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Journal of Electronic Imaging

Robust method for interest region description based on local intensity binary pattern
Author(s): Yi Yang; Fajie Duan; Jiajia Jiang; Ling Ma; Hao Zheng
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Paper 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.

Paper Details

Date Published: 28 August 2017
PDF: 11 pages
J. Electron. Imag. 26(4) 043025 doi: 10.1117/1.JEI.26.4.043025
Published in: Journal of Electronic Imaging Volume 26, Issue 4
Show Author Affiliations
Yi Yang, Tianjin Univ. (China)
Fajie Duan, Tianjin Univ. (China)
Jiajia Jiang, Tianjin Univ. (China)
Ling Ma, Tianjin Univ. (China)
Hao Zheng, Tianjin Univ. (China)

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