This paper presents a novel pattern based feature descriptor named as Local Differential Excitation Binary Cooccurrence Pattern (LDEBCoP) for texture and biomedical image retrieval. The proposed method exploits the local structure information using differential excitation. Further, to produce more compact local binary patterns the adjacent neighbourhood pixel pairs are considered in the computa...

In this paper we propose a new approach for learning local descriptors for matching image patches. It has recently been demonstrated that descriptors based on convolutional neural networks (CNN) can significantly improve the matching performance. Unfortunately their computational complexity is prohibitive for any practical application. We address this problem and propose a CNN based descriptor ...

Iris recognition is well suited to authentication on mobile devices, due to its intrinsic security and non-intrusiveness. However, authentication systems can be easily tricked by attacks based on high-quality printing. A liveness detection module is therefore necessary. Here, we propose a fast and accurate technique to detect printed-iris attacks based on the local binary pattern (LBP) descript...

Binary descriptors have been instrumental in the recent evolution of computationally efficient sparse image alignment algorithms. Increasingly, however, the vision community is interested in dense image alignment methods, which are more suitable for estimating correspondences from high frame rate cameras as they do not rely on exhaustive search. However, classic dense alignment approaches are s...

We present a novel face representation based on locally adaptive regression kernel (LARK) descriptors [1]. Our LARK descriptor measures a self-similarity based on “signal-induced distance” between a center pixel and surrounding pixels in a local neighborhood. By applying principle component analysis (PCA) and a logistic function to LARK consecutively, we develop a new binary-like face represent...

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....

In this paper, we represent (moving) point configurations along a curved directed line qualitatively by means of system relational symbols based on two distance descriptors: one representing the and other signed orthogonal to line. The represents direction movement interest. For instance, it could be straight as in case driving highway or an intersection roundabout. Inspired Point Calculus, ord...

Local Binary Pattern (LBP) is a very efficient local descriptor for describing image texture. In this paper, we propose a novel face recognition technique based on wavelet transform and the least square estimator to enhance the classical LBP. First, Wavelet transform is used to decompose a given image into four kinds of frequency images from which the features of that image can be extracted. Th...

Despite the progress made in the area of local image descriptors in recent years, virtually no literature is available on the use of more recent descriptors for the problem of 3D face recognition, such as BRIEF, ORB, BRISK or FREAK, which are binary in nature and, therefore, tend to be faster to compute and match, while requiring significantly less memory for storage than, for example, SIFT or ...