Illumination Gradient Research Articles

Local $N$ -Ary Pattern and Its Extension for Texture Classification

Texture image classification is important in computer vision research. To effectively capture texture patterns, a distinctive feature such as a local binary pattern (LBP) is needed. An LBP is robust against monotonic and gray-scale variations and it computes quickly. Its robustness and speed advantage have made it popular in various texture analysis applications. However, an LBP is sensitive to noise, particularly smooth weak illumination gradients in near-uniform regions. To mitigate the effect of noise and increase distinctiveness, a local ternary pattern (LTP) is proposed. Compared with a binary coding LBP, an LTP adopts ternary coding. As a result, an LTP can better tolerate noise and is significantly more distinctive. These advantages of an LTP effectively improve its classification accuracy. However, the potential of ternary coding is not fully explored in LTPs because a ternary pattern is split into a pair of binary patterns. In this paper, to fully explore the distinctiveness in the local pattern, the feature extraction process is formulated as an integer decomposition problem, which is a generalized version of the Bachet de Meziriac weight problem (BMWP). Following this generalization, a local $n$ -ary pattern (LNP) is proposed, for which the LBP is a special case parametrized under $n=2$ . The LTP is not a special case of the LNP. Both LBP and LTP are used as benchmark methods to evaluate LNPs performance due to their well-recognized success. In addition, a rotation-invariant and uniform LNP is also proposed and compared with a rotation-invariant and uniform LBP. The proposed LNP achieves significantly improved texture classification accuracy compared with the LBP and also demonstrates considerable improvement over the LTP.

Mobile Surface Reflectometry

AbstractWe present two novel mobile reflectometry approaches for acquiring detailed spatially varying isotropic surface reflectance and mesostructure of a planar material sample using commodity mobile devices. The first approach relies on the integrated camera and flash pair present on typical mobile devices to support free‐form handheld acquisition of spatially varying rough specular material samples. The second approach, suited for highly specular samples, uses the LCD panel to illuminate the sample with polarized second‐order gradient illumination. To address the limited overlap of the front facing camera's view and the LCD illumination (and thus limited sample size), we propose a novel appearance transfer method that combines controlled reflectance measurement of a small exemplar section with uncontrolled reflectance measurements of the full sample under natural lighting. Finally, we introduce a novel surface detail enhancement method that adds fine scale surface mesostructure from close‐up observations under uncontrolled natural lighting. We demonstrate the accuracy and versatility of the proposed mobile reflectometry methods on a wide variety of spatially varying materials.

An Illumination Representation Approach to the Chevreul Effect.

Within cognitive science of brightness and color perception, the argument has repeatedly been brought forward that it is necessary to consider mental representations for illuminations as well as mental representations for surfaces as integral elements of the functional architecture of the perceptual system. Here, we show that such an approach of dual semantic categories for perceptual representations can fruitfully be applied to the Chevreul effect, a brightness phenomenon of enhanced contrast at borders that played a prototypical role for a very different type of approaches. In these approaches, mechanisms processing retinal intensities are postulated that result in just one brightness dimension without explicitly referring to semantic categories of the perceptual system (surface vs. illumination representation). We argue that the Chevreul effect arises as a result of an interpretation by the visual system that the Chevreul stimulus is covered by a gradual illumination. Our first experiment shows that the Chevreul effect diminishes substantially when this interpretation is prevented by separating the elements of the Chevreul stimulus in depth. In the second experiment, we show that the strength of the Chevreul effect is strongly affected by embedding the Chevreul stimulus into three-dimensional scenes that either support or conflict with the interpretation of an illumination gradient across the stimulus.

Benefits of utilizing CellProfiler as a characterization tool for U–10Mo nuclear fuel

Automated image processing techniques have the potential to aid in the performance evaluation of nuclear fuels by eliminating judgment calls that may vary from person-to-person or sample-to-sample. Analysis of in-core fuel performance is required for design and safety evaluations related to almost every aspect of the nuclear fuel cycle. This study presents a methodology for assessing the quality of uranium–molybdenum fuel images and describes image analysis routines designed for the characterization of several important microstructural properties. The analyses are performed in CellProfiler, an open-source program designed to enable biologists without training in computer vision or programming to automatically extract cellular measurements from large image sets. The quality metric scores an image based on three parameters: the illumination gradient across the image, the overall focus of the image, and the fraction of the image that contains scratches. The metric presents the user with the ability to ‘pass’ or ‘fail’ an image based on a reproducible quality score. Passable images may then be characterized through a separate CellProfiler pipeline, which enlists a variety of common image analysis techniques. The results demonstrate the ability to reliably pass or fail images based on the illumination, focus, and scratch fraction of the image, followed by automatic extraction of morphological data with respect to fission gas voids, interaction layers, and grain boundaries.

Optical recording of surface relief on amorphous selenium

Surface reliefs in the form of dots and surrounding rings were recorded by focused laser beam on bulk amorphous selenium samples with an aim to separate the possible contributions of pure light- and thermally stimulated effects to the relief formation process. It is concluded, that heating by the light beam can be cross-linked with light induced mass transport in the gradient of illumination and temperature fields and so with surface relief formation, influencing its efficiency and quality. Such thermal effects should be taken into account in light sensitive chalcogenide glasses with low softening temperatures and possible crystallization effects.

Line Integral Convolution for Real‐Time Illustration of Molecular Surface Shape and Salient Regions

AbstractWe present a novel line drawing algorithm that illustrates surfaces in real‐time to convey their shape. We use line integral convolution (LIC) and employ ambient occlusion for illustrative surface rendering. Furthermore, our method depicts salient regions based on the illumination gradient. Our method works on animated surfaces in a frame‐coherent manner. Therefore, it yields an illustrative representation of time‐dependent surfaces as no preprocessing step is needed. In this paper, the method is used to highlight the structure of molecular surfaces and to illustrate important surface features like cavities, channels, and pockets. The benefit of our method was evaluated with domain experts. We also demonstrate the applicability of our method to medical visualization.

Improving Inertial Pedestrian Dead-Reckoning by Detecting Unmodified Switched-on Lamps in Buildings

This paper explores how inertial Pedestrian Dead-Reckoning (PDR) location systems can be improved with the use of a light sensor to measure the illumination gradients created when a person walks under ceiling-mounted unmodified indoor lights. The process of updating the inertial PDR estimates with the information provided by light detections is a new concept that we have named Light-matching (LM). The displacement and orientation change of a person obtained by inertial PDR is used by the LM method to accurately propagate the location hypothesis, and vice versa; the LM approach benefits the PDR approach by obtaining an absolute localization and reducing the PDR-alone drift. Even from an initially unknown location and orientation, whenever the person passes below a switched-on light spot, the location likelihood is iteratively updated until it potentially converges to a unimodal probability density function. The time to converge to a unimodal position hypothesis depends on the number of lights detected and the asymmetries/irregularities of the spatial distribution of lights. The proposed LM method does not require any intensity illumination calibration, just the pre-storage of the position and size of all lights in a building, irrespective of their current on/off state. This paper presents a detailed description of the light-matching concept, the implementation details of the LM-assisted PDR fusion scheme using a particle filter, and several simulated and experimental tests, using a light sensor-equipped Galaxy S3 smartphone and an external foot-mounted inertial sensor. The evaluation includes the LM-assisted PDR approach as well as the fusion with other signals of opportunity (WiFi, RFID, Magnetometers or Map-matching) in order to compare their contribution in obtaining high accuracy indoor localization. The integrated solution achieves a localization error lower than 1 m in most of the cases.

Identification and expression analysis of the gene lhcSR associated with adaptation to light and low temperature stress in the green tide forming alga Ulva prolifera

As the dominant species of the green tide-forming algae in the Yellow Sea of China during the past four years, Ulva prolifera was proposed as having evolved a perfect response mechanism to deal with different light and temperature stress. The LHCSR (also known as LI818 in green algae and LHCX in diatoms) protein is a stress-related member of the LHC family found only in algae. The homologues in the green alga Chlamydomonas were up-regulated in response to a variety of stresses and required for energy quenching. In this study, we cloned a putative lhcSR full-length cDNA sequence from U. prolifera and analysed the expression in response to various temperature and illumination gradients. The results showed that expression of lhcSR was up-regulated by light and transiently accumulated in 1 h. Expression of lhcSR could also be induced by low-temperature stress and could sustain the up-regulation for up to 6 days. These data suggest that the lhcSR gene in U. prolifera is involved in the adaption to the light and low-temperature stress in both the short and long term.

Learning to use illumination gradients as shape cues.

Learning to use illumination gradients as shape cues.

Invariant Gabor Texture Descriptors for Classification of Gastroenterology Images

Automatic classification of lesions for gastroenterology imaging scenarios poses novel challenges to computer-assisted decision systems, which are mostly attributed to the dynamics of the image acquisition conditions. Such challenges demand that automatic systems are able to give robust characterizations of tissues irrespective of camera rotation, zoom, and illumination gradients when viewing the inner surface of the gastrointestinal tract. In this paper, we study the invariance properties of Gabor filters and propose a novel descriptor, the autocorrelation Gabor features (AGF). We show that our proposed AGF is invariant to scale, rotation, and illumination changes in the images. We integrate these new features in a texton framework (Texton-AGF) to classify images from two complementary gastroenterology imaging scenarios (chromoendoscopy and narrow-band imaging) broadly into three different groups: normal, precancerous, and cancerous. Results show that they compare favorably to using state-of-the-art texture descriptors for both imaging modalities.

Имитационное моделирование направленного движения в условиях градиента освещенности

Имитационное моделирование направленного движения в условиях градиента освещенности

Learning to Use Illumination Gradients as an Unambiguous Cue to Three Dimensional Shape

The luminance and colour gradients across an image are the result of complex interactions between object shape, material and illumination. Using such variations to infer object shape or surface colour is therefore a difficult problem for the visual system. We know that changes to the shape of an object can affect its perceived colour, and that shading gradients confer a sense of shape. Here we investigate if the visual system is able to effectively utilise these gradients as a cue to shape perception, even when additional cues are not available. We tested shape perception of a folded card object that contained illumination gradients in the form of shading and more subtle effects such as inter-reflections. Our results suggest that observers are able to use the gradients to make consistent shape judgements. In order to do this, observers must be given the opportunity to learn suitable assumptions about the lighting and scene. Using a variety of different training conditions, we demonstrate that learning can occur quickly and requires only coarse information. We also establish that learning does not deliver a trivial mapping between gradient and shape; rather learning leads to the acquisition of assumptions about lighting and scene parameters that subsequently allow for gradients to be used as a shape cue. The perceived shape is shown to be consistent for convex and concave versions of the object that exhibit very different shading, and also similar to that delivered by outline, a largely unrelated cue to shape. Overall our results indicate that, although gradients are less reliable than some other cues, the relationship between gradients and shape can be quickly assessed and the gradients therefore used effectively as a visual shape cue.

Prosthetic component segmentation with blur compensation: a fast method for 3D fluoroscopy

A new method for prosthetic component segmentation from fluoroscopic images is presented. The hybrid approach we propose combines diffusion filtering, region growing and level-set techniques without exploiting any a priori knowledge of the analyzed geometry. The method was evaluated on a synthetic dataset including 270 images of knee and hip prosthesis merged to real fluoroscopic data simulating different conditions of blurring and illumination gradient. The performance of the method was assessed by comparing estimated contours to references using different metrics. Results showed that the segmentation procedure is fast, accurate, independent on the operator as well as on the specific geometrical characteristics of the prosthetic component, and able to compensate for amount of blurring and illumination gradient. Importantly, the method allows a strong reduction of required user interaction time when compared to traditional segmentation techniques. Its effectiveness and robustness in different image conditions, together with simplicity and fast implementation, make this prosthetic component segmentation procedure promising and suitable for multiple clinical applications including assessment of in vivo joint kinematics in a variety of cases.

Multiview face capture using polarized spherical gradient illumination

We present a novel process for acquiring detailed facial geometry with high resolution diffuse and specular photometric information from multiple viewpoints using polarized spherical gradient illumination. Key to our method is a new pair of linearly polarized lighting patterns which enables multiview diffuse-specular separation under a given spherical illumination condition from just two photographs. The patterns -- one following lines of latitude and one following lines of longitude -- allow the use of fixed linear polarizers in front of the cameras, enabling more efficient acquisition of diffuse and specular albedo and normal maps from multiple viewpoints. In a second step, we employ these albedo and normal maps as input to a novel multi-resolution adaptive domain message passing stereo reconstruction algorithm to create high resolution facial geometry. To do this, we formulate the stereo reconstruction from multiple cameras in a commonly parameterized domain for multiview reconstruction. We show competitive results consisting of high-resolution facial geometry with relightable reflectance maps using five DSLR cameras. Our technique scales well for multiview acquisition without requiring specialized camera systems for sensing multiple polarization states.

Grouping by Regularity and the perception of illumination

The purpose of this work is to describe how the visual system groups surfaces of unequal lightness under complex patterns of illumination. We propose that the Gestalt principle of Grouping by Regularity explains this process better than the more often cited principle of Grouping by Similarity. In our first experiment we demonstrate that in a perceptual organization task, pitting proximity against illumination gradients, discounting the illuminant was contingent upon the periodicity of the illuminant. Traditional theories of lightness constancy and discounting the illuminant ( Rock, Nijhawan, Palmer, & Tudor, 1992) cannot account for such effects. Three more experiments show that grouping is affected more by local luminance ratios than constant reflectance ratios. We conclude from these findings that Grouping by Regularity is a powerful grouping principle that operates pre-constancy.

Characterization of the LhcSR Gene Under Light and Temperature Stress in the Green Alga Ulva linza

As a green-tide-forming macroalga, Ulva linza is distributed worldwide and therefore subject to various environmental stresses. The LHCSR (also known as LI818 in green alga and LHCX in diatoms) protein is a stress-related member of the LHC family that plays an important role in photo-protective mechanism, which has been only found in algae. In this study, we cloned full-length cDNA sequence encoding the LhcSR gene from U. linza and analyzed its expression in response to different temperature and illumination gradients. The results showed that high light (HL) could enhance expression of LhcSR and that the expression level peaked at 3 h under HL. Similarly, the expression of LhcSR could also be induced by low temperature (LT). However, the expression patterns of LhcSR were quite different in response to LT and HL treatment. Specifically, the maximum gene expression under LT was much higher (11.8-fold) than under HL (5.4-fold) when compared to the expression under normal conditions. The upregulated expression of LhcSR lasted for 12 h under LT, but 3 h under HL. These data suggest that the LhcSR gene is involved in photoprotection in U. linza, and the results suggest a stronger link to LT. In addition, the discrepancy in expression under HL and LT was consistent with the ecological features of this alga, which only thrives during the cold season (featured as LT and low light).

Comprehensive Facial Performance Capture

AbstractWe present a system for recording a live dynamic facial performance, capturing highly detailed geometry and spatially varying diffuse and specular reflectance information for each frame of the performance. The result is a reproduction of the performance that can be rendered from novel viewpoints and novel lighting conditions, achieving photorealistic integration into any virtual environment. Dynamic performances are captured directly, without the need for any template geometry or static geometry scans, and processing is completely automatic, requiring no human input or guidance. Our key contributions are a heuristic for estimating facial reflectance information from gradient illumination photographs, and a geometry optimization framework that maximizes a principled likelihood function combining multi‐view stereo correspondence and photometric stereo, using multi‐resolution belief propagation. The output of our system is a sequence of geometries and reflectance maps, suitable for rendering in off‐the‐shelf software. We show results from our system rendered under novel viewpoints and lighting conditions, and validate our results by demonstrating a close match to ground truth photographs.

Adaptive Records for Irradiance Caching

AbstractIrradiance Caching is one of the most widely used algorithms to speed up global illumination. In this paper, we propose an algorithm based on the Irradiance Caching scheme that allows us (1) to adjust the density of cached records according to illumination changes and (2) to efficiently render the high‐frequency illumination changes. To achieve this, a new record footprint is presented. Although the original method uses records having circular footprints depending only on geometrical features, our record footprints have a more complex shape which accounts for both geometry and irradiance variations. Irradiance values are computed using a classical Monte Carlo ray tracing method that simplifies the determination of nearby objects and the pre‐computation of the shape of the influence zone of the current record. By gathering irradiance due to all the incident rays, illumination changes are evaluated to adjust the footprint’s records. As a consequence, the record footprints are smaller where illumination gradients are high. With this technique, the record density depends on the irradiance variations. Strong variations of irradiance (due to direct contributions for example) can be handled and evaluated accurately. Caching direct illumination is of high importance, especially in the case of scenes having many light sources with complex geometry as well as surfaces exposed to daylight. Recomputing direct illumination for the whole image can be very time‐consuming, especially for walkthrough animation rendering or for high‐resolution pictures. Storing such contributions in the irradiance cache seems to be an appropriate solution to accelerate the final rendering pass.

A progressive error estimation framework for photon density estimation

We present an error estimation framework for progressive photon mapping. Although estimating rendering error has been established for unbiased rendering algorithms, error estimation for biased rendering algorithms has not been investigated well in comparison. We characterize the error by the sum of a bias estimate and a stochastic noise bound, which is motivated by stochastic error bounds formulation in biased methods. As a part of our error computation, we extend progressive photon mapping to operate with smooth kernels. This enables the calculation of illumination gradients with arbitrary accuracy, which we use to progressively compute the local bias in the radiance estimate. We also show how variance can be computed in progressive photon mapping, which is used to estimate the error due to noise. As an example application, we show how our error estimation can be used to compute images with a given error threshold. For this example application, our framework only requires the error threshold and a confidence level to automatically terminate rendering. Our results demonstrate how our error estimation framework works well in realistic synthetic scenes.

Cortical dynamics of surface lightness anchoring, filling-In, and perception

This study proposes how the visual cortex may process natural images under variable illumination conditions to generate surface lightness percepts. It is known that visual representations can adapt to a million-fold change in luminance. How such adaptation also anchors percepts of surface lightness to use the full dynamic range of neurons remains an unsolved problem. Such an anchoring of lightness helps to make an image look natural. Anchoring properties include articulation, insulation, configuration, and area effects (e.g., Gilchrist et al., 1999). A cortical model is developed that quantitatively simulates such psychophysical data, as well as psychophysical data about discounting the illumination gradient and the Cornsweet effect, among others. The model is also consistent with a range of anatomical and neurophysiological data about how the brain may use boundary representations to gate the filling-in of surface lightness via horizontal cortical interactions. The model filling-in mechanism runs a thousand times faster than mechanisms of previous biological filling-in models, and thereby helps to clarify how filling-in can occur at the speeds shown in perceptual experiments. The model can process natural images even under dim moonlight and dazzling sunlight. Application of the model to color domain illustrates that it is also able to process natural color images.