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Synthetic Images (synthetic + image)

Distribution by Scientific Domains

Chemistry	33%

Selected Abstracts

Near-IR spectroscopic imaging for skin hydration: The long and the short of it

BIOPOLYMERS, Issue 2 2002
E. Michael Attas
Abstract Near-IR spectroscopic methods have been developed to determine the degree of hydration of human skin in vivo. Noncontact reflectance spectroscopic imaging was used to investigate the distribution of skin moisture as a function of location. A human study in a clinical setting has generated quantitative data showing the effects of a drying agent and a moisturizer on delineated regions of the forearms of eight volunteers. Two digital imaging systems equipped with liquid-crystal tunable filters were used to collect stacks of monochromatic images at 10-nm intervals over the 650,1050 and 960,1700 nm wavelength bands. Synthetic images generated from measurements of water absorption band areas at three different near-IR wavelengths (970, 1200, and 1450 nm) showed obvious differences in the apparent distribution of water in the skin. Changes resulting from the skin treatments were much more evident in the long-wavelength images than in the short-wavelength ones. The variable sensitivity of the method at different wavelengths has been interpreted as being the result of different penetration depths of the IR light used in the reflectance studies. © 2002 John Wiley & Sons, Inc. Biopolymers (Biospectroscopy) 67: 96,106, 2002 [source]

Projective Texture Mapping with Full Panorama

COMPUTER GRAPHICS FORUM, Issue 3 2002
Dongho Kim
Projective texture mapping is used to project a texture map onto scene geometry. It has been used in many applications, since it eliminates the assignment of fixed texture coordinates and provides a good method of representing synthetic images or photographs in image-based rendering. But conventional projective texture mapping has limitations in the field of view and the degree of navigation because only simple rectangular texture maps can be used. In this work, we propose the concept of panoramic projective texture mapping (PPTM). It projects cubic or cylindrical panorama onto the scene geometry. With this scheme, any polygonal geometry can receive the projection of a panoramic texture map, without using fixed texture coordinates or modeling many projective texture mapping. For fast real-time rendering, a hardware-based rendering method is also presented. Applications of PPTM include panorama viewer similar to QuicktimeVR and navigation in the panoramic scene, which can be created by image-based modeling techniques. Categories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Viewing Algorithms; I.3.7 [Computer Graphics]: Color, Shading, Shadowing, and Texture [source]

Representation of Pseudo Inter-reflection and Transparency by Considering Characteristics of Human Vision

COMPUTER GRAPHICS FORUM, Issue 3 2002
H. Matsuoka
We have succeeded in developing a quick and fully automated system that can generate photo-realistic 3D CG data based on a real object. A major factor in this success comes from our findings through psychophysical experiments that human observers do not have an accurate idea of what should be actually reflected as inter-reflections on the surface of an object. Taking advantage of this characteristic of human vision, we propose a new inter-reflection representation technique in which inter-reflections are simulated by allowing the same quantity of reflection components as there are in the background to pass through the object. Since inter-reflection and transparency are calculated by the same algorithm, our system can capture 3D CG data from various real objects having a strong inter-reflection, such as plastic and porcelain items or translucent glass and acrylic resin objects. The synthetic images from the 3D CG data generated with this pseudo inter-reflection and transparency look very natural. In addition, the 3D CG data and synthetic images are produced quickly at a lower cost. [source]

Model-based shape from shading for microelectronics applications

INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Issue 2 2006
A. Nissenboim
Abstract Model-based shape from shading (SFS) is a promising paradigm introduced by Atick et al. [Neural Comput 8 (1996), 1321,1340] in 1996 for solving inverse problems when we happen to have a lot of prior information on the depth profiles to be recovered. In the present work we adopt this approach to address the problem of recovering wafer profiles from images taken using a scanning electron microscope (SEM). This problem arises naturally in the microelectronics inspection industry. A low-dimensional model, based on our prior knowledge on the types of depth profiles of wafer surfaces, has been developed, and based on it the SFS problem becomes an optimal parameter estimation. Wavelet techniques were then employed to calculate a good initial guess to be used in a minimization process that yields the desired profile parametrization. A Levenberg,Marguardt (LM) optimization procedure has been adopted to address ill-posedness of the SFS problem and to ensure stable numerical convergence. The proposed algorithm has been tested on synthetic images, using both Lambertian and SEM imaging models. © 2006 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 16, 65,76, 2006 [source]

Using statistical image models for objective evaluation of spot detection in two-dimensional gels

PROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 6 2003
Mike Rogers
Abstract Protein spot detection is central to the analysis of two-dimensional electrophoresis gel images. There are many commercially available packages, each implementing a protein spot detection algorithm. Despite this, there have been relatively few studies comparing the performance characteristics of the different packages. This is in part due to the fact that different packages employ different sets of user-adjustable parameters. It is also partly due to the fact that the images are complex. To carry out an evaluation, "ground truth" data specifying spot position, shape and intensities needs to be defined subjectively on selected test images. We address this problem by proposing a method of evaluation using synthetic images with unambiguous interpretation. The characteristics of the spots in the synthetic images are determined from statistical models of the shape, intensity, size, spread and location of real spot data. The distribution of parameters is described using a Gaussian mixture model obtained from training images. The synthetic images allow us to investigate the effects of individual image properties, such as signal-to-noise ratios and degree of spot overlap, by measuring quantifiable outcomes, e.g. accuracy of spot position, false positive and false negative detection. We illustrate the approach by carrying out quantitative evaluations of spot detection on a number of widely used analysis packages. [source]

REVERSIBLE JUMP MARKOV CHAIN MONTE CARLO METHODS AND SEGMENTATION ALGORITHMS IN HIDDEN MARKOV MODELS

AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 2 2010
R. Paroli
Summary We consider hidden Markov models with an unknown number of regimes for the segmentation of the pixel intensities of digital images that consist of a small set of colours. New reversible jump Markov chain Monte Carlo algorithms to estimate both the dimension and the unknown parameters of the model are introduced. Parameters are updated by random walk Metropolis,Hastings moves, without updating the sequence of the hidden Markov chain. The segmentation (i.e. the estimation of the hidden regimes) is a further aim and is performed by means of a number of competing algorithms. We apply our Bayesian inference and segmentation tools to digital images, which are linearized through the Peano,Hilbert scan, and perform experiments and comparisons on both synthetic images and a real brain magnetic resonance image. [source]