Local Binary Pattern (LBP) are considered as a classical descriptor for texture analysis, it has mostly been used in pattern recognition and computer vision applications. However, the LBP gets information from restricted number of local neighbors which is not enough to describe information, other descriptors that get large suffer dimensionality consume much time. In this regard, we propose nove...

Binary descriptors have been very popular in recent years due to their computation and memory efficient capabilities. Many of them could deal with geometrical variations and linear intensity shifts, however, they were not examined for more complex brightness changes specifically, which might result of some internal conditions such as nonlinear camera capturing parameters or external conditions ...

Binary descriptors of image patches are increasingly popular given that they require less storage and enable faster processing. This, however, comes at a price of lower recognition performances. To boost these performances, we project the image patches to a more discriminative subspace, and threshold their coordinates to build our binary descriptor. However, applying complex projections to the ...

In this letter, we propose a novelbinary graph descriptor to improve loop detection for visual SLAM systems. Our contribution is twofold: i) embedding technique generating binary descriptors which conserve both spatial and histogram information extracted from images; ii) generic mean of combining multiple layers heterogeneous data into the proposed descriptor, coupled with matching geometric ch...

In this paper, we propose Local Binary Pattern Histogram Fourier features (LBP-HF), a novel rotation invariant image descriptor computed from discrete Fourier transforms of local binary pattern (LBP) histograms. Unlike most other histogram based invariant texture descriptors which normalize rotation locally, the proposed invariants are constructed globally for the whole region to be described. ...

In this paper, we are evaluating several accelerating techniques for content-based image retrieval, suitable for the Color and Edge Directivity Descriptor (CEDD). To date, the experimental results presented in the literature have shown that the CEDD achieves high rates of successful retrieval in benchmark image databases. Although its storage requirements are minimal, only 54 bytes per image, t...

This paper introduces a shape descriptor based on a combination of topological image analysis and texture information. Critical points of a shape’s skeleton are determined first. The shape is described according to persistence of the local topology at these critical points over a range of scales. The local topology over scale-space is derived using the local binary pattern texture operator with...

In this paper, we present a tracking technique utilizing a simple saliency visual descriptor. Initially, we define a visual descriptor named local similarity pattern that mimics the famous texture operator local binary patterns. The key difference is that it assigns each pixel a code based on the similarity to the neighbouring pixels. Later, we simplify this descriptor to ...

With the explosive growth of web multimedia data, how to manage and retrieval the web-scale data more efficiently has become a urgent problem, which expects more efficient low-level feature with low computation. This pressing need brings a huge challenge to the conventional feature. It is urgent to make descriptor more compact and faster and meanwhile remain robust to many different kinds of im...

Facial expression recognition (FER) is a crucial technology and a challenging task for human–computer interaction. Previous methods have been using different feature descriptors for FER and there is a lack of comparison study. In this paper, we aim to identify the best features descriptor for FER by empirically evaluating five feature descriptors, namely Gabor, Haar, Local Binary Pattern (LBP),...