In this paper we present a novel approach for automatic recognition of ring worm skin disease based on LBP (Local Binary Pattern) feature extracted from the affected skin images. The proposed method is evaluated by extensive experiments on the skin images collected from internet. The dataset is tested using three different classifiers i.e. Bayesian, MLP and SVM. Experimental results show that t...

Textures play an important role in recognition of images. This paper investigates the efficiency of performance of three texture based feature extraction methods for face recognition. The methods for comparative study are Grey Level Co_occurence Matrix (GLCM), Local Binary Pattern (LBP) and Elliptical Local Binary Template (ELBT). Experiments were conducted on a facial expression database, Japa...

Recent methods for learning similarity between images have presented impressive results in the problem of pair matching (same/notsame classification) of face images. In this paper we explore how well this performance carries over to the related task of multi-option face identification, specifically on the Labeled Faces in the Wild (LFW) image set. In addition, we seek to compare the performance...

Extracting an effective facial feature representation is the critical task for automatic expression recognition system. Local Binary Pattern (LBP) known to be a popular texture recognition. However, only few approaches utilize relationship between local neighborhood pixels itself. This paper presents Hybrid Texture Descriptor (HLTD) which derived from logical fusion of Neighborhood XNOR Pattern...

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 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...

While features used for texture analysis have been successfully used in some biometric applications, only quite few works have considered them in facial image analysis. Texture-based region descriptors can be very useful in recognizing faces and facial expressions, detecting faces and different facial components, and in other face related tasks. This paper demonstrates this issue by considering...

In this paper, a personal verification method using finger vein is presented. Finger vein can be considered more secured compared to other hands based biometric traits such as fingerprint and palm print because the features are inside the human body. In the proposed method, a new texture descriptor called local line binary pattern (LLBP) is utilized as feature extraction technique. The neighbou...

The approaches proposed for color texture discrimination can be divided into two types: 1) color and texture information are processed separately, and 2) spatial interactions of pixels both within and between color bands are considered. In this paper, we briefly review recent research and propose an approach based on separate processing of complementary color and pattern information. Color hist...

The methods of facial expression feature extraction based on traditional LBP have some drawbacks such as complexity, high dimension of feature vectors, which may reduce the efficiency of subsequent recognition process. To solve the above problems, this paper proposes an improved LBP algorithm——FastLBP(FLBP). FLBP compresses the feature vectors described by LBP histogram to decrease the complexi...