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This paper investigates a diffeomorphic point-set registration based on non-stationary mixture models. The goal is to improve the non-linear registration of anatomical structures by representing each point as a general non-stationary kernel that provides information about the shape of that point. Our framework generalizes work done by others that use stationary models. We achieve this by integrating...
Handwritten signatures are one of the most widely used biometrics, particularly in financial and legal transactions. Offline Signature verification is still one of the most challenging problems in biometrics. In this study, we have evaluated the performance of different classifiers for offline signature verification based upon local binary patterns feature set. The feature vector is formed by dividing...
A new high performance architecture for the computation of all the DCT operations adopted in the H.264/AVC and HEVC standards is proposed in this paper. Contrasting to other dedicated transform cores, the presented multi-standard transform architecture is supported on a completely configurable, scalable and unified structure, that is able to compute not only the forward and the inverse 8×8 and 4×4...
In this paper we describe a novel method of feature detection and classification using the maximal response of a set of spherical quadrature filters to either a line-segment or wedge-segment signal type. This is achieved via a rotation and illumination invariant distance function. The development of the method is described, and some experimental results are provided to demonstrate the usefulness of...
Partial Least Squares are introduced to build the response surface for multi-collinearity problems, which can effectively work on the problems of small sized samples and multiple correlations. However, this approach is a linear method, which is not capable to deal with the non-linear response surface model. To solve this problem, in this paper, we propose two improved algorithms called Local Partial...
A robust region-based weighted Hough Transform method for the detection of straight lines in poor quality images of building facades is presented in this work. Following a typical preprocessing stage that includes color to grayscale transformation, binarization using Otsu's automatic threshold selection method, morphological opening and decomposition into connected regions a minimum bounding rectangle...
The objective of the present paper is to give a summary of the theory of the bifrequency analysis for the class of linear time-varying (LTV) systems. The emphasis is on the frequency characterization of dynamic systems using the classical two-dimensional Laplace transform (2DLT). The merit of this powerful technique, which has not sufficiently been explored, is illustrated by examples.
Multicore processors are becoming ubiquitous in embedded systems. To take advantage of multicore processor, a great number of previously designed embedded applications need reengineering processes before they are ported to run accurately and efficiently. Massive refactoring of sequential programs to multi-thread programs is required. Parallelisation refactoring is generally implemented by programmers...
The Census Transform is one of the most widely used matching metrics in problems that involve correspondence search such as stereo reconstruction and optical flow. Graphic processing units (GPUs) have become popular platforms for such computation intensive applications that expose a high degree of data parallelism. Their evolution as a platform for general purpose computing by continuously adding...
This paper addresses the problem of image alignment using direct intensity-based methods for affine and homography transformations. Direct methods often employ scale-space smoothing (Gaussian blur) of the images to avoid local minima. Although, it is known that the isotropic blur used is not optimal for some motion models, the correct blur kernels have not been rigorously derived for motion models...
Many blind motion deblur methods model the motion blur as a spatially invariant convolution process. However, motion blur caused by the camera movement in 3D space during shutter time often leads to spatially varying blurring effect over the image. In this paper, we proposed an efficient two-stage approach to remove spatially-varying motion blurring from a single photo. There are three main components...
This paper describes a new family of linear transforms for data restricted to the surface of a 2-sphere in three-dimensional Fourier space. These transforms generalize the existing Funk-Radon Transform, which has previously been used with great success to extract microstructural tissue orientation information from high angular resolution magnetic resonance diffusion imaging data. Several properties...
The Non-Uniform Fast Fourier Transform (NUFFT) is a generalization of FFT to non-equidistant samples. It has many applications which vary from medical imaging to radio astronomy to the numerical solution of partial differential equations. Despite recent advances in speeding up NUFFT on various platforms, its practical applications are still limited, due to its high computational cost, which is significantly...
Kernel method is an effective technique in extracting nonlinear discriminative features. In this paper, we propose a new color face image recognition approach based on kernel holistic orthogonal analysis (KHOA) of discriminant transforms. Original color face images are mapped to high dimensional feature space by kernel function, then extract discriminant transforms of red, green, blue color image...
This paper proposes a recursive-structure and hardware-efficient filterbank design for modified discrete sine transform (MDST) and inverse MDST (IMDST) computations. The proposed algorithm can be derived to obtain a common computation, the type-IV of Discrete Sine Transform (DST-IV), and then can be converted into a recursive structure of the modified type-II of inverse discrete sine transform (Modified...
Data smoothing is an important step within a data processing procedure that allows one to stress the most important pattern of a function relation between a studied object and given variables. Recently, Holčapek and Tichý (2011) suggested a smoothing filter based on fuzzy transform approach of Perfilieva (2004) and compared it to Nadaraya-Watson estimator. However, within the analysis only one independent...
A gap exists between virtual reality (VR) software platforms designed for optimum hardware abstraction and cluster support, and those designed for efficient content authoring and exploration of interaction techniques through prototyping. This paper describes VR JuggLua, a high-level virtual reality application framework based on combining Lua, a dynamic, interpreted language designed for embedding...
Temporal pitch class profiles - commonly referred to as a chromagrams - are the de facto standard signal representation for content-based methods of musical harmonic analysis, despite exhibiting a set of practical difficulties. Here, we present a novel, data-driven approach to learning a robust function that projects audio data into Tonnetz-space, a geometric representation of equal-tempered pitch...
Face representation, including both feature extraction and feature selection, is the key issue for a successful face recognition system. In this paper, we propose a novel face representation scheme based on nonsubsampled contourlet transform (NSCT) and block-based kernel Fisher linear discriminant (BKFLD). NSCT is a newly developed multiresolution analysis tool and has the ability to extract both...
Semi-supervised classification from pairwise constraints is a challenge in pattern recognition, since the constraints just represent the relationships between data pairs rather than the definite labels. In the last few years, several methods have been proposed, however, they still utilize either the discriminability within the constraints or the abundant unlabeled data insufficiently. In this paper,...
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