In this chapter, we propose two novel and curvature-free features: run-lengths of Local Binary Pattern (LBPruns) and Cloud Of Line Distribution (COLD) features for writer identification. The LBPruns is the joint distribution of the traditional run-length and local binary pattern (LBP) methods, which computes the run-lengths of local binary patterns on both binarized images and gray scale images...

This paper presents two novel ways of extending the local binary pattern (LBP) texture analysis operator to multiple scales. First, large-scale texture patterns are detected by combining exponentially growing circular neighborhoods with Gaussian low-pass filtering. Second, cellular automata are proposed as a way of compactly encoding arbitrarily large circular neighborhoods. The performance of ...

In this paper we present a method for objects tracking in images sequence. This approach is achieved into two main steps. In the first one, we constructed the Local Binary Pattern (LBP) histogram pattern of each image in the sequence and the reference pattern. In the second one, we perform the algorithm by the pattern selected based on a distance measures to find similarity between two histogra...

Local or global rotation invariant feature extraction has been widely used in texture classification. Local invariant features, e.g. local binary pattern (LBP), have the drawback of losing global spatial information, while global features preserve little local texture information. This paper proposes an alternative hybrid scheme, globally rotation invariant matching with locally variant LBP tex...

In this paper, a new image indexing and retrieval algorithm using multiresolution directional binary code (DBC) co-occurrence matrix is proposed. DBC histogram captures only the patterns distribution in a texture while the spatial correlation between the pair of patterns is gathered by DBC Co-occurrence. Multi-resolution texture decomposition and co-occurrence calculation has been efficiently u...

ELECT A local binary pattern (LBP)-based tracking algorithm and a novel heterogeneous vision chip architecture that implements the algorithm in high speed are proposed. The algorithm is more robust than previously reported high-speed tracking algorithms. The proposed vision chip architecture adopts multiple levels of parallel processors to execute the algorithm in pixel-parallel and patch-paral...

In this chapter, we propose two novel and curvature-free features: run-lengths of Local Binary Pattern (LBPruns) and Cloud Of Line Distribution (COLD) features for writer identification. The LBPruns is the joint distribution of the traditional run-length and local binary pattern (LBP) methods, which computes the run-lengths of local binary patterns on both binarized images and gray scale images...

In a Local Binary Pattern (LBP) representation, circular point features are taken in their entirety as predicates and restricted to uniform patterns with limited scales of small numbers of features in order to avoid large bin complexity. Such a design cannot fully exploit the discriminative capacity of the features available. To address the problem, this paper proposes (1) a pairwise-coupled re...

This paper presents a novel method for hierarchically organizing large face databases, with application to efficient identity-based face retrieval. The method relies on metric learning with local binary pattern (LBP) features. On one hand, LBP features have proved to be highly resilient to various appearance changes due to illumination and contrast variations while being extremely efficient to ...

More and more attention has been paid to the invariant texture analysis, because the training and testing samples generally have not identical or similar orientations, or are not acquired from the same viewpoint in many practical applications, which often has negative influences on texture analysis. Local binary pattern (LBP) has been widely applied to texture classification due to its simplici...