Multilayer Complex Network Descriptors for Color-Texture Characterization

A new method based on complex networks is proposed for color-texture analysis. The proposal consists on modeling the image as a multilayer complex network where each color channel is a layer, and each pixel (in each color channel) is represented as a network vertex. The network dynamic evolution is accessed using a set of modeling parameters (radii and thresholds), and new characterization techniques are introduced to capt information regarding within and between color channel spatial interaction. An automatic and adaptive approach for threshold selection is also proposed. We conduct classification experiments on 5 well-known datasets: Vistex, Usptex, Outex13, CURet and MBT. Results among various literature methods are compared, including deep convolutional neural networks with pre-trained architectures. The proposed method presented the highest overall performance over the 5 datasets, with 97.7 of mean accuracy against 97.0 achieved by the ResNet convolutional neural network with 50 layers.Comment: 20 pages, 7 figures and 4 table

A Material Investigation of Color Film Technology through the Koshofer Collection

The Koshofer collection is an invaluable resource about the history of color film technology from the late nineteenth century until the 1980s, including film frames from early applied hand coloring, tinting and stencil coloring, to mimetic color processes such as Kinemacolor, Gasparcolor, and many other rare and popular color film stocks. Multispectral imaging in the visible range has been carried out to characterize the optical properties of the color processes, and an extensive microscopic examination allowed to reveal minute material features. These investigations highlight distinctive elements for the identification of some of the most significant historical color processes on film, and at the same time, offer crucial information for classical restoration techniques and for rigorous digitization strategies

Multispectral Imaging for Determination of Astaxanthin Concentration in Salmonids

Multispectral imaging has been evaluated for characterization of the concentration of a specific cartenoid pigment; astaxanthin. 59 fillets of rainbow trout, Oncorhynchus mykiss, were filleted and imaged using a rapid multispectral imaging device for quantitative analysis. The multispectral imaging device captures reflection properties in 19 distinct wavelength bands, prior to determination of the true concentration of astaxanthin. The samples ranged from 0.20 to 4.34 g per g fish. A PLSR model was calibrated to predict astaxanthin concentration from novel images, and showed good results with a RMSEP of 0.27. For comparison a similar model were built for normal color images, which yielded a RMSEP of 0.45. The acquisition speed of the multispectral imaging system and the accuracy of the PLSR model obtained suggest this method as a promising technique for rapid in-line estimation of astaxanthin concentration in rainbow trout fillets

Analysis of Diagnostic Images of Artworks and Feature Extraction: Design of a Methodology

none6noDigital images represent the primary tool for diagnostics and documentation of the state of preservation of artifacts. Today the interpretive filters that allow one to characterize information and communicate it are extremely subjective. Our research goal is to study a quantitative analysis methodology to facilitate and semi-automate the recognition and polygonization of areas corresponding to the characteristics searched. To this end, several algorithms have been tested that allow for separating the characteristics and creating binary masks to be statistically analyzed and polygonized. Since our methodology aims to offer a conservator-restorer model to obtain useful graphic documentation in a short time that is usable for design and statistical purposes, this process has been implemented in a single Geographic Information Systems (GIS) application.openAmura, Annamaria; Aldini, Alessandro; Pagnotta, Stefano; Salerno, Emanuele; Tonazzini, Anna; Triolo, PaoloAmura, Annamaria; Aldini, Alessandro; Pagnotta, Stefano; Salerno, Emanuele; Tonazzini, Anna; Triolo, Paol

Systems evaluation for computer graphics rendering of the total appearance of paintings

One of the challenges when imaging paintings is recording total appearance, that is, the object\u27s color, surface microstructure (gloss), and surface macrostructure (topography). In this thesis, various systems were used to achieve this task, and a psychophysical paired comparison experiment was conducted to evaluate their performance. A pair of strobe lights arranged at 60° from the normal on either side of the painting captured color information where the strobes produced either directional or diffuse illumination geometry. By adding a third strobe, arranging them 120° apart annularly, and cross polarizing, diffuse color and surface normal maps were measured. A fourth strobe was added and the four lights were rearranged 90° apart annularly, capturing similar data. This system was augmented by two scanning linear light sources arranged perpendicularly, facilitating the measurement of spatially varying BRDF and specular maps. A laser scanner was used to capture surface macrostructure and was combined with the diffuse color maps from the four-light configuration. Finally, a dome illumination system was used with software developed by Conservation Heritage Imaging to produce color maps. In all, eight different configurations were achieved and used to image three small paintings with a range of appearance attributes. Twenty-five naive observers compared computer-graphic renderings to the actual painting and judged similarity in terms of total appearance, gloss/shininess, texture, and color. Although the rankings varied with painting, two general trends emerged. First, the four-light configuration with or without the independent laser scanning produced images visually equivalent to conventional strobe illumination. Second, diffuse illumination was always ranked lowest

Multispectral photography for earth resources

A guide for producing accurate multispectral results for earth resource applications is presented along with theoretical and analytical concepts of color and multispectral photography. Topics discussed include: capabilities and limitations of color and color infrared films; image color measurements; methods of relating ground phenomena to film density and color measurement; sensitometry; considerations in the selection of multispectral cameras and components; and mission planning

Spectral 3D Computer Vision -- A Review

Spectral 3D computer vision examines both the geometric and spectral properties of objects. It provides a deeper understanding of an object's physical properties by providing information from narrow bands in various regions of the electromagnetic spectrum. Mapping the spectral information onto the 3D model reveals changes in the spectra-structure space or enhances 3D representations with properties such as reflectance, chromatic aberration, and varying defocus blur. This emerging paradigm advances traditional computer vision and opens new avenues of research in 3D structure, depth estimation, motion analysis, and more. It has found applications in areas such as smart agriculture, environment monitoring, building inspection, geological exploration, and digital cultural heritage records. This survey offers a comprehensive overview of spectral 3D computer vision, including a unified taxonomy of methods, key application areas, and future challenges and prospects

Utility of multispectral imaging for nuclear classification of routine clinical histopathology imagery

<p>Abstract</p> <p>Background</p> <p>We present an analysis of the utility of multispectral versus standard RGB imagery for routine H&E stained histopathology images, in particular for pixel-level classification of nuclei. Our multispectral imagery has 29 spectral bands, spaced 10 nm within the visual range of 420–700 nm. It has been hypothesized that the additional spectral bands contain further information useful for classification as compared to the 3 standard bands of RGB imagery. We present analyses of our data designed to test this hypothesis.</p> <p>Results</p> <p>For classification using all available image bands, we find the best performance (equal tradeoff between detection rate and false alarm rate) is obtained from either the multispectral or our "ccd" RGB imagery, with an overall increase in performance of 0.79% compared to the next best performing image type. For classification using single image bands, the single best multispectral band (in the red portion of the spectrum) gave a performance increase of 0.57%, compared to performance of the single best RGB band (red). Additionally, red bands had the highest coefficients/preference in our classifiers. Principal components analysis of the multispectral imagery indicates only two significant image bands, which is not surprising given the presence of two stains.</p> <p>Conclusion</p> <p>Our results indicate that multispectral imagery for routine H&E stained histopathology provides minimal additional spectral information for a pixel-level nuclear classification task than would standard RGB imagery.</p