It is well recognized that image representation is the most fundamental task of the face recognition, effective and efficient image feature extraction not only has small intraclass variations and large interclass similarity but also robust to the impact of pose, illumination, expression and occlusion. This paper proposes a new local image descriptor for face recognition, named Log–Gabor Weber d...

In this paper, we introduce BoSP (Bonn Salient Points), a method comprising a pair of a keypoint detector and descriptor in image data that are deeply geared to one another. Our detector identifies points of interest to be local maxima of appearance contrast to their surroundings in a statistical manner. This criterion admits a selection of particularly repeatable, but diverse looking keypoints...

Local photometric descriptors are a crucial low level component of numerous computer vision algorithms. In practice, these descriptors are constructed to be invariant to a class of transformations. However, the development of a descriptor that is simultaneously robust to noise and invariant under general deformation has proven difficult. In this paper, we introduce the Topological-Attributed Re...

Despite the significant success of using local feature descriptor with many applications such as, face detection, human facial expression recognition, gender classification, signature verification, etc. Based on our knowledge, there is no research present on the usage of the descriptor to solve the stereo corresponding problem. Despite this, descriptor uses the same methodology for comparing th...

Abstrct The detection of ground plane and free space remains challenging for non-flat plane, especially with the varying latitudinal and longitudinal slope or in the case of multi-ground plane. In this paper, we propose a framework of the ground plane detection with stereo vision. The main contribution of this paper is a newly proposed descriptor which is implemented in the disparity image to o...

In this paper we propose a novel texture recognition feature called Fractal Weighted Local Binary Pattern (FWLBP). It has been observed that fractal dimension (FD) measure is relatively invariant to scale-changes, and presents a good correlation with human perception of surface roughness. We have utilized this property to construct a scale-invariant descriptor. We have sampled the input image u...

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...

Automatic recognition of facial expression is an active research topic in computer vision due to its importance in both human-computer and social interaction. One of the critical issues for a successful facial expression recognition system is to design a robust facial feature descriptor. Among the different existing methods, the Local Binary Pattern (LBP) has been proved to be a simple and effe...

This paper presents a novel binary descriptor Boosted Local Binary (BLB) for object detection. The proposed descriptor encodes variable local neighbour regions in different scales and locations. Each region pair of the proposed descriptor is selected by the RealAdaBoost algorithm with a penalty term on the structural diversity. As a result, confident features that are good at describing specifi...

This paper proposes an augmented version of local feature that enhances the discriminative power of the feature without affecting its invariance to image deformations. The idea is about learning local features, aiming to estimate its semantic, which is then exploited in conjunction with the bag of words paradigm to build an augmented feature descriptor. Basically, any local descriptor can be ca...