Filtering with Gray-code kernels

Author

Ben-Artzi, Gil ; Hel-Or, Hagit ; Hel-Or, Yacov

Author_Institution

Bar-Ilan Univ., Ramat-Gan, Israel

Volume

1

fYear

2004

fDate

23-26 Aug. 2004

Firstpage

556

Abstract

In this paper, we introduce a family of filter kernels - the Gray-code kernels (GCK) and demonstrate their use in image analysis. Filtering an image with a sequence of Gray-code kernels is highly efficient and requires only 2 operations per pixel for each filter kernel, independent of the size or dimension of the kernel. We show that the family of kernels is large and includes the Walsh-Hadamard kernels amongst others. The GCK can also be used to approximate arbitrary kernels since, a sequence of GCK can form a complete representation. The efficiency of computation using a sequence of GCK filters can be exploited for various real-time applications, such as pattern detection, feature extraction, texture analysis, and more.

Keywords

Gray codes; filtering theory; image sequences; trees (mathematics); Gray code kernels filter; Gray code kernels sequence; Walsh-Hadamard kernels; binary tree; feature extraction; image analysis; image filtering; pattern detection; texture analysis; Binary trees; Convolution; Feature extraction; Filtering; Filters; Image sequence analysis; Image texture analysis; Kernel; Pattern analysis; Pixel;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on

ISSN

1051-4651

Print_ISBN

0-7695-2128-2

Type

conf

DOI

10.1109/ICPR.2004.1334198

Filename

1334198