The Display pipeline. The fast forward version. The Display Pipeline The order may vary somewhat. The Graphics Pipeline. To draw images.

Size: px
Start display at page:

Download "The Display pipeline. The fast forward version. The Display Pipeline The order may vary somewhat. The Graphics Pipeline. To draw images."

Transcription

1 View volume The fast forward version The Display pipeline Computer Graphics 1, Fall 2004 Lecture 3 Chapter 1.4, 1.8, 2.5, 8.2, 8.13 Lightsource Hidden surface 3D Projection View plane 2D Rasterization Camera or observer Transformation Shadow Clipping The Graphics Pipeline Polygon in The Display Pipeline The order may vary somewhat... Transform Clipping HSR Light calculations... Modelling, create objects (this is not really a part of the pipeline) Transformations, move, scale, rotate View transformation, put yourself in the origin of the world Clipping, cut away things outside the view volume Hidden surface removal - We do not see through things Light and illumination, shadows perhaps Projection 3D to 2D Rasterization, put things onto our digital screen Texture, shading, image based HSR... To draw images To write the right numbers at the right places in this large array (the screen buffer) This is often done by a function called write_pixel(x,y,color) or (if possible) by directly writing in the array buffer[y][x]=color; Triangles Using write_pixel, we can draw lines and we can draw polygons Tessellation: cutting polygons into smaller polygons In fact, we need solely triangles Triangularisation: cutting polygons into triangles Triangles are always flat, which is a nice property Patrick Karlsson 1

2 Object in World We put our triangles together to form objects We put the objects in a 3D world We use a camera model to view the world Transformations, etc. We use transformations to move around in the world, as well as to move objects around in the world We add light to get a nice 3D effect We remove things we cannot see Fixing some more Visualization We may speedup things using maps of different types, e.g. textures Starting from polygons, it is tedious to build a world. We need modelling tools. Splines and fractals are two such tools COLOR Elements of color Patrick Karlsson 2

3 Color = The eye s and the brain s impression of electromagnetic radiation in the visual spectra. How is color perceived? Visible spectrum light source s( ) reflecting object r( ) detector rods & cones red-sensitive r() green-sensitive g() blue-sensitive b() The Fovea There are three types of cones, S, M and L Rods Sense luminance, or brightness, but not color. Are spread out across the whole retina, and dominate when the pupil is large, i.e. night vision. Less color is seen at night. The response is not linear, but logarithmic. The appearance of an object s intensity depends on the surroundings; the sensation is relative and not absolute. Three kinds of cones red-sensitive r() green-sensitive g() blue-sensitive b() CIE standard (Commission Internationale de L Eclairage, 1931) b=435.8nm wavelength r=700nm g=546.1nm In order to standardize the description of color, a large number of people were instructed to say what combination of basic colors a certain color sample consisted of in standard lighting. This resulted in the color matching curves, i.e. transform r(),(),() g b x(),(),() y z Patrick Karlsson 3

4 Color perception Different spectra can result in identical sensations, called metamers Color perception results from the simultaneous stimulation of 3 cone types (trichromat) Our perception of color is affected by surrounding effects and adaptation standard lightsource object reflectance CIE 1931 standard observer s( ) r( ) z x x y x = CIE XYZ values X=14.27 Y=14.31 Z= nm 700nm 400nm 700nm 400nm 700nm X = s( ) r( ) x( ) d Y = s( ) r( ) y( ) d Z = s( ) r( ) z( ) d Each color is represented by a point (X,Y,Z) in the 3D CIE color space. The point is called the tristimulus value. Projection of the CIE XYZ-space RGB/CMY color space Perceptual equal distances RGB - for additive color mixing, e.g. computer screen. CMY - for subtractive color mixing, e.g. printing or painting. RGB space RGB Three components: red (R) green (G) blue (B) Patrick Karlsson 4

5 Mixing light and mixing pigment Mixing light and mixing pigment Additive Subtractive green yellow yellow cyan red green red magenta blue magenta blue cyan R G B C M Y (K) R C G = M R+B+G=white (additive) R+G=Y [] B 1-[] Y C+M+Y=black (subtractive) C+M=B etc... (CMYK common in printing, where K is black pigment) RGB within CIE XYZ-space HLS color space Hue Lightness Saturation Hue=dominant wavelength, tone Lightness=intensity, brightness Saturation=purity, dilution by white Important aspects: Intensity decoupled from color Related to how humans perceive color HLS space L Hue (Swedish färgton ) Three components: hue (H) brightness (L) saturation (S) Limitation: if S ~ 0, then H undefined cyan green blue yellow H red magenta S Patrick Karlsson 5

6 HLS Segmentation of the H image YIQ color space Y= Lightness I= Inphase = amount red-green Q= Quadrature = amount blue-yellow Optimised for transmission (TV broadcast). Compatible with BW monitors (use only Y component) Human eye is more sensitive to variations in lightness than variations in hue and saturation and more bandwith (bits) is used for Y. NCS color description NCS=Natural Color System A psychological more than a physiological description of color. Common among artists, designers etc. 20 b w 2060-R50B= 20% white 60% black red with 50% blue c Color is relative Hjärnan är lättlurad grön lila gul blå svart It is easy to trick the brain green purple yellow blue black Patrick Karlsson 6

7 Non-existing colors (without use of psychadelic drugs) Blind spot; look at left cross with your right eye Color context Shape context Chromatic adaption Patrick Karlsson 7

8 Mach bands Gamma correction Most displays have non-linear intensity scales. The most common correction method is called gamma correction (usually implemented with a lookup table) Sometimes in computer graphics this effect is exaggerated to compensate for the adaptation of the eye. True-color frame buffer Indexed-color frame buffer Store R,G,B values directly in the frame buffer. Each pixel requires at least 3 bytes => 2^24 colors. Store index into a color map in the frame buffer. Each pixel requires at least 1 bytes => 2^8 simultaneous colors. Enables color-map animations. Different blending versions (how to combine color values) Additive blending C=A+B e.g. combining light Subtractive blending C=A-(1-B) e.g. filter effect Patrick Karlsson 8

9 Average blending C=(A+B)/2 or C=uA+vB e.g. for anti-aliasing Multiplicative blending C=A*B e.g. combining light and matter Patrick Karlsson 9

CS635 Spring Department of Computer Science Purdue University

CS635 Spring Department of Computer Science Purdue University Color and Perception CS635 Spring 2010 Daniel G Aliaga Daniel G. Aliaga Department of Computer Science Purdue University Elements of Color Perception 2 Elements of Color Physics: Illumination Electromagnetic

More information

Computer Graphics 1, Fall 2005

Computer Graphics 1, Fall 2005 Computer Graphics 1, Fall 2005 Computer Graphics 1, Fall 2005 Patrick Karlsson Ingela Nyström Erik Vidholm Anders Hast Filip Malmberg patrick@cb.uu.se ingela@cb.uu.se erik@cb.uu.se aht@hig.se filip@cb.uu.se

More information

3D graphics, raster and colors CS312 Fall 2010

3D graphics, raster and colors CS312 Fall 2010 Computer Graphics 3D graphics, raster and colors CS312 Fall 2010 Shift in CG Application Markets 1989-2000 2000 1989 3D Graphics Object description 3D graphics model Visualization 2D projection that simulates

More information

Reading. 2. Color. Emission spectra. The radiant energy spectrum. Watt, Chapter 15.

Reading. 2. Color. Emission spectra. The radiant energy spectrum. Watt, Chapter 15. Reading Watt, Chapter 15. Brian Wandell. Foundations of Vision. Chapter 4. Sinauer Associates, Sunderland, MA, pp. 69-97, 1995. 2. Color 1 2 The radiant energy spectrum We can think of light as waves,

More information

Computer Graphics. Bing-Yu Chen National Taiwan University The University of Tokyo

Computer Graphics. Bing-Yu Chen National Taiwan University The University of Tokyo Computer Graphics Bing-Yu Chen National Taiwan University The University of Tokyo Introduction The Graphics Process Color Models Triangle Meshes The Rendering Pipeline 1 What is Computer Graphics? modeling

More information

CSE 167: Lecture #6: Color. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2011

CSE 167: Lecture #6: Color. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2011 CSE 167: Introduction to Computer Graphics Lecture #6: Color Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2011 Announcements Homework project #3 due this Friday, October 14

More information

Lecture 12 Color model and color image processing

Lecture 12 Color model and color image processing Lecture 12 Color model and color image processing Color fundamentals Color models Pseudo color image Full color image processing Color fundamental The color that humans perceived in an object are determined

More information

Color and Shading. Color. Shapiro and Stockman, Chapter 6. Color and Machine Vision. Color and Perception

Color and Shading. Color. Shapiro and Stockman, Chapter 6. Color and Machine Vision. Color and Perception Color and Shading Color Shapiro and Stockman, Chapter 6 Color is an important factor for for human perception for object and material identification, even time of day. Color perception depends upon both

More information

The Elements of Colour

The Elements of Colour Color science 1 The Elements of Colour Perceived light of different wavelengths is in approximately equal weights achromatic.

More information

Fall 2015 Dr. Michael J. Reale

Fall 2015 Dr. Michael J. Reale CS 490: Computer Vision Color Theory: Color Models Fall 2015 Dr. Michael J. Reale Color Models Different ways to model color: XYZ CIE standard RB Additive Primaries Monitors, video cameras, etc. CMY/CMYK

More information

Game Programming. Bing-Yu Chen National Taiwan University

Game Programming. Bing-Yu Chen National Taiwan University Game Programming Bing-Yu Chen National Taiwan University What is Computer Graphics? Definition the pictorial synthesis of real or imaginary objects from their computer-based models descriptions OUTPUT

More information

Digital Image Processing COSC 6380/4393. Lecture 19 Mar 26 th, 2019 Pranav Mantini

Digital Image Processing COSC 6380/4393. Lecture 19 Mar 26 th, 2019 Pranav Mantini Digital Image Processing COSC 6380/4393 Lecture 19 Mar 26 th, 2019 Pranav Mantini What is color? Color is a psychological property of our visual experiences when we look at objects and lights, not a physical

More information

Lecture 1. Computer Graphics and Systems. Tuesday, January 15, 13

Lecture 1. Computer Graphics and Systems. Tuesday, January 15, 13 Lecture 1 Computer Graphics and Systems What is Computer Graphics? Image Formation Sun Object Figure from Ed Angel,D.Shreiner: Interactive Computer Graphics, 6 th Ed., 2012 Addison Wesley Computer Graphics

More information

Lecture 1 Image Formation.

Lecture 1 Image Formation. Lecture 1 Image Formation peimt@bit.edu.cn 1 Part 3 Color 2 Color v The light coming out of sources or reflected from surfaces has more or less energy at different wavelengths v The visual system responds

More information

Image Formation. Ed Angel Professor of Computer Science, Electrical and Computer Engineering, and Media Arts University of New Mexico

Image Formation. Ed Angel Professor of Computer Science, Electrical and Computer Engineering, and Media Arts University of New Mexico Image Formation Ed Angel Professor of Computer Science, Electrical and Computer Engineering, and Media Arts University of New Mexico 1 Objectives Fundamental imaging notions Physical basis for image formation

More information

CS452/552; EE465/505. Color Display Issues

CS452/552; EE465/505. Color Display Issues CS452/552; EE465/505 Color Display Issues 4-16 15 2 Outline! Color Display Issues Color Systems Dithering and Halftoning! Splines Hermite Splines Bezier Splines Catmull-Rom Splines Read: Angel, Chapter

More information

Image Formation. Camera trial #1. Pinhole camera. What is an Image? Light and the EM spectrum The H.V.S. and Color Perception

Image Formation. Camera trial #1. Pinhole camera. What is an Image? Light and the EM spectrum The H.V.S. and Color Perception Image Formation Light and the EM spectrum The H.V.S. and Color Perception What is an Image? An image is a projection of a 3D scene into a 2D projection plane. An image can be defined as a 2 variable function

More information

Lecture 11. Color. UW CSE vision faculty

Lecture 11. Color. UW CSE vision faculty Lecture 11 Color UW CSE vision faculty Starting Point: What is light? Electromagnetic radiation (EMR) moving along rays in space R(λ) is EMR, measured in units of power (watts) λ is wavelength Perceiving

More information

CSE 167: Lecture #6: Color. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2012

CSE 167: Lecture #6: Color. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2012 CSE 167: Introduction to Computer Graphics Lecture #6: Color Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2012 Announcements Homework project #3 due this Friday, October 19

More information

INTRODUCTION. Slides modified from Angel book 6e

INTRODUCTION. Slides modified from Angel book 6e INTRODUCTION Slides modified from Angel book 6e Fall 2012 COSC4328/5327 Computer Graphics 2 Objectives Historical introduction to computer graphics Fundamental imaging notions Physical basis for image

More information

Introduction to Computer Graphics with WebGL

Introduction to Computer Graphics with WebGL Introduction to Computer Graphics with WebGL Ed Angel Professor Emeritus of Computer Science Founding Director, Arts, Research, Technology and Science Laboratory University of New Mexico Image Formation

More information

Illumination and Shading

Illumination and Shading Illumination and Shading Light sources emit intensity: assigns intensity to each wavelength of light Humans perceive as a colour - navy blue, light green, etc. Exeriments show that there are distinct I

More information

National Chiao Tung Univ, Taiwan By: I-Chen Lin, Assistant Professor

National Chiao Tung Univ, Taiwan By: I-Chen Lin, Assistant Professor Computer Graphics 1. Graphics Systems National Chiao Tung Univ, Taiwan By: I-Chen Lin, Assistant Professor Textbook: Hearn and Baker, Computer Graphics, 3rd Ed., Prentice Hall Ref: E.Angel, Interactive

More information

Introduction to color science

Introduction to color science Introduction to color science Trichromacy Spectral matching functions CIE XYZ color system xy-chromaticity diagram Color gamut Color temperature Color balancing algorithms Digital Image Processing: Bernd

More information

Physical Color. Color Theory - Center for Graphics and Geometric Computing, Technion 2

Physical Color. Color Theory - Center for Graphics and Geometric Computing, Technion 2 Color Theory Physical Color Visible energy - small portion of the electro-magnetic spectrum Pure monochromatic colors are found at wavelengths between 380nm (violet) and 780nm (red) 380 780 Color Theory

More information

Computer Graphics. Bing-Yu Chen National Taiwan University

Computer Graphics. Bing-Yu Chen National Taiwan University Computer Graphics Bing-Yu Chen National Taiwan University Introduction The Graphics Process Color Models Triangle Meshes The Rendering Pipeline 1 INPUT What is Computer Graphics? Definition the pictorial

More information

(0, 1, 1) (0, 1, 1) (0, 1, 0) What is light? What is color? Terminology

(0, 1, 1) (0, 1, 1) (0, 1, 0) What is light? What is color? Terminology lecture 23 (0, 1, 1) (0, 0, 0) (0, 0, 1) (0, 1, 1) (1, 1, 1) (1, 1, 0) (0, 1, 0) hue - which ''? saturation - how pure? luminance (value) - intensity What is light? What is? Light consists of electromagnetic

More information

Visible Color. 700 (red) 580 (yellow) 520 (green)

Visible Color. 700 (red) 580 (yellow) 520 (green) Color Theory Physical Color Visible energy - small portion of the electro-magnetic spectrum Pure monochromatic colors are found at wavelengths between 380nm (violet) and 780nm (red) 380 780 Color Theory

More information

Light Transport Baoquan Chen 2017

Light Transport Baoquan Chen 2017 Light Transport 1 Physics of Light and Color It s all electromagnetic (EM) radiation Different colors correspond to radiation of different wavelengths Intensity of each wavelength specified by amplitude

More information

Color Vision. Spectral Distributions Various Light Sources

Color Vision. Spectral Distributions Various Light Sources Color Vision Light enters the eye Absorbed by cones Transmitted to brain Interpreted to perceive color Foundations of Vision Brian Wandell Spectral Distributions Various Light Sources Cones and Rods Cones:

More information

Survey in Computer Graphics Computer Graphics and Visualization

Survey in Computer Graphics Computer Graphics and Visualization Example of a Marble Ball Where did this image come from? Fall 2010 What hardware/software/algorithms did we need to produce it? 2 A Basic Graphics System History of Computer Graphics 1200-2008 Input devices

More information

Lecture 16 Color. October 20, 2016

Lecture 16 Color. October 20, 2016 Lecture 16 Color October 20, 2016 Where are we? You can intersect rays surfaces You can use RGB triples You can calculate illumination: Ambient, Lambertian and Specular But what about color, is there more

More information

Chapter 5 Extraction of color and texture Comunicação Visual Interactiva. image labeled by cluster index

Chapter 5 Extraction of color and texture Comunicação Visual Interactiva. image labeled by cluster index Chapter 5 Extraction of color and texture Comunicação Visual Interactiva image labeled by cluster index Color images Many images obtained with CCD are in color. This issue raises the following issue ->

More information

Lecture 2 5 Aug 2004

Lecture 2 5 Aug 2004 TOPICS in IT: ADVANCED GRAPHICS (CS & SE 233.420) Lecture 2 5 Aug 2004 1 Topics Image Formation Electromagnetic spectrum Light Human Visual Image processing Color Programming in OpenGL Background Programming

More information

CSE 167: Introduction to Computer Graphics Lecture #6: Colors. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2013

CSE 167: Introduction to Computer Graphics Lecture #6: Colors. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2013 CSE 167: Introduction to Computer Graphics Lecture #6: Colors Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2013 Announcements Homework project #3 due this Friday, October 18

More information

Colour computer vision: fundamentals, applications and challenges. Dr. Ignacio Molina-Conde Depto. Tecnología Electrónica Univ.

Colour computer vision: fundamentals, applications and challenges. Dr. Ignacio Molina-Conde Depto. Tecnología Electrónica Univ. Colour computer vision: fundamentals, applications and challenges Dr. Ignacio Molina-Conde Depto. Tecnología Electrónica Univ. of Málaga (Spain) Outline Part 1: colorimetry and colour perception: What

More information

Visualisatie BMT. Rendering. Arjan Kok

Visualisatie BMT. Rendering. Arjan Kok Visualisatie BMT Rendering Arjan Kok a.j.f.kok@tue.nl 1 Lecture overview Color Rendering Illumination 2 Visualization pipeline Raw Data Data Enrichment/Enhancement Derived Data Visualization Mapping Abstract

More information

CS5670: Computer Vision

CS5670: Computer Vision CS5670: Computer Vision Noah Snavely Light & Perception Announcements Quiz on Tuesday Project 3 code due Monday, April 17, by 11:59pm artifact due Wednesday, April 19, by 11:59pm Can we determine shape

More information

CS4670: Computer Vision

CS4670: Computer Vision CS4670: Computer Vision Noah Snavely Lecture 30: Light, color, and reflectance Light by Ted Adelson Readings Szeliski, 2.2, 2.3.2 Light by Ted Adelson Readings Szeliski, 2.2, 2.3.2 Properties of light

More information

Digital Image Processing

Digital Image Processing Digital Image Processing 7. Color Transforms 15110191 Keuyhong Cho Non-linear Color Space Reflect human eye s characters 1) Use uniform color space 2) Set distance of color space has same ratio difference

More information

Announcements. Lighting. Camera s sensor. HW1 has been posted See links on web page for readings on color. Intro Computer Vision.

Announcements. Lighting. Camera s sensor. HW1 has been posted See links on web page for readings on color. Intro Computer Vision. Announcements HW1 has been posted See links on web page for readings on color. Introduction to Computer Vision CSE 152 Lecture 6 Deviations from the lens model Deviations from this ideal are aberrations

More information

Light. Properties of light. What is light? Today What is light? How do we measure it? How does light propagate? How does light interact with matter?

Light. Properties of light. What is light? Today What is light? How do we measure it? How does light propagate? How does light interact with matter? Light Properties of light Today What is light? How do we measure it? How does light propagate? How does light interact with matter? by Ted Adelson Readings Andrew Glassner, Principles of Digital Image

More information

CS770/870 Spring 2017 Color and Shading

CS770/870 Spring 2017 Color and Shading Preview CS770/870 Spring 2017 Color and Shading Related material Cunningham: Ch 5 Hill and Kelley: Ch. 8 Angel 5e: 6.1-6.8 Angel 6e: 5.1-5.5 Making the scene more realistic Color models representing the

More information

this is processed giving us: perceived color that we actually experience and base judgments upon.

this is processed giving us: perceived color that we actually experience and base judgments upon. color we have been using r, g, b.. why what is a color? can we get all colors this way? how does wavelength fit in here, what part is physics, what part is physiology can i use r, g, b for simulation of

More information

Color. Phillip Otto Runge ( )

Color. Phillip Otto Runge ( ) Color Phillip Otto Runge (1777-1810) Overview The nature of color Color processing in the human visual system Color spaces Adaptation and constancy White balance Uses of color in computer vision What is

More information

Main topics in the Chapter 2. Chapter 2. Digital Image Representation. Bitmaps digitization. Three Types of Digital Image Creation CS 3570

Main topics in the Chapter 2. Chapter 2. Digital Image Representation. Bitmaps digitization. Three Types of Digital Image Creation CS 3570 Main topics in the Chapter Chapter. Digital Image Representation CS 3570 Three main types of creating digital images Bitmapping, Vector graphics, Procedural modeling Frequency in digital image Discrete

More information

CHAPTER 3 COLOR MEASUREMENT USING CHROMATICITY DIAGRAM - SOFTWARE

CHAPTER 3 COLOR MEASUREMENT USING CHROMATICITY DIAGRAM - SOFTWARE 49 CHAPTER 3 COLOR MEASUREMENT USING CHROMATICITY DIAGRAM - SOFTWARE 3.1 PREAMBLE Software has been developed following the CIE 1931 standard of Chromaticity Coordinates to convert the RGB data into its

More information

Reading. 4. Color. Outline. The radiant energy spectrum. Suggested: w Watt (2 nd ed.), Chapter 14. Further reading:

Reading. 4. Color. Outline. The radiant energy spectrum. Suggested: w Watt (2 nd ed.), Chapter 14. Further reading: Reading Suggested: Watt (2 nd ed.), Chapter 14. Further reading: 4. Color Brian Wandell. Foundations of Vision. Chapter 4. Sinauer Associates, Sunderland, MA, 1995. Gerald S. Wasserman. Color Vision: An

More information

Spectral Color and Radiometry

Spectral Color and Radiometry Spectral Color and Radiometry Louis Feng April 13, 2004 April 13, 2004 Realistic Image Synthesis (Spring 2004) 1 Topics Spectral Color Light and Color Spectrum Spectral Power Distribution Spectral Color

More information

Color to Binary Vision. The assignment Irfanview: A good utility Two parts: More challenging (Extra Credit) Lighting.

Color to Binary Vision. The assignment Irfanview: A good utility Two parts: More challenging (Extra Credit) Lighting. Announcements Color to Binary Vision CSE 90-B Lecture 5 First assignment was available last Thursday Use whatever language you want. Link to matlab resources from web page Always check web page for updates

More information

Lenses: Focus and Defocus

Lenses: Focus and Defocus Lenses: Focus and Defocus circle of confusion A lens focuses light onto the film There is a specific distance at which objects are in focus other points project to a circle of confusion in the image Changing

More information

Light. Computer Vision. James Hays

Light. Computer Vision. James Hays Light Computer Vision James Hays Projection: world coordinatesimage coordinates Camera Center (,, ) z y x X... f z y ' ' v u x. v u z f x u * ' z f y v * ' 5 2 ' 2* u 5 2 ' 3* v If X = 2, Y = 3, Z = 5,

More information

SNC 2PI Optics Unit Review /95 Name:

SNC 2PI Optics Unit Review /95 Name: SNC 2PI Optics Unit Review /95 Name: Part 1: True or False Indicate in the space provided if the statement is true (T) or false(f) [15] 1. Light is a form of energy 2. Shadows are proof that light travels

More information

Lighting. Camera s sensor. Lambertian Surface BRDF

Lighting. Camera s sensor. Lambertian Surface BRDF Lighting Introduction to Computer Vision CSE 152 Lecture 6 Special light sources Point sources Distant point sources Strip sources Area sources Common to think of lighting at infinity (a function on the

More information

Image Formation. CS418 Computer Graphics Eric Shaffer.

Image Formation. CS418 Computer Graphics Eric Shaffer. Image Formation CS418 Computer Graphics Eric Shaffer http://graphics.cs.illinois.edu/cs418/fa14 Some stuff about the class Grades probably on usual scale: 97 to 93: A 93 to 90: A- 90 to 87: B+ 87 to 83:

More information

Digital Image Processing. Introduction

Digital Image Processing. Introduction Digital Image Processing Introduction Digital Image Definition An image can be defined as a twodimensional function f(x,y) x,y: Spatial coordinate F: the amplitude of any pair of coordinate x,y, which

More information

Colour Reading: Chapter 6. Black body radiators

Colour Reading: Chapter 6. Black body radiators Colour Reading: Chapter 6 Light is produced in different amounts at different wavelengths by each light source Light is differentially reflected at each wavelength, which gives objects their natural colours

More information

Animation & Rendering

Animation & Rendering 7M836 Animation & Rendering Introduction, color, raster graphics, modeling, transformations Arjan Kok, Kees Huizing, Huub van de Wetering h.v.d.wetering@tue.nl 1 Purpose Understand 3D computer graphics

More information

Computer Graphics. Instructor: Oren Kapah. Office Hours: T.B.A.

Computer Graphics. Instructor: Oren Kapah. Office Hours: T.B.A. Computer Graphics Instructor: Oren Kapah (orenkapahbiu@gmail.com) Office Hours: T.B.A. The CG-IDC slides for this course were created by Toky & Hagit Hel-Or 1 CG-IDC 2 Exercise and Homework The exercise

More information

Image Processing. Color

Image Processing. Color Image Processing Color Material in this presentation is largely based on/derived from presentation(s) and book: The Digital Image by Dr. Donald House at Texas A&M University Brent M. Dingle, Ph.D. 2015

More information

CS 464 Review. Review of Computer Graphics for Final Exam

CS 464 Review. Review of Computer Graphics for Final Exam CS 464 Review Review of Computer Graphics for Final Exam Goal: Draw 3D Scenes on Display Device 3D Scene Abstract Model Framebuffer Matrix of Screen Pixels In Computer Graphics: If it looks right then

More information

ITP 140 Mobile App Technologies. Colors

ITP 140 Mobile App Technologies. Colors ITP 140 Mobile App Technologies Colors Colors in Photoshop RGB Mode CMYK Mode L*a*b Mode HSB Color Model 2 RGB Mode Based on the RGB color model Called an additive color model because adding all the colors

More information

CS6670: Computer Vision

CS6670: Computer Vision CS6670: Computer Vision Noah Snavely Lecture 21: Light, reflectance and photometric stereo Announcements Final projects Midterm reports due November 24 (next Tuesday) by 11:59pm (upload to CMS) State the

More information

Lecture #2: Color and Linear Algebra pt.1

Lecture #2: Color and Linear Algebra pt.1 Lecture #2: Color and Linear Algebra pt.1 John McNelly, Alexander Haigh, Madeline Saviano, Scott Kazmierowicz, Cameron Van de Graaf Department of Computer Science Stanford University Stanford, CA 94305

More information

Last update: May 4, Vision. CMSC 421: Chapter 24. CMSC 421: Chapter 24 1

Last update: May 4, Vision. CMSC 421: Chapter 24. CMSC 421: Chapter 24 1 Last update: May 4, 200 Vision CMSC 42: Chapter 24 CMSC 42: Chapter 24 Outline Perception generally Image formation Early vision 2D D Object recognition CMSC 42: Chapter 24 2 Perception generally Stimulus

More information

What is it? How does it work? How do we use it?

What is it? How does it work? How do we use it? What is it? How does it work? How do we use it? Dual Nature http://www.youtube.com/watch?v=dfpeprq7ogc o Electromagnetic Waves display wave behavior o Created by oscillating electric and magnetic fields

More information

Color Image Processing

Color Image Processing Color Image Processing Inel 5327 Prof. Vidya Manian Introduction Color fundamentals Color models Histogram processing Smoothing and sharpening Color image segmentation Edge detection Color fundamentals

More information

Pipeline Operations. CS 4620 Lecture 10

Pipeline Operations. CS 4620 Lecture 10 Pipeline Operations CS 4620 Lecture 10 2008 Steve Marschner 1 Hidden surface elimination Goal is to figure out which color to make the pixels based on what s in front of what. Hidden surface elimination

More information

Color. Reading: Optional reading: Chapter 6, Forsyth & Ponce. Chapter 4 of Wandell, Foundations of Vision, Sinauer, 1995 has a good treatment of this.

Color. Reading: Optional reading: Chapter 6, Forsyth & Ponce. Chapter 4 of Wandell, Foundations of Vision, Sinauer, 1995 has a good treatment of this. Today Color Reading: Chapter 6, Forsyth & Ponce Optional reading: Chapter 4 of Wandell, Foundations of Vision, Sinauer, 1995 has a good treatment of this. Feb. 17, 2005 MIT 6.869 Prof. Freeman Why does

More information

Why does a visual system need color? Color. Why does a visual system need color? (an incomplete list ) Lecture outline. Reading: Optional reading:

Why does a visual system need color? Color. Why does a visual system need color? (an incomplete list ) Lecture outline. Reading: Optional reading: Today Color Why does a visual system need color? Reading: Chapter 6, Optional reading: Chapter 4 of Wandell, Foundations of Vision, Sinauer, 1995 has a good treatment of this. Feb. 17, 2005 MIT 6.869 Prof.

More information

... Output System Layers. Application 2. Application 1. Application 3. Swing. UIKit SWT. Window System. Operating System

... Output System Layers. Application 2. Application 1. Application 3. Swing. UIKit SWT. Window System. Operating System Output: Hardware Output System Layers Application 1 Application 2 Application 3 Swing SWT... UIKit Window System Operating System Hardware (e.g., graphics card) 2 Output Hardware 3 Start with some basics:

More information

CS130 : Computer Graphics Lecture 2: Graphics Pipeline. Tamar Shinar Computer Science & Engineering UC Riverside

CS130 : Computer Graphics Lecture 2: Graphics Pipeline. Tamar Shinar Computer Science & Engineering UC Riverside CS130 : Computer Graphics Lecture 2: Graphics Pipeline Tamar Shinar Computer Science & Engineering UC Riverside Raster Devices and Images Raster Devices - raster displays show images as a rectangular array

More information

2003 Steve Marschner 7 Light detection discrete approx. Cone Responses S,M,L cones have broadband spectral sensitivity This sum is very clearly a dot

2003 Steve Marschner 7 Light detection discrete approx. Cone Responses S,M,L cones have broadband spectral sensitivity This sum is very clearly a dot 2003 Steve Marschner Color science as linear algebra Last time: historical the actual experiments that lead to understanding color strictly based on visual observations Color Science CONTD. concrete but

More information

Image Analysis and Formation (Formation et Analyse d'images)

Image Analysis and Formation (Formation et Analyse d'images) Image Analysis and Formation (Formation et Analyse d'images) James L. Crowley ENSIMAG 3 - MMIS Option MIRV First Semester 2010/2011 Lesson 4 19 Oct 2010 Lesson Outline: 1 The Physics of Light...2 1.1 Photons

More information

Graphics Hardware and Display Devices

Graphics Hardware and Display Devices Graphics Hardware and Display Devices CSE328 Lectures Graphics/Visualization Hardware Many graphics/visualization algorithms can be implemented efficiently and inexpensively in hardware Facilitates interactive

More information

CS6670: Computer Vision

CS6670: Computer Vision CS6670: Computer Vision Noah Snavely Lecture 20: Light, reflectance and photometric stereo Light by Ted Adelson Readings Szeliski, 2.2, 2.3.2 Light by Ted Adelson Readings Szeliski, 2.2, 2.3.2 Properties

More information

Pop Quiz 1 [10 mins]

Pop Quiz 1 [10 mins] Pop Quiz 1 [10 mins] 1. An audio signal makes 250 cycles in its span (or has a frequency of 250Hz). How many samples do you need, at a minimum, to sample it correctly? [1] 2. If the number of bits is reduced,

More information

Chapter 4 Color in Image and Video

Chapter 4 Color in Image and Video Chapter 4 Color in Image and Video 4.1 Color Science 4.2 Color Models in Images 4.3 Color Models in Video 4.4 Further Exploration 1 Li & Drew c Prentice Hall 2003 4.1 Color Science Light and Spectra Light

More information

Graphics Systems and Models

Graphics Systems and Models Graphics Systems and Models 2 nd Week, 2007 Sun-Jeong Kim Five major elements Input device Processor Memory Frame buffer Output device Graphics System A Graphics System 2 Input Devices Most graphics systems

More information

COMP3421. Global Lighting Part 2: Radiosity

COMP3421. Global Lighting Part 2: Radiosity COMP3421 Global Lighting Part 2: Radiosity Recap: Global Lighting The lighting equation we looked at earlier only handled direct lighting from sources: We added an ambient fudge term to account for all

More information

CSE 167: Lecture #7: Color and Shading. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2011

CSE 167: Lecture #7: Color and Shading. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2011 CSE 167: Introduction to Computer Graphics Lecture #7: Color and Shading Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2011 Announcements Homework project #3 due this Friday,

More information

OXFORD ENGINEERING COLLEGE (NAAC Accredited with B Grade) DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING LIST OF QUESTIONS

OXFORD ENGINEERING COLLEGE (NAAC Accredited with B Grade) DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING LIST OF QUESTIONS OXFORD ENGINEERING COLLEGE (NAAC Accredited with B Grade) DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING LIST OF QUESTIONS YEAR/SEM.: III/V STAFF NAME: T.ELANGOVAN SUBJECT NAME: Computer Graphics SUB. CODE:

More information

Midterm Exam CS 184: Foundations of Computer Graphics page 1 of 11

Midterm Exam CS 184: Foundations of Computer Graphics page 1 of 11 Midterm Exam CS 184: Foundations of Computer Graphics page 1 of 11 Student Name: Class Account Username: Instructions: Read them carefully! The exam begins at 2:40pm and ends at 4:00pm. You must turn your

More information

Scientific Visualization 1TD389, 5hp Fall 2012

Scientific Visualization 1TD389, 5hp Fall 2012 Department of Scientific Visualization 1TD389, 5hp Fall 2012 Visual Information Course start: Monday September 3 at 13:15 Room: P1211 Stefan Seipel, Professor Stefan.Seipel@it.uu.se 1 Frequently asked

More information

Global Illumination. Frank Dellaert Some slides by Jim Rehg, Philip Dutre

Global Illumination. Frank Dellaert Some slides by Jim Rehg, Philip Dutre Global Illumination Frank Dellaert Some slides by Jim Rehg, Philip Dutre Color and Radiometry What is color? What is Color? A perceptual attribute of objects and scenes constructed by the visual system

More information

TSBK 07! Computer Graphics! Ingemar Ragnemalm, ISY

TSBK 07! Computer Graphics! Ingemar Ragnemalm, ISY 1(46) Information Coding / Computer Graphics, ISY, LiTH TSBK 07 Computer Graphics Ingemar Ragnemalm, ISY 1(46) TSBK07 Computer Graphics Spring 2017 Course leader/examiner/lecturer: Ingemar Ragnemalm ingis@isy.liu.se

More information

Multimedia Databases. 2. Summary. 2 Color-based Retrieval. 2.1 Multimedia Data Retrieval. 2.1 Multimedia Data Retrieval 4/14/2016.

Multimedia Databases. 2. Summary. 2 Color-based Retrieval. 2.1 Multimedia Data Retrieval. 2.1 Multimedia Data Retrieval 4/14/2016. 2. Summary Multimedia Databases Wolf-Tilo Balke Younes Ghammad Institut für Informationssysteme Technische Universität Braunschweig http://www.ifis.cs.tu-bs.de Last week: What are multimedia databases?

More information

CS2401 COMPUTER GRAPHICS ANNA UNIV QUESTION BANK

CS2401 COMPUTER GRAPHICS ANNA UNIV QUESTION BANK CS2401 Computer Graphics CS2401 COMPUTER GRAPHICS ANNA UNIV QUESTION BANK CS2401- COMPUTER GRAPHICS UNIT 1-2D PRIMITIVES 1. Define Computer Graphics. 2. Explain any 3 uses of computer graphics applications.

More information

Computer Graphics Lecture 2

Computer Graphics Lecture 2 1 / 16 Computer Graphics Lecture 2 Dr. Marc Eduard Frîncu West University of Timisoara Feb 28th 2012 2 / 16 Outline 1 Graphics System Graphics Devices Frame Buffer 2 Rendering pipeline 3 Logical Devices

More information

Color and Light CSCI 4229/5229 Computer Graphics Fall 2016

Color and Light CSCI 4229/5229 Computer Graphics Fall 2016 Color and Light CSCI 4229/5229 Computer Graphics Fall 2016 Solar Spectrum Human Trichromatic Color Perception Color Blindness Present to some degree in 8% of males and about 0.5% of females due to mutation

More information

Spectral Adaptation. Chromatic Adaptation

Spectral Adaptation. Chromatic Adaptation Spectral Adaptation Mark D. Fairchild RIT Munsell Color Science Laboratory IS&T/SID 14th Color Imaging Conference Scottsdale 2006 Chromatic Adaptation Spectra-to-XYZ-to-LMS Chromatic adaptation models

More information

Visual areas in the brain. Image removed for copyright reasons.

Visual areas in the brain. Image removed for copyright reasons. Visual areas in the brain Image removed for copyright reasons. Image removed for copyright reasons. FOVEA OPTIC NERVE AQUEOUS HUMOR IRIS CORNEA PUPIL RETINA VITREOUS HUMOR LENS What do you see? Why? The

More information

Distributed Algorithms. Image and Video Processing

Distributed Algorithms. Image and Video Processing Chapter 5 Object Recognition Distributed Algorithms for Motivation Requirements Overview Object recognition via Colors Shapes (outlines) Textures Movements Summary 2 1 Why object recognition? Character

More information

Graphics for VEs. Ruth Aylett

Graphics for VEs. Ruth Aylett Graphics for VEs Ruth Aylett Overview VE Software Graphics for VEs The graphics pipeline Projections Lighting Shading VR software Two main types of software used: off-line authoring or modelling packages

More information

Digital Image Processing. Week 4

Digital Image Processing. Week 4 Morphological Image Processing Morphology deals with form and structure. Mathematical morphology is a tool for extracting image components that are useful in the representation and description of region

More information

Pick up Light Packet & Light WS

Pick up Light Packet & Light WS Pick up Light Packet & Light WS Only sit or stand at a station with a cup. Test or Quiz Make Ups Today/Tomorrow after School Only. Sound Test Corrections/Retakes: Wednesday, Next Tuesday, Wednesday, Thursday

More information

Module 3. Illumination Systems. Version 2 EE IIT, Kharagpur 1

Module 3. Illumination Systems. Version 2 EE IIT, Kharagpur 1 Module 3 Illumination Systems Version 2 EE IIT, Kharagpur 1 Lesson 14 Color Version 2 EE IIT, Kharagpur 2 Instructional Objectives 1. What are Primary colors? 2. How is color specified? 3. What is CRI?

More information

CS 111: Digital Image Processing Fall 2016 Midterm Exam: Nov 23, Pledge: I neither received nor gave any help from or to anyone in this exam.

CS 111: Digital Image Processing Fall 2016 Midterm Exam: Nov 23, Pledge: I neither received nor gave any help from or to anyone in this exam. CS 111: Digital Image Processing Fall 2016 Midterm Exam: Nov 23, 2016 Time: 3:30pm-4:50pm Total Points: 80 points Name: Number: Pledge: I neither received nor gave any help from or to anyone in this exam.

More information

Color. making some recognition problems easy. is 400nm (blue) to 700 nm (red) more; ex. X-rays, infrared, radio waves. n Used heavily in human vision

Color. making some recognition problems easy. is 400nm (blue) to 700 nm (red) more; ex. X-rays, infrared, radio waves. n Used heavily in human vision Color n Used heavily in human vision n Color is a pixel property, making some recognition problems easy n Visible spectrum for humans is 400nm (blue) to 700 nm (red) n Machines can see much more; ex. X-rays,

More information

SRM INSTITUTE OF SCIENCE AND TECHNOLOGY

SRM INSTITUTE OF SCIENCE AND TECHNOLOGY SRM INSTITUTE OF SCIENCE AND TECHNOLOGY DEPARTMENT OF INFORMATION TECHNOLOGY QUESTION BANK SUB.NAME: COMPUTER GRAPHICS SUB.CODE: IT307 CLASS : III/IT UNIT-1 2-marks 1. What is the various applications

More information