Texture analysis using local region contrast

Jiangping He; Hongwei Ji; Xin Yang

doi:10.1117/1.JEI.22.2.023007

9 May 2013 Texture analysis using local region contrast

Jiangping He, Hongwei Ji, Xin Yang

Author Affiliations +

Funded by: National Basic Research Program of China

Journal of Electronic Imaging, Vol. 22, Issue 2, 023007 (May 2013). https://doi.org/10.1117/1.JEI.22.2.023007

Abstract

The local binary pattern (LBP) operator is a very effective texture descriptor that describes images using texture patterns. However, existing LBP operators discard the texture contrast information by definition and, in addition, they are sensitive to noise. This paper presents a local contrast descriptor (LCD) to represent images using texture contrast by measuring how far neighbors are spread out in a given neighborhood. LCD and LBPs can be combined to improve texture description performance. Furthermore, the LCD is extended to the local ternary contrast descriptor (LTCD) to describe textures using both contrast and magnitude features. Experiments on the UIUC texture database show that the LCD and LBP combinations are more accurate than either descriptor alone and LCD is an easy and efficient complement to LBPs. Experiments on the FERET face database and the database in which the probe sets contain added noise show that LCD, especially LTCD, has promising discriminative power and strong robustness against noise.

Citation Download Citation

Jiangping He, Hongwei Ji, and Xin Yang "Texture analysis using local region contrast," Journal of Electronic Imaging 22(2), 023007 (9 May 2013). https://doi.org/10.1117/1.JEI.22.2.023007

Published: 9 May 2013

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE