ichiro Kamata

Fast Polar Cosine Transform for image description

Zhuo Yang^*, Sei Ichiro Kamata

^*Corresponding author for this work

Graduate School of Information, Production and Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

Polar Cosine Transform (PCT) is one of the Polar Harmonic Transforms that those kernels are basic waves and harmonic in nature. They are proposed to represent invariant patterns for two dimensional image description and are demonstrated to show superiorities comparing with other methods on extracting rotation invariant patterns for images. However in order to increase the computation speed, fast algorithm for PCT is proposed for real world applications like limited computing environments, large image databases and realtime systems. Based on our previous work, this paper novelly employs relative prime number theory to develop Fast Polar Cosine Transform (FPCT). The proposed FPCT is averagely over 11 ∼ 12.5 times faster than PCT that significantly boost computation process. The experimental results are given to illustrate the effectiveness of the proposed method.

Original language	English
Title of host publication	Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011
Pages	320-323
Number of pages	4
Publication status	Published - 2011 Dec 1
Event	12th IAPR Conference on Machine Vision Applications, MVA 2011 - Nara, Japan Duration: 2011 Jun 13 → 2011 Jun 15

Publication series

Name	Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011

Conference

Conference	12th IAPR Conference on Machine Vision Applications, MVA 2011
Country/Territory	Japan
City	Nara
Period	11/6/13 → 11/6/15

ASJC Scopus subject areas

Computer Vision and Pattern Recognition

Cite this

@inproceedings{ecf221edd10f48f3affc595c2448c871,

title = "Fast Polar Cosine Transform for image description",

abstract = "Polar Cosine Transform (PCT) is one of the Polar Harmonic Transforms that those kernels are basic waves and harmonic in nature. They are proposed to represent invariant patterns for two dimensional image description and are demonstrated to show superiorities comparing with other methods on extracting rotation invariant patterns for images. However in order to increase the computation speed, fast algorithm for PCT is proposed for real world applications like limited computing environments, large image databases and realtime systems. Based on our previous work, this paper novelly employs relative prime number theory to develop Fast Polar Cosine Transform (FPCT). The proposed FPCT is averagely over 11 ∼ 12.5 times faster than PCT that significantly boost computation process. The experimental results are given to illustrate the effectiveness of the proposed method.",

author = "Zhuo Yang and Kamata, {Sei Ichiro}",

year = "2011",

month = dec,

day = "1",

language = "English",

isbn = "9784901122115",

series = "Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011",

pages = "320--323",

booktitle = "Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011",

note = "12th IAPR Conference on Machine Vision Applications, MVA 2011 ; Conference date: 13-06-2011 Through 15-06-2011",

}

TY - GEN

T1 - Fast Polar Cosine Transform for image description

AU - Yang, Zhuo

AU - Kamata, Sei Ichiro

PY - 2011/12/1

Y1 - 2011/12/1

N2 - Polar Cosine Transform (PCT) is one of the Polar Harmonic Transforms that those kernels are basic waves and harmonic in nature. They are proposed to represent invariant patterns for two dimensional image description and are demonstrated to show superiorities comparing with other methods on extracting rotation invariant patterns for images. However in order to increase the computation speed, fast algorithm for PCT is proposed for real world applications like limited computing environments, large image databases and realtime systems. Based on our previous work, this paper novelly employs relative prime number theory to develop Fast Polar Cosine Transform (FPCT). The proposed FPCT is averagely over 11 ∼ 12.5 times faster than PCT that significantly boost computation process. The experimental results are given to illustrate the effectiveness of the proposed method.

AB - Polar Cosine Transform (PCT) is one of the Polar Harmonic Transforms that those kernels are basic waves and harmonic in nature. They are proposed to represent invariant patterns for two dimensional image description and are demonstrated to show superiorities comparing with other methods on extracting rotation invariant patterns for images. However in order to increase the computation speed, fast algorithm for PCT is proposed for real world applications like limited computing environments, large image databases and realtime systems. Based on our previous work, this paper novelly employs relative prime number theory to develop Fast Polar Cosine Transform (FPCT). The proposed FPCT is averagely over 11 ∼ 12.5 times faster than PCT that significantly boost computation process. The experimental results are given to illustrate the effectiveness of the proposed method.

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M3 - Conference contribution

AN - SCOPUS:84872574754

SN - 9784901122115

T3 - Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011

SP - 320

EP - 323

BT - Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011

T2 - 12th IAPR Conference on Machine Vision Applications, MVA 2011

Y2 - 13 June 2011 through 15 June 2011

ER -

Fast Polar Cosine Transform for image description

Abstract

Publication series

Conference

ASJC Scopus subject areas

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