Disguised face recognition is a major challenge in the field of face recognition which has been taken less attention. Therefore, in this paper a disguised face recognition algorithm based on Local Phase Quantization (LPQ) method and Singular Value Decomposition (SVD) is presented which deals with two main challenges. The first challenge is when an individual intentionally alters the appearance ...

The religion of Islam is based on a sacred text called Qur‟an, a divine speech expressed in Arabic language. Qur‟an constitutes the main root of Islam jurisprudence which has a second source of inspiration known as Hadiths. As the Muslim‟s life is governed by those holy texts, need of their authenticity is required. Using VSM (Vector Space Model), we can represent Hadiths as a vector of words. ...

Abstract: In this paper, we present results pertaining to two different extensions of vector quantization and the related question of k−means clustering. The first part of the paper is about the theoretical performance of quantization and clustering with Bregman divergences. The second one is dedicated to model selection issues for principal curves. Some numerical illustrations are provided in ...

In this paper we introduce a technique of tracking and quantizing the complex envelope of a narrowband process, which is a continuous time Gauss-Markov process of arbitrary order. The narrowband process is modeled in a state space framework and several quantization schemes using the inphase and the quadrature components of the narrowband process are considered. These inphase and quadrature comp...

Color quantization is an important technique in digital image processing. Generally it involves two steps. The first step is to choose a proper color palette. The second step is to reconstruct an image by replacing original colors with the most similar palette colors. However a problem exists while choosing palette colors. That is how to choose the colors with different illumination intensities...

We develop a new approach to vector quantization, which guarantees an intrinsic stationarity property that also holds, in contrast to regular quantization, for non-optimal quantization grids. This goal is achieved by replacing the usual nearest neighbor projection operator for Voronoi quantization by a random splitting operator, which maps the random source to the vertices of a triangle of d-si...