Robust method for interest region description based on local intensity binary pattern

Yi Yang; Fajie Duan; Jiajia Jiang; Ling Ma; Hao Zheng

doi:10.1117/1.JEI.26.4.043025

28 August 2017 Robust method for interest region description based on local intensity binary pattern

Yi Yang, Fajie Duan, Jiajia Jiang, Ling Ma, Hao Zheng

Author Affiliations +

Journal of Electronic Imaging, Vol. 26, Issue 4, 043025 (August 2017). https://doi.org/10.1117/1.JEI.26.4.043025

Abstract

This paper proposes a robust method based on a local intensity binary pattern for interest feature description. To avoid estimating reference orientation, local features were calculated on a rotation invariant system. Different from the local binary patterns (LBP) and center-symmetric-LBP operator, our proposed local circular contrast pattern (LCCP) operator calculates a local binary feature by comparing the relative intensity order information of each two adjacent elements in the sequence consisting of the sampling point and its neighboring points. To evaluate the performance of our proposed descriptor LCCP and other existing descriptors (e.g., scale-invariant feature transform, DAISY, HRI-CSLTP, multisupport region order-based gradient histogram-single, local intensity order pattern), image matching experiments were first conducted on the Oxford dataset, additional image pairs with complex light changes, image sequences with different noise, and three-dimensional objects dataset. To further evaluate the discriminative ability of local descriptors, a simple object recognition experiment was carried out on three public datasets. The experimental results show that our descriptor LCCP exhibits a better performance and robustness than other evaluated descriptors.

Citation Download Citation

Yi Yang, Fajie Duan, Jiajia Jiang, Ling Ma, and Hao Zheng "Robust method for interest region description based on local intensity binary pattern," Journal of Electronic Imaging 26(4), 043025 (28 August 2017). https://doi.org/10.1117/1.JEI.26.4.043025

Received: 28 March 2017; Accepted: 9 August 2017; Published: 28 August 2017

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

Includes PDF, HTML & Video, when available