149 research outputs found

    Refinement of the RLAB Color Space

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    The prediction of color appearance using the RLAB color space has been tested for a variety of viewing conditions and stimulus types. These tests have shown that RLAB performs well for complex stimuli and not-so-well for simple stimuli. This article reviews the various psychophysical results, interprets their differences, and describes evolutionary enhancements to the RLAB model that simplify it and improve its performance

    Pushing the Limits of 3D Color Printing: Error Diffusion with Translucent Materials

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    Accurate color reproduction is important in many applications of 3D printing, from design prototypes to 3D color copies or portraits. Although full color is available via other technologies, multi-jet printers have greater potential for graphical 3D printing, in terms of reproducing complex appearance properties. However, to date these printers cannot produce full color, and doing so poses substantial technical challenges, from the shear amount of data to the translucency of the available color materials. In this paper, we propose an error diffusion halftoning approach to achieve full color with multi-jet printers, which operates on multiple isosurfaces or layers within the object. We propose a novel traversal algorithm for voxel surfaces, which allows the transfer of existing error diffusion algorithms from 2D printing. The resulting prints faithfully reproduce colors, color gradients and fine-scale details.Comment: 15 pages, 14 figures; includes supplemental figure

    Determinants of colour constancy

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    Colour constancy describes the ability of our visual system to keep colour percepts stable through illumination changes. This is an outstanding feat given that in the retinal image surface and illuminant properties are conflated. Still, in our everyday lives we are able attribute stable colour-labels to objects to make communication economic and efficient. Past research shows colour constancy to be imperfect, compensating for 40% and 80% of the illumination change. While different constancy determinants are suggested, no carefully controlled study shows perfect constancy. The first study presented here addresses the issue of imperfect constancy by investigating colour constancy in a cue rich environment, using a task that resembles our everyday experience with colours. Participants were asked to recall the colour of unique personal objects in natural environment under four chromatic illuminations. This approach yielded perfect colour constancy. The second study investigated the relation between illumination discrimination and chromatic detection. Recent studies using an illumination discrimination paradigm suggest that colour constancy is optimized for bluish daylight illuminations. Because it is not clear if illumination discrimination is directly related to colour constancy or is instead explained by sensitivity to changes in chromaticity of different hues, thresholds for illumination discrimination and chromatic detection for the same 12 illumination hues were compared. While the reported blue bias could be replicated, thresholds for illumination discrimination and chromatic detection were highly related, indicating that lower sensibility towards bluish hues is not exclusive to illumination discrimination. Accompanying the second study, the third study investigated the distribution of colour constancy for 40 chromatic illuminations of different hue using achromatic adjustments and colour naming. These measurements were compared to several determinants of colour constancy, including the daylight locus, colour categories, illumination discrimination, chromatic detection, relational colour constancy and metameric mismatching. In accordance with the observations in study 2, achromatic adjustments revealed a bias towards bluish daylight illumination. This blue bias and naming consistency explained most of the variance in achromatic adjustments, while illumination discrimination was not directly related to colour constancy. The fourth study examined colour memory biases. Past research shows that colours of objects are remembered as being more saturated than they are perceived. These works often used natural objects that exist in a variety of colour and hue, such as grass or bananas. The approach presented here directly compared perceived and memorized colours for unique objects, used also in the first study, and confirmed the previous findings that on average, objects were remembered more saturated than they were perceived.Farbkonstanz beschreibt die FĂ€higkeit unseres visuellen Systems FarbeindrĂŒcke unter BeleuchtungsĂ€nderungen bestĂ€ndig zu halten. Dies ist eine außergewöhnliche Leistung, wenn man in Betracht zieht, dass in dem Lichtsignal welches das Auge erreicht Eigenschaften der Beleuchtung und der OberflĂ€chen konfundiert sind. Trotz dieser Problematik sind wir in unserem alltĂ€glichen Leben in der Lage Objekten stabile Farbnamen zuzuordnen, und damit unsere Kommunikation effizient und ökonomisch zu gestalten. Bisherige Studien zur Farbkonstanz berichten jedoch, dass Farbkonstanz nicht perfekt ist, Beleuchtungswechsel wurden nur zwischen 40-80% kompensiert. WĂ€hrend unterschiedliche Determinanten der Farbkonstanz vorgeschlagen wurden, konnte bisher keine sorgfĂ€ltig kontrollierte Studie perfekte Farbkonstanz zeigen. In der ersten Studie dieser Arbeit wurde dieser Aspekt untersucht, indem Farbkonstanz in einer hinweisreichen Umgebung unter Verwendung einer Aufgabe, die möglichst prĂ€zise unserer alltĂ€glichen Erfahrung im Umgang mit Farben wiederspiegelt, gemessen wurde. Die Versuchsteilnehmer wurden aufgefordert die Farbe eines spezifischen persönlichen Gegenstandes unter vier farbigen Beleuchtungen aus dem GedĂ€chtnis abzurufen. Unter Verwendung dieses Ansatzes konnte perfekte Farbkonstanz erreicht werden. Die zweite Studie untersuchte die Beziehung zwischen Beleuchtungs-Diskrimination und chromatischer Detektion. Die Ergebnisse von kĂŒrzlich veröffentlichten Forschungsarbeiten, welche ein Beleuchtungs-Diskriminations-Paradigma verwendeten, zeigen das diese Diskrimination in Richtung blĂ€ulicher Beleuchtung verzerrt ist. Daraus wurde geschlossen, das Farbkonstanz fĂŒr blĂ€uliche Tageslicht-Beleuchtungen optimiert ist . Da es aber nicht klar ist, ob Beleuchtungs-Diskrimination in direkter Beziehung zur Farbkonstanz steht, oder aber vielmehr auf die SensitivitĂ€t fĂŒr chromatische VerĂ€nderungen zurĂŒckfĂŒhren ist, wurden Wahrnehmungsschwellen fĂŒr Beleuchtungs-Diskrimination und chromatische Detektion fĂŒr die selben 12 Beleuchtungsfarben gemessen und verglichen. WĂ€hrend die bereits berichtete Verzerrung in Richtung der blĂ€ulichen Tageslichtbeleuchtung repliziert werden konnte, wurde ebenfalls eine hoher Zusammenhang zwischen chromatischer Detektion und Beleuchtungs-Diskrimination gefunden, welcher darauf hinweist, dass die Verzerrung in Richtung blĂ€ulicher Farben keine exklusive Eigenschaft der Beleuchtung-Diskrimination ist. AnknĂŒpfend an die zweite Studie wurde in der dritten Studie die Verteilung von Farbkonstanz ĂŒber 40 chromatische Beleuchtungen anhand von achromatischen Einstellungen und Farbbenennung untersucht. Farbkonstanz wurde auf ihren Zusammenhang zu mehreren Determinanten der Farbkonstanz ĂŒberprĂŒft, unter anderem mit Tageslichtvariationen, Farbkategorien, Beleuchtungs-Diskrimination, relationaler Farbkonstanz und metameric mismatching. In Übereinstimmung mit der zweiten Studie wurde auch fĂŒr achromatische Einstellungen eine Verzerrung in Richtung blĂ€ulicher Tageslichtbeleuchtungen gefunden. Diese Verzerrung und der Konsensus der Beleuchtungsbenennung erklĂ€rten den Großteil der Varianz der achromatischen Einstellungen, wĂ€hrend Beleuchtungs-Diskrimination nicht in direkter Verbindung zur Farbkonstanz stand. In der vierten Studie wurden Verzerrungen des FarbgedĂ€chtnisses untersucht. FrĂŒhere Studien berichten, dass Objektfarben hĂ€ufig gesĂ€ttigter erinnert werden als sie tatsĂ€chlich wahrgenommen werden. In diesen Studien wurden hĂ€ufig natĂŒrliche Objekte verwendet, die in einer Vielzahl an Farbtönen und SĂ€ttigungen existieren, wie beispielsweise Gras oder Bananen. In dem hier prĂ€sentierten Ansatz wurden Farbwahlen aus dem GedĂ€chtnis mit Farbwahlen der direkten Objektwahrnehmung fĂŒr persönliche, spezifische Objekte, die auch schon in der ersten Studie verwendet wurden, verglichen. Die Ergebnisse der vorherigen Studien konnten fĂŒr diese Objekte repliziert werden: Im Durchschnitt wurden Objektfarben gesĂ€ttigter erinnert als das Objekt im direkten Vergleich wahrgenommen wurde

    Plants Detection, Localization and Discrimination using 3D Machine Vision for Robotic Intra-row Weed Control

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    Weed management is vitally important in crop production systems. However, conventional herbicide-based weed control can lead to negative environmental impacts. Manual weed control is laborious and impractical for large scale production. Robotic weeding offers a possibility of controlling weeds precisely, particularly for weeds growing close to or within crop rows. The fusion of two-dimensional textural images and three-dimensional spatial images to recognize and localize crop plants at different growth stages were investigated. Images of different crop plants at different growth stages with weeds were acquired. Feature extraction algorithms were developed, and different features were extracted and used to train plant and background classifiers, which also addressed the problems of canopy occlusion and leaf damage. Then, the efficacy and accuracy of the proposed methods in classification were demonstrated by experiments. Currently, the algorithms were only developed and tested for broccoli and lettuce. For broccoli plants, the crop plants detection true positive rate was 93.1%, and the false discover rate was 1.1%, with the average crop-plant-localization error of 15.9 mm. For lettuce plants, the crop plants detection true positive rate was 92.3%, and the false discover rate was 4.0%, with the average crop-plant-localization error of 8.5 mm. The results have shown that 3D imaging based plant recognition algorithms are effective and reliable for crop/weed differentiation

    Evaluation and improvement of the workflow of digital imaging of fine art reproduction in museums

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    Fine arts refer to a broad spectrum of art formats, ie~painting, calligraphy, photography, architecture, and so forth. Fine art reproductions are to create surrogates of the original artwork that are able to faithfully deliver the aesthetics and feelings of the original. Traditionally, reproductions of fine art are made in the form of catalogs, postcards or books by museums, libraries, archives, and so on (hereafter called museums for simplicity). With the widespread adoption of digital archiving in museums, more and more artwork is reproduced to be viewed on a display. For example, artwork collections are made available through museum websites and Google Art Project for art lovers to view on their own displays. In the thesis, we study the fine art reproduction of paintings in the form of soft copy viewed on displays by answering four questions: (1) what is the impact of the viewing condition and original on image quality evaluation? (2) can image quality be improved by avoiding visual editing in current workflows of fine art reproduction? (3) can lightweight spectral imaging be used for fine art reproduction? and (4) what is the performance of spectral reproductions compared with reproductions by current workflows? We started with evaluating the perceived image quality of fine art reproduction created by representative museums in the United States under controlled and uncontrolled environments with and without the presence of the original artwork. The experimental results suggest that the image quality is highly correlated with the color accuracy of the reproduction only when the original is present and the reproduction is evaluated on a characterized display. We then examined the workflows to create these reproductions, and found that current workflows rely heavily on visual editing and retouching (global and local color adjustments on the digital reproduction) to improve the color accuracy of the reproduction. Visual editing and retouching can be both time-consuming and subjective in nature (depending on experts\u27 own experience and understanding of the artwork) lowering the efficiency of artwork digitization considerably. We therefore propose to improve the workflow of fine art reproduction by (1) automating the process of visual editing and retouching in current workflows based on RGB acquisition systems and by (2) recovering the spectral reflectance of the painting with off-the-shelf equipment under commonly available lighting conditions. Finally, we studied the perceived image quality of reproductions created by current three-channel (RGB) workflows with those by spectral imaging and those based on an exemplar-based method

    Color reproduction of CRT-displayed images as projected transparencies

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    This thesis evaluated the color appearance predictions of four digital color transforms (Hunt, RLAB, CIELAB, and von Kries) between CRT original images, viewed in a lighted room, and projected slides, viewed in the dark. Calibrated projection of these images required resolution of several complex issues. Upon projection, the slide colors changed. A rapid color shift (on the order of 75 seconds) was followed by a slower, steady degradation which also had to be minimized for accurate image presentation. Therefore, a model of the film behavior was based upon dye absorptivities and color measurements of slides as they were projected. The psychophysical experiments included a comparison between preference choices and memory matching to the CRT original. Two CRT white points were evaluated: D93 and D65. The preference choices were, in fact, distinct from the selected matches. RLAB produced statistically superior matches over any other model for both white points. Model performance was image dependent. Occasionally, CIELAB or von Kries images were equivalent to RLAB. However, CIELAB and von Kries predictions ranged widely in their performance. Hunt\u27s image predictions consistently gave the worst results. Interestingly, RLAB was also elected as the most acceptable choice: judged \u27acceptable\u27 in more than 2/3 of all cases, with a maximum approval of 89%

    Study of various metrics evaluating color quality of light sources

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    CIE (Commission Internationale del Eclairage) color rendering index (CRI) is the only internationally recognized and widely used metric to assess color rendering abilities of light sources. Despite its simplicity, CIE CRI has many shortcomings. These include outdated color space and outdated chromatic adaptation formula. CIE established technical committees several times to tackle the problems with CIE CRI. However, every committee was closed in five to ten years as they could not find a solution that every member would agree upon. One such committee formed by CIE in 2006 is CIE TC 1-69 (Color Rendition by White Light Sources). The aim of CIE TC 1-69 is to recommend new assessment procedures for assessing the color rendition properties of white-light source used for illumination. A wide variety of approaches have been proposed. Till now nine metrics have been submitted to CIE TC 1-69. Some of the proposed metrics address specific aspect of color rendition while other metrics try to intregate more than one aspects of color rendition. CIE is in the process of developing and recommending a new final metric. This work provides walk-through of various metrics to evaluate color quality of light sources. Altogether fourteen different metrics are discussed. This work also discusses how the new metrics will solve the limitations of CIE CRI

    Testing Colour-Appearance Models: Guidelines for Coordinated Research

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    These guidelines provide an overview of the many issues involved in generating visual data that can be used to evaluate the performance of colour-appearance models. the three main sections of these guidelines outline the parameters that must be evaluated and controlled in experimental setups for colour-appearance experiments, suggested psychophysical techniques for gathering the data, and some suggested techniques for data analysis. Experimental parameters addressed include models to be tested, illumination conditions, background and surround conditions, types of stimuli to be used, and issues relating to viewing technique. the psychophysical techniques of magnitude estimation, matching, and direct model testing (paired comparison) are described. Data analysis techniques for the evaluation of colour-appearance scales, corresponding-colours data, and model performance scales are suggested
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