In this paper we presented a new approach to manipulate digital signal in order create features array, which can be used as signature retrieve the signal. Each is associated with local binary pattern (LBP) histogram; histogram will calculated based on LBP operator, then k-means clustering was generate required for each The proposed method implemented, tested and obtained experimental results we...

To aim at the challenge of face recognition to uncontrolled situations, robust face recognition system requires to take into account different kinds of face appearance feature. However, most existing methods only use features of just one type. We show that integrating two of global and local representations, Shearlets features and local binary pattern (LBP), which gets better performance than e...

A novel descriptor able to improve the classification capabilities of a typical pattern recognition system is proposed in this paper. The introduced descriptor is derived by incorporating two efficient region descriptors, namely image moments and Local Binary Patterns (LBP), commonly used in pattern recognition applications, in the last decades. The main idea behind this novel feature extractio...

Face spoofing is considered to be one of the prominent threats to face recognition systems. However, in order to improve the security measures of such biometric systems against deliberate spoof attacks, liveness detection has received significant recent attention from researchers. For this purpose, analysis of facial skin texture properties becomes more popular because of its limited resource r...

Many state-of-the-art face recognition algorithms use image descriptors based on features known as Local Binary Patterns (LBPs). While many variations of LBP exist, so far none of them can automatically adapt to the training data. We introduce and analyze a novel generalization of LBP that learns the most discriminative LBP-like features for each facial region in a supervised manner. Since the ...

This paper presents a way to classify between the nest image and the non-nest image. The input image is processed by Canny Edge Detection, and using Local Binary Pattern to extract the local textural features. K-means was applied to clustering LBP feature. And, dividing images into several blocks and finding out the dominant local textural features for describing the corresponding block. The pe...

In this paper, a novel parallelized implementation of rotation invariant texture classification using Heterogeneous Computing Platforms like CPU and Graphics Processing Unit (GPU) is proposed. A complete modeling of the LBP operator as well as its improvised versions of Complete Local Binary Patterns (CLBP) and Multi-scale Local Binary Patterns (MLBP) has been developed on a CPU and GPU based H...

Digital watermarking has rise as a new research area for preventing illicit copying and duplication. In this paper two methods 3-level DWT & Local Binary Pattern (LBP) algorithm for watermarking in digital images are discussed. In order to compare the robustness of both algorithms noise attack is used.

This paper proposes using soft histograms for the Local Binary Pattern (LBP) operator that has been widely applied in different image analysis tasks. This makes the operator more robust to noise and make its output continuous with respect to input. The proposed extension is shown to significantly enhance the performance of the operator with degraded images.

Previously, we proposed an efficient algorithm using vector quantization (VQ) histogram for facial image recognition in low-frequency DCT domains. In this paper, we newly utilize Local Binary Pattern (LBP) histogram in spatial domain. These two histograms, which contain both spatial and frequency domain information of a facial image, are utilized as a very effective personal feature. Publicly a...