Effect of intrinsic nanoparticle pigmentation on the color stability of denture base acrylic resins

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Color texture analysis based on fractal descriptors

Color texture classification is an important step in image segmentation and recognition. The color information is especially important in textures of natural scenes, such as leaves surfaces, terrains models, etc. In this paper, we propose a novel approach based on the fractal dimension for color texture analysis. The proposed approach investigates the complexity in R, G and B color channels to characterize a texture sample. We also propose to study all channels in combination, taking into consideration the correlations between them. Both these approaches use the volumetric version of the Bouligand-Minkowski Fractal Dimension method. The results show a advantage of the proposed method over other color texture analysis methods. (C) 2011 Elsevier Ltd. All rights reserved.

Chemical and morphological features of nanofilled composite resin: Influence of finishing and polishing procedures and fluoride solutions

This study evaluated the influence of finishing and polishing procedures and different fluoride solutions on superficial morphology and chemistry of the nanofilled composite resin Supreme XT (3M) through the EDX analysis and SEM evaluation. Circular specimens (n = 30) of 10 mm diameter and 2 mm thickness were prepared, with half of the sample assays finished and polished with Super-Snap (R) sandpaper. The experimental groups were divided according to the presence or absence of finishing and polishing and solutions (artificial saliva, 0.05% of manipulated sodium fluoride solution, Fluordent Reach, Oral B, Fluorgard). Specimens were immersed in each respective solution for 1 min per day, during 60 days and stored in artificial saliva at 37 +/- 1 degrees C between immersion periods. Topography and chemical analysis was qualitative. It was observed that specimens submitted to finishing and polishing procedures had lower superficial degradation. Fluoride solutions promoted superficial alterations on specimens, being the highest degradation obtained with Fluordent Reach. It can be concluded that finishing and polishing procedures and the immersion media influence the superficial morphology of composite resin tested; the Fluordent Reach was the fluoride solution that most affected the material's surface. Microsc. Res. Tech. 2011., (c) 2011 Wiley Periodicals, Inc.

Implementation of a robust optical flow method for color images

We analyse the influence of colour information in optical flow methods. Typically, most of these techniques compute their solutions using grayscale intensities due to its simplicity and faster processing, ignoring the colour features. However, the current processing systems have minimized their computational cost and, on the other hand, it is reasonable to assume that a colour image offers more details from the scene which should facilitate finding better flow fields. The aim of this work is to determine if a multi-channel approach supposes a quite enough improvement to justify its use. In order to address this evaluation, we use a multi-channel implementation of a well-known TV-L1 method. Furthermore, we review the state-of-the-art in colour optical flow methods. In the experiments, we study various solutions using grayscale and RGB images from recent evaluation datasets to verify the colour benefits in motion estimation.

Ultrasonographic features of PMEL17 ( Silver ) mutant gene-associated multiple congenital ocular anomalies (MCOA) in Comtois and Rocky Mountain horses

OBJECTIVE: (1) To describe the ultrasonographic appearance of multiple congenital ocular anomalies (MCOA) in the eyes of horses with the PMEL17 (Silver) mutant gene. (2) To compare the accuracy of B-mode ocular ultrasound to conventional direct ophthalmoscopy. ANIMALS STUDIED: Sixty-seven Comtois and 18 Rocky Mountain horses were included in the study. PROCEDURES: Horses were classified as being carriers or noncarriers of the PMEL17 mutant allele based on coat color or genetic testing. Direct ophthalmoscopy followed by standardized ultrasonographic examination was performed in all horses. RESULTS: Seventy-five of 85 horses (88.24%) carried at least one copy of the Silver mutant allele. Cornea globosa, severe iridal hypoplasia, uveal cysts, cataracts, and retinal detachment could be appreciated with ultrasound. Carrier horses had statistically significantly increased anterior chamber depth and decreased thickness of anterior uvea compared with noncarriers (P < 0.05). Uveal cysts had a wide range of location and ultrasonographic appearances. In 51/73 (69.86%) carrier horses, ultrasound detected ciliary cysts that were missed with direct ophthalmoscopy. CONCLUSIONS: In this study, ultrasonography was useful to identify uveal cysts in PMEL17 mutant carriers and to assess anterior chamber depth.

Robust Denoising using Feature and Color Information

We propose a method that robustly combines color and feature buffers to denoise Monte Carlo renderings. On one hand, feature buffers, such as per pixel normals, textures, or depth, are effective in determining denoising filters because features are highly correlated with rendered images. Filters based solely on features, however, are prone to blurring image details that are not well represented by the features. On the other hand, color buffers represent all details, but they may be less effective to determine filters because they are contaminated by the noise that is supposed to be removed. We propose to obtain filters using a combination of color and feature buffers in an NL-means and cross-bilateral filtering framework. We determine a robust weighting of colors and features using a SURE-based error estimate. We show significant improvements in subjective and quantitative errors compared to the previous state-of-the-art. We also demonstrate adaptive sampling and space-time filtering for animations.

A Food Recognition System for Diabetic Patients based on an Optimized Bag of Features Model

Computer vision-based food recognition could be used to estimate a meal's carbohydrate content for diabetic patients. This study proposes a methodology for automatic food recognition, based on the Bag of Features (BoF) model. An extensive technical investigation was conducted for the identification and optimization of the best performing components involved in the BoF architecture, as well as the estimation of the corresponding parameters. For the design and evaluation of the prototype system, a visual dataset with nearly 5,000 food images was created and organized into 11 classes. The optimized system computes dense local features, using the scale-invariant feature transform on the HSV color space, builds a visual dictionary of 10,000 visual words by using the hierarchical k-means clustering and finally classifies the food images with a linear support vector machine classifier. The system achieved classification accuracy of the order of 78%, thus proving the feasibility of the proposed approach in a very challenging image dataset.

Region-dependent vehicle classification using PCA features

Video-based vehicle detection is the focus of increasing interest due to its potential towards collision avoidance. In particular, vehicle verification is especially challenging due to the enormous variability of vehicles in size, color, pose, etc. In this paper, a new approach based on supervised learning using Principal Component Analysis (PCA) is proposed that addresses the main limitations of existing methods. Namely, in contrast to classical approaches which train a single classifier regardless of the relative position of the candidate (thus ignoring valuable pose information), a region-dependent analysis is performed by considering four different areas. In addition, a study on the evolution of the classification performance according to the dimensionality of the principal subspace is carried out using PCA features within a SVM-based classification scheme. Indeed, the experiments performed on a publicly available database prove that PCA dimensionality requirements are region-dependent. Hence, in this work, the optimal configuration is adapted to each of them, rendering very good vehicle verification results.

Merit function for the evaluation of color uniformity in the far field of LED spot lights

The scope of the present paper is the derivation of a merit function which predicts the visual perception of LED spot lights. The color uniformity level Usl is described by a linear regression function of the spatial color distribution in the far field. Hereby, the function is derived from four basic functions. They describe the color uniformity of spot lights through different features. The result is a reliable prediction for the perceived color uniformity in spot lights. A human factor experiment was performed to evaluate the visual preferences for colors and patterns. A perceived rank order was derived from the subjects’ answers and compared with the four basic functions. The correlation between the perceived rank order and the basic functions was calculated resulting in the definition of the merit function Usl. The application of this function is shown by a comparison of visual evaluations and measurements of LED retrofit spot lamps. The results enable a prediction of color uniformity levels of simulations and measurements concerning the visual perception. The function provides a possibility to evaluate the far field of spot lights without individual subjective judgment. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Learning 3D structure from 2D images using LBP features

An automatic machine learning strategy for computing the 3D structure of monocular images from a single image query using Local Binary Patterns is presented. The 3D structure is inferred through a training set composed by a repository of color and depth images, assuming that images with similar structure present similar depth maps. Local Binary Patterns are used to characterize the structure of the color images. The depth maps of those color images with a similar structure to the query image are adaptively combined and filtered to estimate the final depth map. Using public databases, promising results have been obtained outperforming other state-of-the-art algorithms and with a computational cost similar to the most efficient 2D-to-3D algorithms.

Psychophysical evidence for fast region-based segmentation processes in motion and color.

Theories of image segmentation suggest that the human visual system may use two distinct processes to segregate figure from background: a local process that uses local feature contrasts to mark borders of coherent regions and a global process that groups similar features over a larger spatial scale. We performed psychophysical experiments to determine whether and to what extent the global similarity process contributes to image segmentation by motion and color. Our results show that for color, as well as for motion, segmentation occurs first by an integrative process on a coarse spatial scale, demonstrating that for both modalities the global process is faster than one based on local feature contrasts. Segmentation by motion builds up over time, whereas segmentation by color does not, indicating a fundamental difference between the modalities. Our data suggest that segmentation by motion proceeds first via a cooperative linking over space of local motion signals, generating almost immediate perceptual coherence even of physically incoherent signals. This global segmentation process occurs faster than the detection of absolute motion, providing further evidence for the existence of two motion processes with distinct dynamic properties.

Primate photopigments and primate color vision.

The past 15 years have brought much progress in our understanding of several basic features of primate color vision. There has been particular success in cataloging the spectral properties of the cone photopigments found in retinas of a number of primate species and in elucidating the relationship between cone opsin genes and their photopigment products. Direct studies of color vision show that there are several modal patterns of color vision among groupings of primates: (i) Old World monkeys, apes, and humans all enjoy trichromatic color vision, although the former two groups do not seem prone to the polymorphic variations in color vision that are characteristic of people; (ii) most species of New World monkeys are highly polymorphic, with individual animals having any of several types of dichromatic or trichromatic color vision; (iii) less is known about color vision in prosimians, but evidence suggests that at least some diurnal species have dichromatic color vision; and (iv) some nocturnal primates may lack color vision completely. In many cases the photopigments and photopigment gene arrangements underlying these patterns have been revealed and, as a result, hints are emerging about the evolution of color vision among the primates.

Self-recognition in primates: phylogeny and the salience of species-typical features.

Self-recognition has been explored in nonlinguistic organisms by recording whether individuals touch a dye-marked area on visually inaccessible parts of their face while looking in a mirror or inspect parts of their body while using the mirror's reflection. Only chimpanzees, gorillas, orangutans, and humans over the age of approximately 2 years consistently evidence self-directed mirror-guided behavior without experimenter training. To evaluate the inferred phylogenetic gap between hominoids and other animals, a modified dye-mark test was conducted with cotton-top tamarins (Saguinus oedipus), a New World monkey species. The white hair on the tamarins' head was color-dyed, thereby significantly altering a visually distinctive species-typical feature. Only individuals with dyed hair and prior mirror exposure touched their head while looking in the mirror. They looked longer in the mirror than controls, and some individuals used the mirror to observe visually inaccessible body parts. Prior failures to pass the mirror test may have been due to methodological problems, rather than to phylogenetic differences in the capacity for self-recognition. Specifically, an individual's sensitivity to experimentally modified parts of its body may depend crucially on the relative saliency of the modified part (e.g., face versus hair). Moreover, and in contrast to previous claims, we suggest that the mirror test may not be sufficient for assessing the concept of self or mental state attribution in nonlinguistic organisms.

Boston, Massachusetts Region 1:5,000 Color Ortho Imagery (1/2-meter Resolution), 2001

1/2-meter resolution 1:5,000 orthophoto image of the Boston region from April 2001. This datalayer is a subset (covering only the Boston region) of the Massachusetts statewide orthophoto image series available from MassGIS. It consists of 23 orthophoto quads mosaicked together (MassGIS orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 233906, 233910, 237890, 237894, 237898, 237902, 237906, 237910, 241890, 241894, 241898, 241902, 245898, 245902). These medium resolution true color images are considered the new "basemap" for the Commonwealth by MassGIS and the Executive Office of Environmental Affairs (EOEA). MassGIS/EOEA and the Massachusetts Highway Department jointly funded the project. The photography for the mainland was captured in April 2001 when deciduous trees were mostly bare and the ground was generally free of snow. The geographic extent of this dataset is the same as that of the MassGIS dataset: Boston, Massachusetts Region LIDAR First Return Elevation Data, 2002 [see cross references].

SPECTRAL DOMAIN-OPTICAL COHERENCE TOMOGRAPHY IMAGE CONTRAST AND BACKGROUND COLOR SETTINGS INFLUENCE IDENTIFICATION OF RETINAL STRUCTURES.

PURPOSE To evaluate image contrast and color setting on assessment of retinal structures and morphology in spectral-domain optical coherence tomography. METHODS Two hundred and forty-eight Spectralis spectral-domain optical coherence tomography B-scans of 62 patients were analyzed by 4 readers. B-scans were extracted in 4 settings: W + N = white background with black image at normal contrast 9; W + H = white background with black image at maximum contrast 16; B + N = black background with white image at normal contrast 12; B + H = black background with white image at maximum contrast 16. Readers analyzed the images to identify morphologic features. Interreader correlation was calculated. Differences between Fleiss-kappa correlation coefficients were examined using bootstrap method. Any setting with significantly higher correlation coefficient was deemed superior for evaluating specific features. RESULTS Correlation coefficients differed among settings. No single setting was superior for all respective spectral-domain optical coherence tomography parameters (P = 0.3773). Some variables showed no differences among settings. Hard exudates and subretinal fluid were best seen with B + H (κ = 0.46, P = 0.0237 and κ = 0.78, P = 0.002). Microaneurysms were best seen with W + N (κ = 0.56, P = 0.025). Vitreomacular interface, enhanced transmission signal, and epiretinal membrane were best identified using all color/contrast settings together (κ = 0.44, P = 0.042, κ = 0.57, P = 0.01, and κ = 0.62, P ≤ 0.0001). CONCLUSION Contrast and background affect the evaluation of retinal structures on spectral-domain optical coherence tomography images. No single setting was superior for all features, though certain changes were best seen with specific settings.