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 this paper, we propose Local Binary Pattern Histogram Fourier features (LBP-HF), a novel rotation invariant image descriptor computed from discrete Fourier transforms of local binary pattern (LBP) histograms. Unlike most other histogram based invariant texture descriptors which normalize rotation locally, the proposed invariants are constructed globally for the whole region to be described. ...

Both the Local Binary Pattern (LBP) and the Coordinated Clusters Representation (CCR) are two methods used successfully in the classification and segmentation of images. They look very similar at first sight. In this work we analyze the principles of the two methods and show that the methods are not reducible to each other. Topologically they are as different as a sphere and a torus. In extract...

This paper presents a new method for facial expression recognition using divided local binary pattern features. Motivated by Fourier’s parity decomposition, we decompose a LBP descriptor into two subdescriptors. This method reduces the amount of data of the feature extraction, reducing the data dimension effectively. Experimental results on JAFFE facial expression database show that the propose...

In this paper, we propose a new type of local binary pattern (LBP)-based feature, called Rotation Invariant Co-occurrence among adjacent LBPs (RIC-LBP), which simultaneously has characteristics of rotation invariance and a high descriptive ability. LBP was originally designed as a texture description for a local region, called a micropattern, and has been extended to various types of LBP-based ...

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...