Shaded Images Research Articles

Measurement of plaque‐forming macrophages activated by lipopolysaccharide in a micro‐channel chip

In the present study, micro-channel arrays were fabricated on the surface of plastic-based disposable chips. The cell adhesion process and the detection of plaque-forming macrophages were observed. Further, we evaluated cell adhesion in a fluid system in vitro. Features of the micro-channel (1.4 mm wide and 10 mm long) included twenty micro-pillars (with a projection of 200 microm diameter and 250 microm high) coated in a 50 microm thick silicon rubber layer, which were regularly arranged at the bottom of each channel. The efficiency of cell capture was expected to increase by arrangement of micro-pillars in a micro-channel. Mouse macrophage RAW264.7 cells, stimulated for 24 h with lipopolysaccharide (LPS) derived from periodontopathic bacteria, were circulated continuously for 2 h at room temperature by the pump in a chip. Control cells had not formed plaques on micro-pillars 20 min into the experiment. By contrast, LPS-activated macrophages produced plaques at the side walls of micro-pillars after 20 min. The plaques grew during the flow test, and image shading became clearer with increasing flow time for 120 min. The maximal adhesion rate per unit area appeared at 20% for control cells, whereas the peak was shifted to 30% for LPS-activated macrophages (n = 20). The average adhesion rate was 3.0 +/- 2.0% for control cells and 5.0 +/- 3.9% for LPS-activated macrophages (n = 100). These findings indicate that LPS-activated macrophages accumulate in micro-channel arrays, and suggest that macrophage plaque formation is a two-step procedure: (1) LPS-activated macrophages adhere physically to the silicon rubber layer on micro-pillars; and (2) consequently, the cells adhere to the activated macrophage layer.

Real-Time Machinability Analysis of Free Form Surfaces on the GPU

In this paper a new hardware accelerated method is presented to evaluate the machinability of free-form surfaces. This method works on tessellated models that are commonly used by computer aided design (CAD) systems to render three-dimensional shaded images of solid models. Modern graphics processing units (GPUs) can be programed in hardware to accelerate specialized rendering techniques. In this research, we have developed new algorithms that utilize the programmability of GPUs to evaluate the machinability of free-form surfaces. The method runs in real-time on fairly inexpensive hardware (<$600), and performs well regardless of the surface type. The complexity of the method is dictated by the size of the projected view of the model. The proposed method can be used as a plug-in in a CAD system to evaluate the manufacturability of a part at early design stages. The efficiency and the speed of the proposed method are demonstrated on some complex objects.

Shape from Shading Using Probability Functions and Belief Propagation

Shape-from-shading (SFS) aims to reconstruct the three-dimensional shape of an object from a single shaded image. This article proposes an improved framework based on belief propagation for computing SFS. The implementation of the well-known brightness, integrability and smoothness constraints inside this framework is shown. We implement the constraints as probability density functions. For example, the brightness constraint is a two-dimensional probability density function that relates all possible surface gradients at a pixel to their probability given the pixel intensity. A straightforward extension of the framework to photometric stereo is presented, where multiple images of the same scene taken under different lighting conditions are available. The results are promising, especially since the solution is obtained by iteratively applying simple operations on a regular grid of points. The presented framework therefore can be implemented in parallel and is a reasonably likely biological scheme.

Edge detection in digital images using fuzzy numbers

The purpose of this paper is to introduce a new approach for edge detection in grey shaded images. The proposed approach is based on the fuzzy number theory. The idea is to deal with the uncertainties concerning the grey shades making up the image and, thus, calculate the appropriateness of the pixels in relation to a homogeneous region around them. The pixels not belonging to the region are then classified as border pixels. The results have shown that the technique is simple, computationally efficient and with good results when compared with both the traditional border detectors and the fuzzy edge detectors.

A perceptually validated model for surface depth hallucination

Capturing detailed surface geometry currently requires specialized equipment such as laser range scanners, which despite their high accuracy, leave gaps in the surfaces that must be reconciled with photographic capture for relighting applications. Using only a standard digital camera and a single view, we present a method for recovering models of predominantly diffuse textured surfaces that can be plausibly relit and viewed from any angle under any illumination. Our multiscale shape-from-shading technique uses diffuse-lit/flash-lit image pairs to produce an albedo map and textured height field. Using two lighting conditions enables us to subtract one from the other to estimate albedo. In the absence of a flash-lit image of a surface for which we already have a similar exemplar pair, we approximate both albedo and diffuse shading images using histogram matching. Our depth estimation is based on local visibility. Unlike other depth-from-shading approaches, all operations are performed on the diffuse shading image in image space, and we impose no constant albedo restrictions. An experimental validation shows our method works for a broad range of textured surfaces, and viewers are frequently unable to identify our results as synthetic in a randomized presentation. Furthermore, in side-by-side comparisons, subjects found a rendering of our depth map equally plausible to one generated from a laser range scan. We see this method as a significant advance in acquiring surface detail for texturing using a standard digital camera, with applications in architecture, archaeological reconstruction, games and special effects.

Shading extraction and correction for scanned book images

When one scans document pages from a bound book, shading artifacts are commonly occurred in the book spine area. In this letter, we propose a general-purpose method for image shading correction based on an assumption that the reflectance function of the page surface is piecewise constant and the illumination function is smooth. The proposed method is able to completely correct more general types of shading artifacts which are nonuniformly distributed along the book spine. Comparison experiments on a synthetic and a variety of real scanned book images demonstrate the feasibility and effectiveness of the proposed method.

Spatial autocorrelation and mean intercept length analysis of trabecular bone anisotropy applied to in vivo magnetic resonance imaging

Osteoporosis is characterized by bone loss and deterioration of the trabecular bone (TB) architecture that leads to impaired overall mechanical strength of the bone. Bone mineral density (BMD) measured by dual-energy x-ray absorptiometry is currently the standard clinical metric assessing bone integrity but it fails to capture the structural changes in the TB. Recent research suggests that structure contributes to bone strength in a manner complementary to BMD. Besides parameters of scale such as the mean TB thickness and mean bone volume fraction, parameters describing the anisotropy of the trabecular architecture play an important role in the characterization of TB since trabeculae are preferentially oriented along the direction of local loading. Therefore, the degree of structural anisotropy is of pivotal importance to the bone's mechanical competence. The most common method for measuring structural anisotropy of TB is the mean-intercept length (MIL). In this work we present a method, based on the three-dimensional spatial autocorrelation function (ACF), for mapping of the full structural anisotropy ellipsoid of both TB thickness and spacing and we examine its performance as compared to that of MIL. Not only is the ACF method faster by several orders of magnitude, it is also considerably more robust to noise. Further, it is applicable at lower spatial resolution and is relatively insensitive to image shading. The chief reason for ACF's superior performance is that it does not require binarization, which is difficult to achieve in the limited spatial regime of in vivo magnetic resonance imaging. MIL and ACF have been applied to high-resolution magnetic resonances images of the tibia in a group of ten healthy postmenopausal women by comparing the structural anisotropy and principal direction of the computed fabric tensor for each method. While there is fair agreement between the two methods, ACF analysis yielded greater anisotropy than MIL for both TB thickness and spacing. There was good agreement between the two techniques as far as the eigenvectors of the fabric ellipsoids were concerned, which parallel the bone's macroscopic axis.

Combining estimators for Monte Carlo volume rendering with shading

Monte Carlo volume rendering (MCVR), which allows for generating X-ray like images, offers significant advantages over existing volume rendering techniques in terms of time and memory complexity. The classical shading for MCVR, however, results in a low quality image. In this paper, a so-called estimators combining technique is presented that estimates a realistic rendering using the Lambertian reflection illumination model. Such a technique is particularly adapted to changes in viewing and lighting, and provides high quality shading images exhibiting strong shape and spatial relationship of objects.

３Ｄ物体の鉛筆画風画像の生成

A simple technique is presented for generating pencil drawing images resembling hand-drawn sketches of 3D objects. We devised a method for extracting edge enhancement components by using division of an input image by its blurred one instead of conventional subtraction methods. Depth images are used for completion of edge enhancement components, which are impossible to extract from shading images. Edges are enhanced by removing one side of the edge enhancement shading. Thus, the obtained edge-enhanced shading images are transformed to stippling images using the point redistribution method presented by Secord et al. This stippling image is then anisotropically smoothed to produce a hatching image. We also applied this technique to moving images. One merit of our method is that it can produce movies with very low flicker without any specific overhead processing.

Obtaining Shape from Scanning Electron Microscope using Hopfield Neural Network

In the environment of the Scanning Electron Microscope (SEM), it is necessary to establish the technology of recovering the 3D shape of a target object from the observed 2D shading image. SEM has the function to rotate the object stand to some extent. This paper uses this principle and proposes a new method to recover the object shape using two shading images taken during the rotation. The proposed method uses the optimization of the energy function using Hopfield neural network, which is based on the standard regularization theory. It is also important to give the initial vector that is close to the true optimal solution vector. Computer simulation evaluates the essential ability of the proposed method. Further, the real experiments for the SEM images are also demonstrated and discussed.

The Role of Edges in Object Recognition by Pigeons

In three experiments, we explored how pigeons use edges, corresponding to orientation and depth discontinuities, in visual recognition tasks. In experiment 1, we compared the pigeon's ability to recognize line drawings of four different geons when trained with shaded images. The birds were trained with either a single view or five different views of each object. Because the five training views had markedly different appearances and locations of shaded surfaces, reflectance edges, etc, the pigeons might have been expected to rely more on the orientation and depth discontinuities that were preserved over rotation and in the line drawings. In neither condition, however, was there any transfer from the rendered images to the outline drawings. In experiment 2, some pigeons were trained with line drawings and shaded images of the same objects associated with the same response (consistent condition), whereas other pigeons were trained with a line drawing and a shaded image of two different objects associated with the same response (inconsistent condition). If the pigeons perceived any correspondence between the stimulus types, then birds in the consistent condition should have learned the discrimination more quickly than birds in the inconsistent condition. But, there was no difference in performance between birds in the consistent and inconsistent conditions. In experiment 3, we explored pigeons' processing of edges by comparing their discrimination of shaded images or line drawings of four objects. Once trained, the pigeons were tested with planar rotations of those objects. The pigeons exhibited different patterns of generalization depending on whether they were trained with line drawings or shaded images. The results of these three experiments suggest that pigeons may place greater importance on surface features indicating materials, such as food or water. Such substances do not have definite boundaries cued by edges which are thought to be central to human recognition.

A Biologically Inspired Algorithm for the Recovery of Shading and Reflectance Images

We present an algorithm for separating the shading and reflectance images of photographed natural scenes. The algorithm exploits the constraint that in natural scenes chromatic and luminance variations that are co-aligned mainly arise from changes in surface reflectance, whereas near-pure luminance variations mainly arise from shading and shadows. The novel aspect of the algorithm is the initial separation of the image into luminance and chromatic image planes that correspond to the luminance, red-green, and blue-yellow channels of the primate visual system. The red-green and blue-yellow image planes are analysed to provide a map of the changes in surface reflectance, which is then used to separate the reflectance from shading changes in both the luminance and chromatic image planes. The final reflectance image is obtained by reconstructing the chromatic and luminance-reflectance-change maps, while the shading image is obtained by subtracting the reconstructed luminance-reflectance image from the original luminance image. A number of image examples are included to illustrate the successes and limitations of the algorithm.

Reconstruction of Lambertian surfaces by discrete equal height contours and regions propagation

This paper describes two new methods for the reconstruction of discrete surfaces from shading images. Both approaches are based on the reconstruction of a discrete surface by mixing photometric and geometric techniques. The processing of photometric information is based on reflectance maps, which are classic tools of Shape from Shading. The geometric features are extracted from the discrete surface and propagated along the surface. The propagation is based in one case on equal height discrete contour propagation and in the other case on region propagation. Both methods allow photometric stereo. Results of reconstruction from synthetic and real images are presented.

2-5 最適閾値を自動的に設定できる変動閾値式2値化処理法(第2部門 コンシューマエレクトロニクス)

2-5 最適閾値を自動的に設定できる変動閾値式2値化処理法(第2部門 コンシューマエレクトロニクス)

Shape constancy does not hold for images rendered with different types of material surfaces

Shading in images of 3-D objects refers to variations in luminance or color as a function of the surface orientation with respect to the illumination and viewing directions. A shaded image often gives rise to a compelling sense of 3-D shape, surface and illumination properties. Contrary to this intuitive sense that shading elicits, in theory, it is not yet certain how this is achieved. We used local attitude and cross-section adjustment procedures to examine whether the perception of shape from shading can be influenced by type of material surfaces and light field. Stimuli were renderings of 3-D convex, solid objects projected onto a CRT screen. Four different types of material surface reflectance (diffuse, specular, backscattering, asperity scattering BRDFs (bi-directional reflectance distribution function)), three different lighting modes (collimated, hemispherically diffuse and combination of collimated and Ganzfeld lighting), and four different illumination directions (0, 30, 60 and 90 degree elevations) were used to render the surface of the objects (sphere or ellipsoid). Observers' task was to adjust the attitude of a probe to match perceived attitude of 7 test locations on the image and then to set the extent of perceived protuberance of these points. Results from the two tasks showed that surfaces having the backscattering and asperity reflection tended to be perceived as flatter than those having the diffuse and specular scattering. However, the lighting mode and light directions had no effect on the perceived orientation of the shape. This suggests that 3-D surface relief is not affected by changes in the distribution of intensity caused by the extrinsic factors such as lighting modes and directions, but by those in the material surfaces. In conclusion, shape constancy does not hold for images rendered with different types of material surfaces.

Perception of three-dimensional shape from specular highlights, deformations of shading, and other types of visual information.

There have been numerous computational models developed in an effort to explain how the human visual system analyzes three-dimensional (3D) surface shape from patterns of image shading, but they all share some important limitations. Models that are applicable to individual static images cannot correctly interpret regions that contain specular highlights, and those that are applicable to moving images have difficulties when a surface moves relative to its sources of illumination. Here we describe a psychophysical experiment that measured the sensitivity of human observers to small differences of 3D shape over a wide variety of conditions. The results provide clear evidence that the presence of specular highlights or the motions of a surface relative to its light source do not pose an impediment to perception, but rather, provide powerful sources of information for the perceptual analysis of 3D shape.

A neural network for recovering 3D shape from erroneous and few depth maps of shaded images

In this paper, we present a new neural network (NN) for three-dimensional (3D) shape reconstruction. This NN provides an analytic mapping of an initial 3D polyhedral model into its projection depth images. Through this analytic mapping, the NN can analytically refine vertices position of the model using error back-propagation learning. This learning is based on shape-from-shading (SFS) depth maps taken from multiple views. The depth maps are obtained by Tsai–Shah SFS algorithm. They are considered as partial 3D shapes of the object to be reconstructed. The task is to reconstruct an accurate and complete representation of a given object relying only on a limited number of views and erroneous SFS depth maps. Through hierarchical reconstruction and annealing reinforcement strategies, our reconstruction system gives more exact and stable results. In addition, it corrects and smoothly fuses the erroneous SFS depth maps. The implementation of this neural network algorithm used in this paper is available at http://kumazawa-www.cs.titech.ac.jp/~fanany/MV-SPRNN/mv-sprnn.html.

Measuring 3-D shapes of a human face using photometric stereo method with color light sources and slit patterns

We propose a new method for measuring 3-D facial shapes. This method uses two point light sources with red filters and a slit pattern projector with a blue filter. The time required for sampling data can be reduced by switching the color light rays at high speed, and hence a series of 3-D shapes of a human face at each instant can be measured. First, two facial images projected by both the red light rays and the blue light stripes are taken by the video camera, and these images are sepa- rated into two shading images and one slit image using the color infor- mation. Next, the normal vectors at points on the face are computed from the two shading images using the photometric stereo method. The 3-D coordinates of the points on the light stripes are measured from the slit image using the stereo vision algorithm. Finally, all the computed results are blended and the 3-D shape of the face is computed. Experimental results are shown to demonstrate the feasibility of the proposed method. © 2003 Society of Photo-Optical Instrumentation Engineers.

Motion and structure from multiple cues; image motion, shading flow, and stereo disparity

We investigate the recovery of 3-D motion and structure from the stereo images of a stationary environment. A Kalman filter-based framework is proposed for the reconstruction of 3-D structure from multiple visual cues, through the integration of image motion and stereo disparity with the shading flow that is induced by the rotational motion of the source. A common scenario involves the coupled motion of artificial source(s) and stereo cameras that are installed on mobile submersible vehicles. Utilizing shading flow with the image motion leads to devising a more robust 3-D motion estimation algorithm, in addition to the important role in depth recovery/refinement by constraining the local surface gradients. Collectively, use of multiple cues enhances robustness with respect to perturbation in any of the cues. Results of experiments with synthetic and real imagery are presented to evaluate the performance of the proposed algorithm, including the construction of a composite 3-D depth map of an underwater scene from a sequence of stereo pairs.

Illusory 3-D rotation induced by dynamic image shading.

Observers' perceptions of the three-dimensional structure of smoothly curved surfaces defined by patterns of image shading were investigated under varying conditions of illumination. In five experiments, observers judged the global orientation and the motion of the simulated surfaces from both static and dynamic patterns of image shading. We found that perceptual performance was more accurate with static than with dynamic displays. Dynamic displays evoked systematic biases in perceptual performance when the surface and the illumination source were simulated as rotating in opposite directions. In these conditions, the surface was incorrectly perceived as rotating in the same direction as the illumination source. Conversely, the orientation of the simulated surfaces was perceived correctly when the frames making up the apparent-motion sequences of the dynamic displays were presented as static images. In Experiment 6, moreover, the results obtained with the computer-generated displays were replicated with solid objects.