Effective and real-time face detection has been made possible by using the method of rectangle Haar-like features with AdaBoost learning since Viola and Jones’ work [12]. In this paper, we present the use of a new set of distinctive rectangle features, called Multi-block Local Binary Patterns (MB-LBP), for face detection. The MB-LBP encodes rectangular regions’ intensities by local binary patte...

The local binary pattern operator is an image operator which transforms an image into an array or image of integer labels describing small-scale appearance of the image. These labels or their statistics, most commonly the histogram, are then used for further image analysis. The most widely used versions of the operator are designed for monochrome still images but it has been extended also for c...

Effectiveness of local binary pattern (LBP) for face recognition has been proven. But the weight of weighted LBP is difficult to determine. In this paper, we proposed a biologically plausible approach to set the weight automatically. Combining LBP and visual attention, a weight map can be constructed by summing over the saliency map. The weight map outlines salient information in the image and ...

In this paper, we propose a new finger biometric method. Infrared finger images are first captured, and then feature extraction is performed using a modified gaussian high-pass filter through binarization, local binary pattern (LBP), and local derivative pattern (LDP) methods. Infrared finger images include the multimodal features of finger veins and finger geometries. Instead of extracting eac...

Measurement of visual quality is of fundamental importance for numerous image and video processing applications. This paper presented a novel and concise reduced reference (RR) image quality assessment method. Statistics of local binary pattern (LBP) is introduced as a similarity measure to form a novel RR image quality assessment (IQA) method for the first time. With this method, first, the te...

In this paper, we propose a simple and robust local descriptor, called the robust local binary pattern (RLBP). The local binary pattern (LBP) works very successfully in many domains, such as texture classification, human detection and face recognition. However, an issue of LBP is that it is not so robust to the noise present in the image. We improve the robustness of LBP by changing the coding ...

This work proposes a new formulation of the objects modeling combining geometry and appearance. The object local appearance location is referenced with respect to an invariant which is a geometric landmark. The appearance (shape and texture) is a combination of Harris-Laplace descriptor and local binary pattern (LBP), all is described by the invariant local appearance model (ILAM). We applied t...

This paper presents a novel face and periocular biometric fusion at feature level using canonical correlation analysis. Face recognition itself has limitations such as illumination, pose, expression, occlusion etc. Also, periocular biometrics has spectacles, head angle, hair and expression as its limitations. Unimodal biometrics cannot surmount all these limitations. The recognition accuracy ca...

Nowadays pedestrian detection plays a crucial role in image or video retrieval, video monitoring systems and driving assistance systems. Detecting moving pedestrians is a challenging task, some of the detection methods are ineffective and slow. Occlusion, rotation, changes in object shapes, real time detection and illumination conditions are predominant obstacles. This paper is focus on the imp...

This paper presents a novel approach for texture classification, generalizing the well-known local binary patterns (LBP). In the proposed approach, a local binary pattern (LBP) operator offers a systematic way of analyzing textures. It has a simple theory and combines properties of structural and statistical texture analysis methods. LBP approach is used to find crowd density. This approach est...