We present a novel methodology that utilizes four-dimensional (4D) space deformation to simulate a magnification lens on versatile volume datasets and textured solid models. Compared with other magnification methods (e.g. geometric optics, mesh editing), 4D differential geometry theory and its practices are much more flexible and powerful for preserving shape features (i.e. minimizing angle dis...

Introduction: Compressed sensing (CS) MRI has been used to achieve satisfactory image reconstructions from fewer k-space samples as compared to traditional (i.e. Nyquist-sampled) methods [1]. To do this, CS relies on an assumption of transform sparsity of the image. However, if the signal is not strictly transform sparse, as is the case for most MR images, the mismatch between assumption and re...

Historically, Capacity Planning has delivered measurable value to the organization in the form of reduced costs, deferred acquisitions, and service level delivery, all of which deliver a Return on Investment (ROI) for the organization. However, fundamental changes in the underpinnings of the capacity planning ROI threaten the traditional value of capacity planning, and raise the question of whe...

This paper gives a short summary of work related to the creation of a department-hosted hand vein database. After the introducing section, special properties of the hand vein acquisition are explained, followed by a comparison table, which shows key differences to existing well-known hand vein databases. At the end, the ROI extraction process is described and sample images and ROIs are presented.

Taking a test during learning enhances later retention more than spending equivalent time restudying the same materials (Roediger & Karpicke, 2006). In the study, we first recorded participants’ eye movements in a paired-associate learning task while they were re-studying or tested for immediate cue recall. Testing prompted final item memory but not memory for its associated location. Participa...

Statistical colour models may be used to characterise regions of interest within images or sequences of images. In this work two types of model, one based on underlying Gaussian statistics and one using a Bingham distribution, are compared on both a theoretical and an experimental level. It is shown that when certain conditions hold, the Bingham model tends to have superior performance but that...

Introduction: Accurate film dosimetry requires careful consideration of sources of uncertainty. Some of the sources of uncertainty are dependent on the size and location of region of interest (ROI), especially in small fields. Avoiding the penumbra is often a reason for using a small ROI. In contrast, choosing very small ROIs may increase uncertainty due to the reduction of th...

This work reports and illustrates the application of enhancement techniques to images of nervous system from a confocal microscope. These images are processed to enhance regions of interest, e.g. nucleus and nervous terminations. Hidden information due to non-ideal acquisition must be exposed after processing, and errors such as non-uniform brightness, noise and artifacts must be eliminated.

Fall detection, especially for elderly people, is a challenging problem which demands new products and technologies. In this paper a fuzzy model for fall detection and inactivity monitoring in infrared video is presented. The classification features proposed include geometric and kinematic parameters associated with more or less sudden changes in the tracked human-related regions of interest. A...

This paper presents a methodology for localization of manmade objects in complex scenes by learning multiple feature models in images. The methodology is based on a modular structure consisting of multiple classifiers, each of which solves the problem independently based on its input observations. Each classifier module is trained to detect manmade object regions and a higher order decision int...