This work develops a novel face-based matcher composed of a multi-resolution hierarchy of patch-based feature descriptors for periocular recognition recognition based on the soft tissue surrounding the eye orbit. The novel patch-based framework for periocular recognition is compared against other feature descriptors and a commercial full-face recognition system against a set of four uniquely ch...

The local binary pattern approach has evolved to represent a significant breakthrough in texture analysis, outperforming earlier methods in many applications. Perhaps the most important property of the LBP operator in real-world applications is its tolerance against illumination changes. Another equally important is its computational simplicity, which makes it possible to analyze images in chal...

The beneficial characteristics of Local Binary Pattern can be conserved by computing simple approach COMPLETE LBP (CLBP). The proposed technique called Binary Rotation Invariance and Noise Tolerant texture classification is mainly based this CLBP approach. This BRINT not just exhibits better execution than various late cutting edge LBP variations under ordinary conditions, but also performs sig...

0957-4174/$ see front matter 2010 Elsevier Ltd. A doi:10.1016/j.eswa.2010.11.048 ⇑ Corresponding author. E-mail addresses: [email protected], lnanni@de [email protected] (S. Brahnam), alessandra.lum This paper focuses on the combination of variants of local binary patterns (LBP), widely considered the state of the art among texture descriptors, using the same radius and the same number o...

Recently, a spatiotemporal local binary pattern operator from three orthogonal planes (LBP-TOP) was proposed for describing and recognizing dynamic textures and applied to facial expression recognition. In this paper, we extend the LBP-TOP features to multi-resolution spatiotemporal space and use them for describing facial expressions. AdaBoost is utilized to learn the principal appearance and ...

In this paper, we present a novel rotation-invariant and computationally efficient texture descriptor called Dominant Rotated Local Binary Pattern (DRLBP). A rotation invariance is achieved by computing the descriptor with respect to a reference in a local neighborhood. A reference is fast to compute maintaining the computational simplicity of the Local Binary Patterns (LBP). The proposed appro...

We consider the Schur complement operation for symmetric matrices over GF(2), which we identify with graphs through the adjacency matrix representation. It is known that Schur complementation for such a matrix (i.e., for a graph) can be decomposed into a sequence of two types of elementary Schur complement operations: (1) local complementation on a looped vertex followed by deletion of that ver...

Feature extraction is a main step in all perceptual image hashing schemes in which robust features will led to better results in perceptual robustness. Simplicity, discriminative power, computational efficiency and robustness to illumination changes are counted as distinguished properties of Local Binary Pattern features. In this paper, we investigate the use of local binary patterns for percep...

In this work, we have proposed a learning paradigm for obtaining weight-optimal local binary patterns (WoLBP). We first reformulate the LBP problem into matrix multiplication with all the bitmaps flattened and then resort to the Fisher ratio criterion for obtaining the optimal weight matrix for LBP encoding. The solution is closed form and can be easily solved using one eigen-decomposition. The...

This paper introduces a shape descriptor based on a combination of topological image analysis and texture information. Critical points of a shape’s skeleton are determined first. The shape is described according to persistence of the local topology at these critical points over a range of scales. The local topology over scale-space is derived using the local binary pattern texture operator with...