MONOGENIC-LBP: A new approach for rotation invariant texture classification

Lin Zhang; Lei Zhang; Zhenhua Guo; Dapeng Zhang

doi:10.1109/ICIP.2010.5651885

MONOGENIC-LBP: A new approach for rotation invariant texture classification

Lin Zhang
, Lei Zhang
, Zhenhua Guo
, Dapeng Zhang

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

59 Citations (Scopus)

Abstract

Analysis of two-dimensional textures has many potential applications in computer vision. In this paper, we investigate the problem of rotation invariant texture classification, and propose a novel texture feature extractor, namely Monogenic-LBP (M-LBP). M-LBP integrates the traditional Local Binary Pattern (LBP) operator with the other two rotation invariant measures: the local phase and the local surface type computed by the 1st-order and 2nd-order Riesz transforms, respectively. The classification is based on the image's histogram of M-LBP responses. Extensive experiments conducted on the CUReT database demonstrate the overall superiority of M-LBP over the other state-of-the-art methods evaluated.

Original language	English
Title of host publication	2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Pages	2677-2680
Number of pages	4
DOIs	https://doi.org/10.1109/ICIP.2010.5651885
Publication status	Published - 1 Dec 2010
Event	2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong Duration: 26 Sept 2010 → 29 Sept 2010

Conference

Conference	2010 17th IEEE International Conference on Image Processing, ICIP 2010
Country/Territory	Hong Kong
City	Hong Kong
Period	26/09/10 → 29/09/10

Keywords

LBP
Monogenic signal
Texture classification

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Signal Processing

More information

10.1109/ICIP.2010.5651885

Cite this

@inproceedings{27504ce78f964ab09f51f62b71c07872,

title = "MONOGENIC-LBP: A new approach for rotation invariant texture classification",

abstract = "Analysis of two-dimensional textures has many potential applications in computer vision. In this paper, we investigate the problem of rotation invariant texture classification, and propose a novel texture feature extractor, namely Monogenic-LBP (M-LBP). M-LBP integrates the traditional Local Binary Pattern (LBP) operator with the other two rotation invariant measures: the local phase and the local surface type computed by the 1st-order and 2nd-order Riesz transforms, respectively. The classification is based on the image's histogram of M-LBP responses. Extensive experiments conducted on the CUReT database demonstrate the overall superiority of M-LBP over the other state-of-the-art methods evaluated.",

keywords = "LBP, Monogenic signal, Texture classification",

author = "Lin Zhang and Lei Zhang and Zhenhua Guo and Dapeng Zhang",

year = "2010",

month = dec,

day = "1",

doi = "10.1109/ICIP.2010.5651885",

language = "English",

isbn = "9781424479948",

pages = "2677--2680",

booktitle = "2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings",

note = "2010 17th IEEE International Conference on Image Processing, ICIP 2010 ; Conference date: 26-09-2010 Through 29-09-2010",

}

Zhang, L, Zhang, L, Guo, Z & Zhang, D 2010, MONOGENIC-LBP: A new approach for rotation invariant texture classification. in 2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings., 5651885, pp. 2677-2680, 2010 17th IEEE International Conference on Image Processing, ICIP 2010, Hong Kong, Hong Kong, 26/09/10. https://doi.org/10.1109/ICIP.2010.5651885

MONOGENIC-LBP: A new approach for rotation invariant texture classification. / Zhang, Lin; Zhang, Lei; Guo, Zhenhua et al.
2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings. 2010. p. 2677-2680 5651885.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - MONOGENIC-LBP: A new approach for rotation invariant texture classification

AU - Zhang, Lin

AU - Zhang, Lei

AU - Guo, Zhenhua

AU - Zhang, Dapeng

PY - 2010/12/1

Y1 - 2010/12/1

N2 - Analysis of two-dimensional textures has many potential applications in computer vision. In this paper, we investigate the problem of rotation invariant texture classification, and propose a novel texture feature extractor, namely Monogenic-LBP (M-LBP). M-LBP integrates the traditional Local Binary Pattern (LBP) operator with the other two rotation invariant measures: the local phase and the local surface type computed by the 1st-order and 2nd-order Riesz transforms, respectively. The classification is based on the image's histogram of M-LBP responses. Extensive experiments conducted on the CUReT database demonstrate the overall superiority of M-LBP over the other state-of-the-art methods evaluated.

AB - Analysis of two-dimensional textures has many potential applications in computer vision. In this paper, we investigate the problem of rotation invariant texture classification, and propose a novel texture feature extractor, namely Monogenic-LBP (M-LBP). M-LBP integrates the traditional Local Binary Pattern (LBP) operator with the other two rotation invariant measures: the local phase and the local surface type computed by the 1st-order and 2nd-order Riesz transforms, respectively. The classification is based on the image's histogram of M-LBP responses. Extensive experiments conducted on the CUReT database demonstrate the overall superiority of M-LBP over the other state-of-the-art methods evaluated.

KW - LBP

KW - Monogenic signal

KW - Texture classification

UR - https://www.scopus.com/pages/publications/78651073040

U2 - 10.1109/ICIP.2010.5651885

DO - 10.1109/ICIP.2010.5651885

M3 - Conference article published in proceeding or book

SN - 9781424479948

SP - 2677

EP - 2680

BT - 2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings

T2 - 2010 17th IEEE International Conference on Image Processing, ICIP 2010

Y2 - 26 September 2010 through 29 September 2010

ER -

MONOGENIC-LBP: A new approach for rotation invariant texture classification

Abstract

Conference

Keywords

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this