Interest region description using local binary pattern of gradients

Abstract

Multispectral imaging system maps the contents of a scene to different intensity levels with in spectral images. This imaging process induces spectral variations among the different wavelength band images of the same scene and results in uncorrelated interest region descriptors for cross spectral image matching. This paper presents Local Binary Pattern of Gradients (LBPG) to improve the strength of interest region description under such spectral variations. In LBPG the image gradients are first transformed into binary patterns and then the gradient patterns are used instead of raw gradients for interest region description. We validate the LBPG approach on the spectral images of six different indoor and outdoor scenes. The experimental results confirm better cross spectral image matching performance as compared to SIFT and Center Symmetric Local Binary Patterns. © 2013 Springer-Verlag.