Point representation augmented to surface reconstruction in image-based VR

The ability to accurately predict natural backgrounds over a wide range of potential image acquisition conditions is key to wide-area change detection. The lack of robustness in pure image-based techniques has led to the development of site modeling and model-supported exploitation approaches. Instead of using multiple images to build a site model, we consider the possibility of using them directly to estimate the background of a new image for change detection. Our method uses a nonlinear mean-squared estimation technique to compute image backgrounds from multiple reference images. In comparing linear and nonlinear estimators, we find that although the performance of both improves as the number of reference images increases, the nonlinear estimator yields significantly better background estimates and is much less sensitive to registration errors between images than the linear estimator. We show that as the number of references increases, the pixels within a region become physically significant; i.e., they correspond to parts of the scene with similar physical properties. Synthetic aperture radar (SAR) background modeling and change detection results including a crosssensor change detection example in which SAR reference images are used to predict the background of an electro-optical (EO) image are presented. Significant performance gains over linear change detection (up to two orders of magnitude reduction in the false alarm rate) are demonstrated in each case over a 60-deg range of SAR sensor aspect angles.

An improved visually meaningful encrypted image scheme

Projector-based display systems have been used in area of computer interaction as Ad-hoc interface in recent time. The mobile hand-held projectors are becoming more popular. Many human centric user interfaces with the human wearable computer are being developed. Most of such system uses daily objects for projection and the interaction. But most of ignores the fact that these object surfaces are not planar. Hence such interfaces suffers from the distortion due to non-planar projection surface. Besides this projection quality also suffers from the radiometric distortion as well. Further more the interaction proposed with such interfaces bound to the planar surface only. Hence this paper is targeted to address the geometric distortion free projection of and interaction with such interfaces on non planar surfaces. Kinect is used as depth sensor for 3D scenario acquisition. We use image-per warping to mesh from Kinect. We use colored fingertip gloves for interaction. Here our system aims any day to day object surface for distortion free projection such as human body, curved wall, room corners, curtain's and many more objects.

Natural feeling color image fusion technology is an important direction in image processing.This paper first summarizes contributions from both domestic and foreign researchers.Then according to the theory of 2D color-lookup-table, it puts forwards the multiple reference images fusion algorithm, and gives the results of using two and three reference images.The comparing and analyzing of those results proves the validity of the algorithm.

The present communication addresses the reflection and transmission analysis of a two-dimensional waveguide structure with planar and non-planar surfaces. In the fields of physics, engineering and applied mathematics, research is being carried out to control or reduce unwanted and harmful noise to an acceptable level. Our aim is to solve the boundary value problem developed to simulate the transmission and reflection of a bifurcated waveguide structure in the channels or ducts that have abrupt changes in the height together with planar and non-planar surfaces. Furthermore, the eigenfunctions are linearly independent and non-orthogonal. To solve non-orthogonal eigenfunctions, a generalized orthogonality relation has been developed. Solution is obtained using mode matching technique (MMT) along with generalized orthogonal relations. In the last section, solution is viewed graphically in the inner and outer ducts or channels for different frequencies and height. The expressions for energy distribution in different duct regions are obtained and sketched subject to the various properties of the waveguide material. The results are well supported for a number of mathematical and physical reasons.

A new security system is proposed using optical joint transform correlation technique which employs multiple phase-shifted reference images. In the proposed technique, the address code is used as the reference image and fed into four channels after performing phase shifting on them by different amount. The output signals from each channel are added with the input image to be encrypted for security purpose. Joint power spectra (JPS) signals can then be derived by applying Fourier transformation, and the resultant signals are phase-shifted and combined to form a modified JPS signal. Inverse Fourier transformation of the modified JPS signal yields the encrypted image which is now secure from any unauthorized access and/or loss of information. For decryption purpose, the received encrypted signal is first Fourier transformed and multiplied by the address code used in encryption, which is then inverse Fourier transformed to generate the output signal. The proposed technique does not involve any complex mathematical operation on the address code otherwise required in other security techniques. The proposed technique requires a simple architecture and operates fast, automatic and is invariant to noise and distortions. Performance of the proposed scheme is investigated using computer simulation using binary as well as gray images in both noise-free and noisy conditions.

A characteristics of imbalanced points is their localities--an imbalanced point may be contiguous to some other imbalanced points in terms of 8-connectivity. A two-layer scheme was recently proposed for matching imbalanced points based on localities, where the first layer aims to build locality correspondence, and the second layer aims to build point correspondence within corresponding localities. Under the framework of the two-layer matching, we propose a hybrid representation of imbalanced points. Specifically, an imbalanced point in the first layer is represented by a discriminant SIFT-type descriptor, and in the second layer, the imbalanced point is simply represented by a patch-type descriptor (the intensities of its neighborhood). We will justify the rationale of the proposed hybrid representation scheme and show its superiority over nonhybrid representation with experiments.

A variety of DNA, protein or cell microarray devices and systems have been developed and commercialized. In addition to the biomolecule related analysis, they are also being used for pharmacogenomic research, infectious and genetic disease and cancer diagnostics, and proteomic and cellular analysis.1 Currently, microarray is fabricated on a planar surface; this limits the amount of biomolecules that can be bounded on the surface. In this work, a planar protein microarray chip with nonplanar spot surface was fabricated to enhance the chip performance. A nonplanar spot surface was created by first coating the silica nanoparticles with albumin and depositing them into the patterned microwells. The curve surfaces of the nanoparticles increase the surface area for immobilization of proteins, which helps to enhance the detection sensitivity of the chip. Using this technique, proteins are immobilized onto the nanoparticles before they are deposited onto the chip, and therefore the method of protein immobilization can be customized at each spot. Furthermore, a nonplanar surface promotes the retention of native protein structure better than planar surface.2 The technique developed can be used to produce different types of microarrays, such as DNA, protein and antibody microarrays.

Purpose: Integrating neuroradiology with neuroanatomy is essential in medical neuroeducation and neuroimage interpretation. To bridge 2D neuroradiology and 3D neuroanatomy, spatially correlated pairs of labeled images were employed, planar radiologic, and planar-surface combined. Research design: The method employs a 3D fully parcellated and labeled brain atlas extended to the head and neck with about 3000 3D components to create planar radiologic and surface neuroanatomic images. The atlas handles reformatted radiologic images as 3D objects using texture mapping which provides consistency with polygonal 3D neuroanatomic structures. This ensures a precise spatial correspondence of dual 2D-2D/3D images for any composed 3D scene reformatted in arbitrary orientation. The sequences of labeled dual images were created spanning a structure/system of interest in multiple orientations. To facilitate image searching, the image name encodes its content, orientation, and stereotactic location. Results: Labeled dual 2D-2D/3D neuroimage sequences in multiple orientations were created for the cerebrum, brainstem, deep nuclei, cerebral ventricles, intracranial arteries, dural sinuses, extracranial arteries, extracranial veins, trigeminal nerve, head muscles, glands, bones of cranium, and visual system. They all were hierarchically organized as a planar-surface gallery with 42 folders and 502 neuroimages. This gallery was integrated with a public NOWinBRAIN repository at www.nowinbrain.org with more than 7700 neuroimages. Conclusions: Owing to its advantages, simplicity, and free availability, this resource is useful for medical students, residents, educators, and clinicians to study the brain, head, and neck as well as to prepare presentations and teaching materials. The approach might potentially enhance image interpretation by integrating brain atlases with radiologic workstations.

In this work, we describe how to recover the perspective functions induced by the dominant faces of a rigid polyhedral scene captured by two cameras at different positions. The faces of any polyhedron can be dealt with as if they were planar surfaces, therefore we analyze this problem in a multi-planar scene context. We assume that the scene is populated with polyhedral objects and that a regular grid is imposed on the reference image. We describe a robust strategy that is able to merge patches that belong to the same planar surface and to impose the epipolar geometry constraints to the recovered perspective functions.

Irregularities at the {001} surface of MgO: Topography and other aspects

This paper proposes a real-time method to compute multiple scattering in non-homogeneous participating media having general phase functions. The volume represented by a particle system is supposed to be static, but the lights and the camera may move. Lights can be arbitrarily close to the volume and can even be inside. Real-time performance is achieved by reusing light scattering paths that are generated with global line bundles traced in sample directions in a preprocessing phase. For each particle we obtain those other particles which can be seen in one of the sample directions, and their radiances toward the given particle. This information is stored in an illumination network that allows the fast iteration of the volumetric rendering equation. The illumination network can be stored in two-dimensional arrays indexed by the particles and the directions, respectively. Interpreting these two-dimensional arrays as texture maps, the iteration of the scattering steps can be efficiently executed by the graphics hardware, and the illumination can spread over the media in real-time.

This paper considers image matching for objects with individual differences and deformations, such as the human face, and proposes the concept of probabilistic increment sign correlation (ISC) as a new statistic suited to the purpose. Probabilistic ISC is a statistic based on the probability of occurrence of incremental signs calculated from multiple reference images. Since matching is sought considering only the increase or decrease of the spatial brightness, it is less affected by changes of illumination and other factors. In matching, the variation of the incremental sign produced by changes of the object shape and other factors is represented by a probability, and high matching accuracy is achieved by assigning larger weights to features with smaller variation. The computation cost is as low as that of increment sign correlation, and the method is also suited to hardware implementation. It is possible to set the matching threshold analytically on the basis of statistical properties. In order to verify the effectiveness of the proposed method, an experiment was performed to detect a face from 2420 images, and higher detection accuracy was obtained than by methods based on correlation, such as normalized correlation and increment sign correlation, or the subspace method. © 2007 Wiley Periodicals, Inc. Syst Comp Jpn, 38(3): 12–22, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.20613

Environment maps, like texture maps or any other maps consisting of discretely stored data have to be properly filtered, if they are being resampled in the process of rendering an image. For environment maps, this is especially important, as the sampling rate is subject to extreme changes due to the curvature of the reflecting surfaces. However, for the same reason, the antialiasing is especially difficult to perform, as the sampling rate has to be determined for each pixel. We introduce a method to perform this calculation and determine the parameters for anisotropic filtering of the environment map. Instead of the BRDF, we employ roughness pyramids to account for the properties of the reflecting surface. The principles that are used to perform this antialiasing can be applied for antialiasing reflected textures in general e.g. in ray tracing.

This work proposes a new unsupervised steganalysis scheme which mainly tackles the challenge in identifying individual JPEG image as stego or cover. The proposed scheme does not need a large number of samples to train classification model, and thus it is significantly different from the existing supervised steganalysis schemes. The proposed scheme employs calibration technology to construct multiple reference images from one suspicious image. These reference images are considered as the imitation of cover. Furthermore, randomized sampling is performed to construct sub-image sets from suspicious image and reference images, respectively. By calculating the maximum mean discrepancy between any two sub-image sets, an efficient measure is provided to give the optimal decision on this suspicious image. Experimental results show that the proposed scheme is effective and efficient in identifying individual image, and outperforms the state-of-the-art steganalysis scheme.