Precise Color Communication
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Colors and Fillstyle
GraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphicsGraphics andandandandandandandandandandandandandandandandandandandandandandandandandandandandandand TTTTTTTTTTTTTTTTTTETETETETETXETXETXETXETXETXETXETXEXEXEXEXEXEXEXEXEXEXEXEXEXEXEXEXEXEXXXXX Ordinary colors More colors Colorful Fill—in style Custom colors From one color to another Tricks Online L Part II – Graphics AT EX Tutorial PSTricks c 2002, 2003, The Indian T This document is generated by hyperref, pstricks, pdftricks and pdfscreen packages on an intel and is released under EX Users Group The Indian T pc pdf running Floor lppl T Trivandrum 695014, EX with iii, sjp http://www.tug.org.in gnu/linux Buildings,EX Users Cotton HillsGroup india 1/19 Ordinary colors More colors Fill—in style Custom colors From one color to another 2. Colorful Tricks Seeing the (ps)tricks so far, at least some of you may be wishing for a bit of color in the graphics. Here’s good news for such people: you can have your wish! PSTricks comes with a set of macros that provide a basic set of colors Online LAT X Tutorial and lets you define your own colors. However, it has some incompatibility with E the LATEX package color. However, David Carlisle has written a package pstcol Part II – Graphics which modifies the PSTricks color interface to work with LATEX colors. All of our examples in this chapter assumes that this package is loaded, using the PSTricks command \usepackage{pstcol} in the preamble. Note that this loads the pstricks package also, so that it need not be separately loaded. c 2002, 2003, The Indian TEX Users Group This document is generated by pdfTEX with hyperref, pstricks, pdftricks and pdfscreen packages on an intel pc running gnu/linux and is released under lppl The Indian TEX Users Group Floor iii, sjp Buildings, Cotton Hills Trivandrum 695014, india http://www.tug.org.in 2/19 Colorful Tricks 2.1. -
Color Models
Color Models Jian Huang CS456 Main Color Spaces • CIE XYZ, xyY • RGB, CMYK • HSV (Munsell, HSL, IHS) • Lab, UVW, YUV, YCrCb, Luv, Differences in Color Spaces • What is the use? For display, editing, computation, compression, …? • Several key (very often conflicting) features may be sought after: – Additive (RGB) or subtractive (CMYK) – Separation of luminance and chromaticity – Equal distance between colors are equally perceivable CIE Standard • CIE: International Commission on Illumination (Comission Internationale de l’Eclairage). • Human perception based standard (1931), established with color matching experiment • Standard observer: a composite of a group of 15 to 20 people CIE Experiment CIE Experiment Result • Three pure light source: R = 700 nm, G = 546 nm, B = 436 nm. CIE Color Space • 3 hypothetical light sources, X, Y, and Z, which yield positive matching curves • Y: roughly corresponds to luminous efficiency characteristic of human eye CIE Color Space CIE xyY Space • Irregular 3D volume shape is difficult to understand • Chromaticity diagram (the same color of the varying intensity, Y, should all end up at the same point) Color Gamut • The range of color representation of a display device RGB (monitors) • The de facto standard The RGB Cube • RGB color space is perceptually non-linear • RGB space is a subset of the colors human can perceive • Con: what is ‘bloody red’ in RGB? CMY(K): printing • Cyan, Magenta, Yellow (Black) – CMY(K) • A subtractive color model dye color absorbs reflects cyan red blue and green magenta green blue and red yellow blue red and green black all none RGB and CMY • Converting between RGB and CMY RGB and CMY HSV • This color model is based on polar coordinates, not Cartesian coordinates. -
Estimation and Correction of the Distortion in Forensic Image Due to Rotation of the Photo Camera
Master Thesis Electrical Engineering February 2018 Master Thesis Electrical Engineering with emphasis on Signal Processing February 2018 Estimation and Correction of the Distortion in Forensic Image due to Rotation of the Photo Camera Sathwika Bavikadi Venkata Bharath Botta Department of Applied Signal Processing Blekinge Institute of Technology SE–371 79 Karlskrona, Sweden This thesis is submitted to the Department of Applied Signal Processing at Blekinge Institute of Technology in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering with Emphasis on Signal Processing. Contact Information: Author(s): Sathwika Bavikadi E-mail: [email protected] Venkata Bharath Botta E-mail: [email protected] Supervisor: Irina Gertsovich University Examiner: Dr. Sven Johansson Department of Applied Signal Processing Internet : www.bth.se Blekinge Institute of Technology Phone : +46 455 38 50 00 SE–371 79 Karlskrona, Sweden Fax : +46 455 38 50 57 Abstract Images, unlike text, represent an effective and natural communica- tion media for humans, due to their immediacy and the easy way to understand the image content. Shape recognition and pattern recog- nition are one of the most important tasks in the image processing. Crime scene photographs should always be in focus and there should be always be a ruler be present, this will allow the investigators the ability to resize the image to accurately reconstruct the scene. There- fore, the camera must be on a grounded platform such as tripod. Due to the rotation of the camera around the camera center there exist the distortion in the image which must be minimized. -
Review of Measures for Light-Source Color Rendition and Considerations for a Two-Measure System for Characterizing Color Rendition
Review of measures for light-source color rendition and considerations for a two-measure system for characterizing color rendition Kevin W. Houser,1,* Minchen Wei,1 Aurélien David,2 Michael R. Krames,2 and Xiangyou Sharon Shen3 1Department of Architectural Engineering, The Pennsylvania State University, University Park, PA, 16802, USA 2Soraa, Inc., Fremont, CA 94555, USA 3Inno-Solution Research LLC, 913 Ringneck Road, State College, PA 16801, USA *[email protected] Abstract: Twenty-two measures of color rendition have been reviewed and summarized. Each measure was computed for 401 illuminants comprising incandescent, light-emitting diode (LED) -phosphor, LED-mixed, fluorescent, high-intensity discharge (HID), and theoretical illuminants. A multidimensional scaling analysis (Matrix Stress = 0.0731, R2 = 0.976) illustrates that the 22 measures cluster into three neighborhoods in a two- dimensional space, where the dimensions relate to color discrimination and color preference. When just two measures are used to characterize overall color rendition, the most information can be conveyed if one is a reference- based measure that is consistent with the concept of color fidelity or quality (e.g., Qa) and the other is a measure of relative gamut (e.g., Qg). ©2013 Optical Society of America OCIS codes: (330.1690) Color; (330.1715) Color, rendering and metamerism; (230.3670) Light-emitting diodes. References and links 1. CIE, “Methods of measuring and specifying colour rendering properties of light sources,” in CIE 13 (CIE, Vienna, Austria, 1965). 2. W. Walter, “How meaningful is the CIE color rendering index?” Light Design Appl. 11(2), 13–15 (1981). 3. T. Seim, “In search of an improved method for assessing the colour rendering properties of light sources,” Lighting Res. -
Color Measurement1 Agr1c Ü8 ,
I A^w /\PK4 1946 USDA COLOR MEASUREMENT1 AGR1C ü8 , ,. 2001 DEC-1 f=> 7=50 AndA ItsT ApplicationA rL '"NT SERIAL Í to the Grading of Agricultural Products A HANDBOOK ON THE METHOD OF DISK COLORIMETRY ui By S3 DOROTHY NICKERSON, Color Technologist, Producdon and Marketing Administration 50! es tt^iSi as U. S. DEPARTMENT OF AGRICULTURE Miscellaneous Publication 580 March 1946 CONTENTS Page Introduction 1 Color-grading problems 1 Color charts in grading work 2 Transparent-color standards in grading work 3 Standards need measuring 4 Several methods of expressing results of color measurement 5 I.C.I, method of color notation 6 Homogeneous-heterogeneous method of color notation 6 Munsell method of color notation 7 Relation between methods 9 Disk colorimetry 10 Early method 22 Present method 22 Instruments 23 Choice of disks 25 Conversion to Munsell notation 37 Application of disk colorimetry to grading problems 38 Sample preparation 38 Preparation of conversion data 40 Applications of Munsell notations in related problems 45 The Kelly mask method for color matching 47 Standard names for colors 48 A.S.A. standard for the specification and description of color 50 Color-tolerance specifications 52 Artificial daylighting for grading work 53 Color-vision testing 59 Literature cited 61 666177—46- COLOR MEASUREMENT And Its Application to the Grading of Agricultural Products By DOROTHY NICKERSON, color technologist Production and Marketing Administration INTRODUCTION cotton, hay, butter, cheese, eggs, fruits and vegetables (fresh, canned, frozen, and dried), honey, tobacco, In the 16 years since publication of the disk method 3 1 cereal grains, meats, and rosin. -
Relationship of Solid Ink Density and Dot Gain in Digital Printing
International Journal of Engineering and Technical Research (IJETR) ISSN: 2321-0869, Volume-2, Issue-7, July 2014 Relationship of Solid Ink Density and Dot Gain in Digital Printing Vikas Jangra, Abhishek Saini, Anil Kundu gain while meeting density requirements. As discussed Abstract— Ours is the generation which is living in the age of above Dot gain is the measurement of the increase in tone science and technology. The latest scientific inventions have value from original file to the printed sheet. given rise to various technologies in every aspect of our life. Newer technologies have entered the field of printing also. II. MATERIALS AND METHODS Digital printing is one of these latest technologies which have further revolutionized entire modern printing industry in many Densitometer is used for measuring density of ink ways. It also facilitates working on large variety of surfaces, on the paper. Densitometer can be classified according to besides these factors digital printing have grown widely and type of materials they are designed to measure i.e. opaque made a special impact in print market. The presented analysis and transparent. Density of opaque materials is measured by system is used for study of print quality in Digital Printing. reflected light with a device called reflection type densitometer. Density of transparent materials is measured Index Terms— Digital Printing, Dot Gain, Solid ink density, by transmitted light with a device called transmission type Coated Paper and Uncoated Paper. densitometer. In order to measure the print quality i.e. solid ink density (SID) and dot gain (DG) on coated and uncoated I. -
Depth of Field in Photography
Instructor: N. David King Page 1 DEPTH OF FIELD IN PHOTOGRAPHY Handout for Photography Students N. David King, Instructor WWWHAT IS DDDEPTH OF FFFIELD ??? Photographers generally have to deal with one of two main optical issues for any given photograph: Motion (relative to the film plane) and Depth of Field. This handout is about Depth of Field. But what is it? Depth of Field is a major compositional tool used by photographers to direct attention to specific areas of a print or, at the other extreme, to allow the viewer’s eye to travel in focus over the entire print’s surface, as it appears to do in reality. Here are two example images. Depth of Field Examples Shallow Depth of Field Deep Depth of Field using wide aperture using small aperture and close focal distance and greater focal distance Depth of Field in PhotogPhotography:raphy: Student Handout © N. DavDavidid King 2004, Rev 2010 Instructor: N. David King Page 2 SSSURPRISE !!! The first image (the garden flowers on the left) was shot IIITTT’’’S AAALL AN ILLUSION with a wide aperture and is focused on the flower closest to the viewer. The second image (on the right) was shot with a smaller aperture and is focused on a yellow flower near the rear of that group of flowers. Though it looks as if we are really increasing the area that is in focus from the first image to the second, that apparent increase is actually an optical illusion. In the second image there is still only one plane where the lens is critically focused. -
Color Appearance Models Today's Topic
Color Appearance Models Arjun Satish Mitsunobu Sugimoto 1 Today's topic Color Appearance Models CIELAB The Nayatani et al. Model The Hunt Model The RLAB Model 2 1 Terminology recap Color Hue Brightness/Lightness Colorfulness/Chroma Saturation 3 Color Attribute of visual perception consisting of any combination of chromatic and achromatic content. Chromatic name Achromatic name others 4 2 Hue Attribute of a visual sensation according to which an area appears to be similar to one of the perceived colors Often refers red, green, blue, and yellow 5 Brightness Attribute of a visual sensation according to which an area appears to emit more or less light. Absolute level of the perception 6 3 Lightness The brightness of an area judged as a ratio to the brightness of a similarly illuminated area that appears to be white Relative amount of light reflected, or relative brightness normalized for changes in the illumination and view conditions 7 Colorfulness Attribute of a visual sensation according to which the perceived color of an area appears to be more or less chromatic 8 4 Chroma Colorfulness of an area judged as a ratio of the brightness of a similarly illuminated area that appears white Relationship between colorfulness and chroma is similar to relationship between brightness and lightness 9 Saturation Colorfulness of an area judged as a ratio to its brightness Chroma – ratio to white Saturation – ratio to its brightness 10 5 Definition of Color Appearance Model so much description of color such as: wavelength, cone response, tristimulus values, chromaticity coordinates, color spaces, … it is difficult to distinguish them correctly We need a model which makes them straightforward 11 Definition of Color Appearance Model CIE Technical Committee 1-34 (TC1-34) (Comission Internationale de l'Eclairage) They agreed on the following definition: A color appearance model is any model that includes predictors of at least the relative color-appearance attributes of lightness, chroma, and hue. -
Chromatic Adaptation Transform by Spectral Reconstruction Scott A
Chromatic Adaptation Transform by Spectral Reconstruction Scott A. Burns, University of Illinois at Urbana-Champaign, [email protected] February 28, 2019 Note to readers: This version of the paper is a preprint of a paper to appear in Color Research and Application in October 2019 (Citation: Burns SA. Chromatic adaptation transform by spectral reconstruction. Color Res Appl. 2019;44(5):682-693). The full text of the final version is available courtesy of Wiley Content Sharing initiative at: https://rdcu.be/bEZbD. The final published version differs substantially from the preprint shown here, as follows. The claims of negative tristimulus values being “failures” of a CAT are removed, since in some circumstances such as with “supersaturated” colors, it may be reasonable for a CAT to produce such results. The revised version simply states that in certain applications, tristimulus values outside the spectral locus or having negative values are undesirable. In these cases, the proposed method will guarantee that the destination colors will always be within the spectral locus. Abstract: A color appearance model (CAM) is an advanced colorimetric tool used to predict color appearance under a wide variety of viewing conditions. A chromatic adaptation transform (CAT) is an integral part of a CAM. Its role is to predict “corresponding colors,” that is, a pair of colors that have the same color appearance when viewed under different illuminants, after partial or full adaptation to each illuminant. Modern CATs perform well when applied to a limited range of illuminant pairs and a limited range of source (test) colors. However, they can fail if operated outside these ranges. -
The Trade-Off Between Image Resolution and Field of View: the Influence of Lens Selection
The Trade-off between Image Resolution and Field of View: the Influence of Lens Selection “I want a lens that can cover the whole parking lot and I want to be able to read a license plate.” Sound familiar? As a manufacturer of wide angle lenses, Theia Technologies is frequently asked if we have a product that allows the user to do both of these things simultaneously. And the answer is ‘it depends’. It depends on several variables - the resolution you start with from the camera, how far away the subject is from the lens, and the field of view of the lens. But keeping the first two variables constant, the impact of the lens field of view becomes clear. One of the important factors to consider when designing video surveillance installations is the trade-off between lens field of view and image resolution. Image Resolution versus Field of View One important, but often neglected consideration in video surveillance systems design is the trade-off between image resolution and field of view. With any given combination of camera and lens the native resolution from the camera is spread over the entire field of view of the lens, determining pixel density and image resolution. The wider the resolution is spread, the lower the pixel density, the lower the image resolution or image detail. The images below, taken with the same camera from the same distance away, illustrate this trade-off. The widest field of view allows you to cover the widest area but does not allow you to see high detail, while the narrowest field of view permits capture of high detail at the expense of wide area coverage. -
A Guide to Smartphone Astrophotography National Aeronautics and Space Administration
National Aeronautics and Space Administration A Guide to Smartphone Astrophotography National Aeronautics and Space Administration A Guide to Smartphone Astrophotography A Guide to Smartphone Astrophotography Dr. Sten Odenwald NASA Space Science Education Consortium Goddard Space Flight Center Greenbelt, Maryland Cover designs and editing by Abbey Interrante Cover illustrations Front: Aurora (Elizabeth Macdonald), moon (Spencer Collins), star trails (Donald Noor), Orion nebula (Christian Harris), solar eclipse (Christopher Jones), Milky Way (Shun-Chia Yang), satellite streaks (Stanislav Kaniansky),sunspot (Michael Seeboerger-Weichselbaum),sun dogs (Billy Heather). Back: Milky Way (Gabriel Clark) Two front cover designs are provided with this book. To conserve toner, begin document printing with the second cover. This product is supported by NASA under cooperative agreement number NNH15ZDA004C. [1] Table of Contents Introduction.................................................................................................................................................... 5 How to use this book ..................................................................................................................................... 9 1.0 Light Pollution ....................................................................................................................................... 12 2.0 Cameras ................................................................................................................................................ -
ARC Laboratory Handbook. Vol. 5 Colour: Specification and Measurement
Andrea Urland CONSERVATION OF ARCHITECTURAL HERITAGE, OFARCHITECTURALHERITAGE, CONSERVATION Colour Specification andmeasurement HISTORIC STRUCTURESANDMATERIALS UNESCO ICCROM WHC VOLUME ARC 5 /99 LABORATCOROY HLANODBOUOKR The ICCROM ARC Laboratory Handbook is intended to assist professionals working in the field of conserva- tion of architectural heritage and historic structures. It has been prepared mainly for architects and engineers, but may also be relevant for conservator-restorers or archaeologists. It aims to: - offer an overview of each problem area combined with laboratory practicals and case studies; - describe some of the most widely used practices and illustrate the various approaches to the analysis of materials and their deterioration; - facilitate interdisciplinary teamwork among scientists and other professionals involved in the conservation process. The Handbook has evolved from lecture and laboratory handouts that have been developed for the ICCROM training programmes. It has been devised within the framework of the current courses, principally the International Refresher Course on Conservation of Architectural Heritage and Historic Structures (ARC). The general layout of each volume is as follows: introductory information, explanations of scientific termi- nology, the most common problems met, types of analysis, laboratory tests, case studies and bibliography. The concept behind the Handbook is modular and it has been purposely structured as a series of independent volumes to allow: - authors to periodically update the