Color Concepts 101
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In Concert with Teaching Strategies That Have a Solid Theoretical Basis
1 www.onlineeducation.bharatsevaksamaj.net www.bssskillmission.in “Teaching and Learning Technology”. In Section 1 of this course you will cover these topics: Learning And Instruction Computer Applications In Education The Impact Of The Computer On Education Topic : Learning And Instruction Topic Objective: At the end of this topic student would be able to understand: Computer's Role In Instruction Instructional Technology Early Applications The Internet Era Outcomes Research Social Context Gagne's Nine Events of Instruction Definition/Overview: The first topic establishes a framework for looking at the computer's role in instruction and examines its role in student learning. A brief review of behaviorist and constructivist theories of instruction and learning is presented. The intent is to demonstrate that the computer can be a practical tool usedWWW.BSSVE.IN in concert with teaching strategies that have a solid theoretical basis. We recognize that thinking patterns and learning styles vary and that many different cognitive processes and intelligences should be valued. This topic presents a brief overview of types of intelligences, perception and motivation in order to emphasize the importance of analyzing student populations and matching instructional materials to student needs. Recognizing the important role that software plays in instruction and learning, a good deal of discussion takes place on the selection and evaluation of effective software. www.bsscommunitycollege.in www.bssnewgeneration.in www.bsslifeskillscollege.in 2 www.onlineeducation.bharatsevaksamaj.net www.bssskillmission.in Key Points: 1.Computer's Role in Instruction American education has long incorporated technology in K-12 classrooms tape recorders, televisions, calculators, computers, and many others. -
Pale Intrusions Into Blue: the Development of a Color Hannah Rose Mendoza
Florida State University Libraries Electronic Theses, Treatises and Dissertations The Graduate School 2004 Pale Intrusions into Blue: The Development of a Color Hannah Rose Mendoza Follow this and additional works at the FSU Digital Library. For more information, please contact [email protected] THE FLORIDA STATE UNIVERSITY SCHOOL OF VISUAL ARTS AND DANCE PALE INTRUSIONS INTO BLUE: THE DEVELOPMENT OF A COLOR By HANNAH ROSE MENDOZA A Thesis submitted to the Department of Interior Design in partial fulfillment of the requirements for the degree of Master of Fine Arts Degree Awarded: Fall Semester, 2004 The members of the Committee approve the thesis of Hannah Rose Mendoza defended on October 21, 2004. _________________________ Lisa Waxman Professor Directing Thesis _________________________ Peter Munton Committee Member _________________________ Ricardo Navarro Committee Member Approved: ______________________________________ Eric Wiedegreen, Chair, Department of Interior Design ______________________________________ Sally Mcrorie, Dean, School of Visual Arts & Dance The Office of Graduate Studies has verified and approved the above named committee members. ii To Pepe, te amo y gracias. iii ACKNOWLEDGMENTS I want to express my gratitude to Lisa Waxman for her unflagging enthusiasm and sharp attention to detail. I also wish to thank the other members of my committee, Peter Munton and Rick Navarro for taking the time to read my thesis and offer a very helpful critique. I want to acknowledge the support received from my Mom and Dad, whose faith in me helped me get through this. Finally, I want to thank my son Jack, who despite being born as my thesis was nearing completion, saw fit to spit up on the manuscript only once. -
Dell Ultrasharp Premiercolor Monitors Brochure (EN)
Dell UltraSharp PremierColor Monitors BRING YOUR VISION TO LIFE Engineered to meet the demands of creative professionals, Dell UltraSharp PremierColor Monitors push the boundaries of monitor technology to deliver exceptional performance that sets the standard for today’s digital creators. Choose Dell UltraSharp PremierColor monitors for the tools you need that help bring your vision to life. Learn more at Dell.com/UltraSharp See everything. Do anything. VISUALS THAT RIVAL REAL LIFE High resolution Dell See visuals with astounding clarity on UltraSharp PremierColor these high resolution monitors, up to Monitors set the standard Ultra HD 8K resolution. These monitors feature IPS (In-Plane Switching) panel technology for consistent color and picture for creative professionals. quality across a wide 178°/178° viewing angle. Count on a wide color gamut, incredible color THE COLORS YOU NEED depth, powerful calibration Dell UltraSharp PremierColor Monitors oer a wide color capabilities, and consistent, coverage across professional color spaces, including AdobeRGB, accurate colors. Bringing sRGB, Rec. 709, as well as the widest DCI-P3 color coverage in a professional monitor at 99.8%*. This enables support everything you need in a for projects across dierent formats, making UltraSharp monitor for all your color- PremierColor monitors the ideal choice for photographers, lm critical projects. and video creators, animators, VFX artists and more. Features vary by model. Please visit dell.com/monitors for details. Dell UltraSharp PremierColor Monitors INCREDIBLE COLOR DEPTH AND CONTRAST Get amazingly smooth color gradients and precision across more shades with an incredible color depth of 1.07 billion colors and true 10 bit color**. -
A Method of Content-Based Image Retrieval for the Generation of Image Mosaics
University of Central Florida STARS Electronic Theses and Dissertations, 2004-2019 2007 A Method Of Content-based Image Retrieval For The Generation Of Image Mosaics Michael Snead University of Central Florida Part of the Computer Engineering Commons Find similar works at: https://stars.library.ucf.edu/etd University of Central Florida Libraries http://library.ucf.edu This Masters Thesis (Open Access) is brought to you for free and open access by STARS. It has been accepted for inclusion in Electronic Theses and Dissertations, 2004-2019 by an authorized administrator of STARS. For more information, please contact [email protected]. STARS Citation Snead, Michael, "A Method Of Content-based Image Retrieval For The Generation Of Image Mosaics" (2007). Electronic Theses and Dissertations, 2004-2019. 3358. https://stars.library.ucf.edu/etd/3358 A METHOD OF CONTENT-BASED IMAGE RETRIEVAL FOR THE GENERATION OF IMAGE MOSAICS by MICHAEL CHRISTOPHER SNEAD B.S. University of Central Florida, 2005 A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the School of Electrical Engineering and Computer Science in the College of Engineering & Computer Science at the University of Central Florida Orlando, Florida Spring Term 2007 © 2007 Michael Christopher Snead ii ABSTRACT An image mosaic is an artistic work that uses a number of smaller images creatively combined together to form another larger image. Each building block image, or tessera, has its own distinctive and meaningful content, but when viewed from a distance the tesserae come together to form an aesthetically pleasing montage. This work presents the design and implementation of MosaiX, a computer software system that generates these image mosaics automatically. -
First Semester
NATIONAL UNIVERSITY F o u r t h Y e a r S y l l a b u s D e p a r t m e n t of Computer Science and Engineering Four Year B.Sc. Honours Course Effective from the Session: 2017–2018 National University Subject: Computer Science and Engineering Syllabus for Four Year B.Sc. Honours Course Effective from the Session: 2017-2018 Year wise courses and marks distribution FOURTH YEAR Semester VII Course Code Course Title Credit Hours 540201 Artificial Intelligence 3.0 540202 Artificial Intelligence Lab 1.5 540203 Compiler Design and Construction 3.0 540204 Compiler Design Lab 1.5 540205 Computer Graphics 3.0 540206 Computer Graphics Lab 1.5 540207 E-Commerce and Web Engineering 3.0 540208 E-Commerce and Web Engineering Lab 1.5 Total Credits in 7th Semester 18.0 Semester VIII Course Code Course Title Credit Hours Major Theory Courses 540209 Network and Information Security 3.0 540210 Network and Information Security Lab 1.5 540211 Information System Management 3.0 Project/Industry Attachment 540240 Project/Industry Attachment 6.0 Optional Course (any one) 3.0 540212 Simulation and Modeling 540214 Parallel and Distributed Systems 540216 Digital Signal Processing 540218 Digital Image Processing 540220 Multimedia 540222 Pattern Recognition 540224 Design and Analysis of VLSI Systems 540226 Micro-controller and Embedded System 540228 Cyber Law and Computer Forensic 540230 Natural Language Processing 540232 System Analysis and Design 540234 Optical Fiber Communication 540236 Human Computer Interaction 540238 Graph Theory Page 2 of 18 Optional Course -
Effects of Color Depth
EFFECTS OF COLOR DEPTH By Tom Kopin – CTS, ISF-C MARCH 2011 KRAMER WHITE PAPER WWW.KRAMERELECTRONICS.COM TABLE OF CONTENTS WHAT IS COLOR DEPTH? ...................................................................................1 DEEP COLOR ......................................................................................................1 CALCULATING HDMI BANDWIDTH ......................................................................1 BLU-RAY PLAYERS AND DEEP COLOR .................................................................3 THE SOLUTIONS .................................................................................................3 SUMMARY ..........................................................................................................4 The first few years of HDMI in ProAV have been, for lack of a better word, unpredictable. What works with one display doesn’t work with another. Why does HDMI go 50ft out of this source, but not that source? The list is endless and comments like this have almost become commonplace for HDMI, but why? Furthermore, excuses have been made in order to allow ambiguity to remain such as, "All Blu-ray players are not made equally, because their outputs must have different signal strength." However, is this the real reason? While the real answers may not truly be known, understanding how color depth quietly changes our HDMI signals will help make HDMI less unpredictable. What is Color Depth? Every HDMI signal has a color depth associated with it. Color depth defines how many different colors can be represented by each pixel of a HDMI signal. A normal HDMI signal has a color depth of 8 bits per color. This may also be referred to as 24-bit color (8-bits per color x 3 colors RGB). The number of bits refers to the amount of binary digits used to determine the maximum number of colors that can be rendered. For example, the maximum number of colors for 24-bit color would be: 111111111111111111111111(binary) = 16,777,215 = 16.7 million different colors. -
Working with Colors
Working With Colors INK: The physical form of color; Ink is how color is applied to paper There are two different types of inks: • TRANSPARENT INKS are commonly used in printing • OPAQUE INKS are considered a specialty ink and generally cost more COLOR: in printing, there are two types of color modes: • SPOT COLOR; aka: Match color, PMS color, Solid color • 4-COLOR PRocESS; aka: Process, CMYK Working With Colors With Working SPot COLOR • A pre-mixed color; a color mixed prior to the printing press PMS : PANtoNE MAtcHING SYSTEM • Color system that has several color libraries for reference in reproducing color • Popular PMS color libraries: • Spot color Formula guide (coated, uncoated, and matte versions) solid color guide that identifies specific colors • 4-Color Process Guide (coated and uncoated versions) identifies colors using CMYK inks • Color Bridge (coated and uncoated versions) using the colors from the spot color Formula guide this book shows the difference Working With Colors With Working between a spot color and the same color when converted to CMYK • Metallic Inks • Pastels • Tints • www.pantone.com COATED: Paper stock that has been treated with a special coating in order to have a glossy appearance. • Ink sits on this type of paper stock as a result of the glossy coating • Colors appear to be brighter compared to uncoated paper Matte: coated paper stock that has been dulled UNcoATED : Paper stock that has not been treated; it has no coating. • Ink is absorbed into this type of paper stock • Ink color appears darker and duller Working With Colors With Working BENEFit OF USING SPot coLOR: • consistent color within a print job. -
Chapter 2 Fundamentals of Digital Imaging
Chapter 2 Fundamentals of Digital Imaging Part 4 Color Representation © 2016 Pearson Education, Inc., Hoboken, 1 NJ. All rights reserved. In this lecture, you will find answers to these questions • What is RGB color model and how does it represent colors? • What is CMY color model and how does it represent colors? • What is HSB color model and how does it represent colors? • What is color gamut? What does out-of-gamut mean? • Why can't the colors on a printout match exactly what you see on screen? © 2016 Pearson Education, Inc., Hoboken, 2 NJ. All rights reserved. Color Models • Used to describe colors numerically, usually in terms of varying amounts of primary colors. • Common color models: – RGB – CMYK – HSB – CIE and their variants. © 2016 Pearson Education, Inc., Hoboken, 3 NJ. All rights reserved. RGB Color Model • Primary colors: – red – green – blue • Additive Color System © 2016 Pearson Education, Inc., Hoboken, 4 NJ. All rights reserved. Additive Color System © 2016 Pearson Education, Inc., Hoboken, 5 NJ. All rights reserved. Additive Color System of RGB • Full intensities of red + green + blue = white • Full intensities of red + green = yellow • Full intensities of green + blue = cyan • Full intensities of red + blue = magenta • Zero intensities of red , green , and blue = black • Same intensities of red , green , and blue = some kind of gray © 2016 Pearson Education, Inc., Hoboken, 6 NJ. All rights reserved. Color Display From a standard CRT monitor screen © 2016 Pearson Education, Inc., Hoboken, 7 NJ. All rights reserved. Color Display From a SONY Trinitron monitor screen © 2016 Pearson Education, Inc., Hoboken, 8 NJ. -
Colornet--Estimating Colorfulness in Natural Images
COLORNET - ESTIMATING COLORFULNESS IN NATURAL IMAGES Emin Zerman∗, Aakanksha Rana∗, Aljosa Smolic V-SENSE, School of Computer Science, Trinity College Dublin, Dublin, Ireland ABSTRACT learning-based objective metric ‘ColorNet’ for the estimation of colorfulness in natural images. Based on a convolutional neural Measuring the colorfulness of a natural or virtual scene is critical network (CNN), our proposed ColorNet is a two-stage color rating for many applications in image processing field ranging from captur- model, where at stage I, a feature network extracts the characteristics ing to display. In this paper, we propose the first deep learning-based features from the natural images and at stage II, a rating network colorfulness estimation metric. For this purpose, we develop a color estimates the colorfulness rating. To design our feature network, rating model which simultaneously learns to extracts the pertinent we explore the designs of the popular high-level CNN based fea- characteristic color features and the mapping from feature space to ture models such as VGG [22], ResNet [23], and MobileNet [24] the ideal colorfulness scores for a variety of natural colored images. architectures which we finally alter and tune for our colorfulness Additionally, we propose to overcome the lack of adequate annotated metric problem at hand. We also propose a rating network which dataset problem by combining/aligning two publicly available color- is simultaneously learned to estimate the relationship between the fulness databases using the results of a new subjective test which characteristic features and ideal colorfulness scores. employs a common subset of both databases. Using the obtained In this paper, we additionally overcome the challenge of the subjectively annotated dataset with 180 colored images, we finally absence of a well-annotated dataset for training and validating Col- demonstrate the efficacy of our proposed model over the traditional orNet model in a supervised manner. -
Computational RYB Color Model and Its Applications
IIEEJ Transactions on Image Electronics and Visual Computing Vol.5 No.2 (2017) -- Special Issue on Application-Based Image Processing Technologies -- Computational RYB Color Model and its Applications Junichi SUGITA† (Member), Tokiichiro TAKAHASHI†† (Member) †Tokyo Healthcare University, ††Tokyo Denki University/UEI Research <Summary> The red-yellow-blue (RYB) color model is a subtractive model based on pigment color mixing and is widely used in art education. In the RYB color model, red, yellow, and blue are defined as the primary colors. In this study, we apply this model to computers by formulating a conversion between the red-green-blue (RGB) and RYB color spaces. In addition, we present a class of compositing methods in the RYB color space. Moreover, we prescribe the appropriate uses of these compo- siting methods in different situations. By using RYB color compositing, paint-like compositing can be easily achieved. We also verified the effectiveness of our proposed method by using several experiments and demonstrated its application on the basis of RYB color compositing. Keywords: RYB, RGB, CMY(K), color model, color space, color compositing man perception system and computer displays, most com- 1. Introduction puter applications use the red-green-blue (RGB) color mod- Most people have had the experience of creating an arbi- el3); however, this model is not comprehensible for many trary color by mixing different color pigments on a palette or people who not trained in the RGB color model because of a canvas. The red-yellow-blue (RYB) color model proposed its use of additive color mixing. As shown in Fig. -
HD-SDI, HDMI, and Tempus Fugit
TECHNICALL Y SPEAKING... By Steve Somers, Vice President of Engineering HD-SDI, HDMI, and Tempus Fugit D-SDI (high definition serial digital interface) and HDMI (high definition multimedia interface) Hversion 1.3 are receiving considerable attention these days. “These days” really moved ahead rapidly now that I recall writing in this column on HD-SDI just one year ago. And, exactly two years ago the topic was DVI and HDMI. To be predictably trite, it seems like just yesterday. As with all things digital, there is much change and much to talk about. HD-SDI Redux difference channels suffice with one-half 372M spreads out the image information The HD-SDI is the 1.5 Gbps backbone the sample rate at 37.125 MHz, the ‘2s’ between the two channels to distribute of uncompressed high definition video in 4:2:2. This format is sufficient for high the data payload. Odd-numbered lines conveyance within the professional HD definition television. But, its robustness map to link A and even-numbered lines production environment. It’s been around and simplicity is pressing it into the higher map to link B. Table 1 indicates the since about 1996 and is quite literally the bandwidth demands of digital cinema and organization of 4:2:2, 4:4:4, and 4:4:4:4 savior of high definition interfacing and other uses like 12-bit, 4096 level signal data with respect to the available frame delivery at modest cost over medium-haul formats, refresh rates above 30 frames per rates. distances using RG-6 style video coax. -
Switchable Primaries Using Shiftable Layers of Color Filter Arrays
Switchable Primaries Using Shiftable Layers of Color Filter Arrays Behzad Sajadi ∗ Kazuhiro Hiwadaz Atsuto Makix Ramesh Raskar{ Aditi Majumdery Toshiba Corporation Toshiba Research Europe Camera Culture Group University of California, Irvine Cambridge Laboratory MIT Media Lab RGB Camera Our Camera Ground Truth Our Camera CMY Camera RGB Camera 8.14 15.87 Dark Scene sRGB Image 17.57 21.49 ∆E Difference ∆E Bright Scene CMY Camera Our Camera (2.36, 9.26, 1.96) (8.12, 29.30, 4.93) (7.51, 22.78, 4.39) Figure 1: Left: The CMY mode of our camera provides a superior SNR over a RGB camera when capturing a dark scene (top) and the RGB mode provides superior SNR over CMY camera when capturing a lighted scene. To demonstrate this, each image is marked with its quantitative SNR on the top left. Right: The RGBCY mode of our camera provides better color fidelity than a RGB or CMY camera for colorful scene (top). The DE deviation in CIELAB space of each of these images from a ground truth (captured using SOC-730 hyperspectral camera) is encoded as grayscale images with error statistics (mean, maximum and standard deviation) provided at the bottom of each image. Note the close match between the image captured with our camera and the ground truth. Abstract ment of the primaries in the CFA) to provide an optimal solution. We present a camera with switchable primaries using shiftable lay- We investigate practical design options for shiftable layering of the ers of color filter arrays (CFAs). By layering a pair of CMY CFAs in CFAs.