In this paper, a new algorithm meant for object tracking application is proposed using local extrema patterns (LEP) and color features. The standard local binary pattern (LBP) encodes the relationship between reference pixel and its surrounding neighbors by comparing gray level values. The proposed method differs from the existing LBP in a manner that it extracts the edge information based on l...

The wavelet transform is one of the widely used transforms that proved to be very powerful in many applications, as it has strong localization ability in both frequency and space. In this paper, the 3D Stationary Wavelet Transform (SWT) is combined with a Local Binary Pattern (LBP) histogram to represent and describe the human actions in video sequences. A global representation is obtained and ...

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...

This paper presents a novel implementation of the “Local Binary Pattern” (LBP) texture analysis operator on a consumer-grade graphical processing unit (GPU), which yields a 14 to 18-fold run time reduction compared to standard CPU implementations. The obtained result allows the application of this powerful texture analysis method for tasks requiring both high resolution and real time performanc...

classical lbp such as complexity and high dimensions of feature vectors that make it necessary to apply dimension reduction processes. in this paper, we introduce an improved lbp algorithm to solve these problems that utilizes fast pca algorithm for reduction of vector dimensions of extracted features. in other words, proffer method (fast pca+lbp) is an improved lbp algorithm that is extracted ...

Despite progress in image retrieval by using low-level features, such as colors, textures and shapes, the performance is still unsatisfied as there are existing gaps between low-level features and high-level semantic concepts (semantic gaps). In this research, we propose a novel image retrieval system based on bag-of-features (BoF) model by integrating scale invariant feature transform (SIFT) a...

CBIR (Content based image retrieval) deals with the retrieval of same image from the databases of image by utilizing the feature vector extracted from the image and that features basically describes the visual content presented in the image, like the color, texture, shape and the spatial relation among vectors. Herein, the concept of LBP (Local binary pattern) is used for the comparative analys...

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...

Traditionally, iris recognition systems capture iris images in the 700 to 900nm range. It is within these ranges that researchers have found the most viable iris textures for iris recognition. Recently, there has been an interest for exploration of spectrum ranges that falls outside of these traditional ranges. In this work, we will explore the performance of feature extraction techniques on a ...

While features used for texture analysis have been successfully used in some biometric applications, only quite few works have considered them in facial image analysis. Texture-based region descriptors can be very useful in recognizing faces and facial expressions, detecting faces and different facial components, and in other face related tasks. This paper demonstrates this issue by considering...