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 ...

Recently, spoof detection has become an important and challenging topic in iris recognition. Based on the textural differences between the counterfeit iris images and the live iris images, we propose an efficient method to tackle this problem. Firstly, the normalized iris image is divided into sub-regions according to the properties of iris textures. Local binary patterns (LBP) are then adopted...

In this work, we introduce a new fusion framework for multispectral face recognition in the textures space. Active and passive infrared imaging modalities are used and comparison with visible face recognition is performed. The proposed texture space is based on the use of LBP (Local Binary Pattern) and LTP (Local Ternary Pattern) techniques. Also, a new adaptive texture descriptor is presented....

The image space, scale and orientation domains can give valuable clues not seen in either individual of the domains. First we decomposed the face image into different orientation and scale by Gabor filter. Second, we combine local binary pattern analysis with Gabor. It gives a good face representation for recognition. Then we classify in discriminant based up on median histogram distance. The f...

The French National Library (BnF∗) has launched many mass digitization projects in order to give access to its collection. The indexation of digital documents on Gallica (digital library of the BnF) is done through their textual content obtained thanks to service providers that use Optical Character Recognition softwares (OCR). OCR softwares have become increasingly complex systems composed of ...

The face of a human being conveys extensive information about the identity and emotional state of the person. However, the most important phase in face recognition is extraction. In which the most useful and unique features of the face image are extracted. The Center-Symmetric Local binary Pattern (CS-LBP) feature can be viewed a combination of the texture-based feature and the gradient-based f...

One of the most common signs of tiredness or fatigue is yawning. Naturally, identification of fatigued individuals would be helped if yawning is detected. Existing techniques for yawn detection are centred on measuring the mouth opening. This approach, however, may fail if the mouth is occluded by the hand, as it is frequently the case. The work presented in this paper focuses on a technique to...

This research Paper represents a recent use of the extended local binary pattern for face recognition. Extended Local Binary Pattern (ELBP) Technique is more accurate and describes the texture and shape of a digital image by using of 3*3 & 5*5 matrices we have to compare the performance of both matrices so that how we recognize the image. Variance help to measure continuous output where the qua...

The local binary pattern (LBP) provides a simple and efficient approach to gray-scale and rotation invariant texture classification. However, the LBP operator thresholds P neighbors at the value of the center pixel in a local neighborhood and employs a P-bit binary pattern to encode only the signs of the differences between the gray values. Thus, the LBP operator discards some important texture...

To accomplish face recognition more efficiently, a distributed face recognition framework based on MB-LBP features and data fusion is presented in this paper. Firstly, four face regions are interactively marked and the Multi-scale Block Local Binary Patterns are extracted from these regions to achieve both locally and globally informative features. Secondly, a distributed framework is introduce...