Digital image Levels of gray levels, quality: 1 byte = 8 bit 0 = Black

Slides:



Advertisements
Similar presentations
Chapter Eleven Digital Darkroom Expert Techniques.
Advertisements

Prénom Nom Document Analysis: Document Image Processing Prof. Rolf Ingold, University of Fribourg Master course, spring semester 2008.
Green Screen. Objectives: 2. Understand what the difference is between a Luma key and a Chroma key. By the end of todays lesson students will: 3. Understand.
An article by: Itay Bar-Yosef, Nate Hagbi, Klara Kedem, Itshak Dinstein Computer Science Department Ben-Gurion University Beer-Sheva, Israel Presented.
Image Enhancement To process an image so that the result is more suitable than the original image for a specific application. Spatial domain methods and.
Digital Image Processing, 2nd ed. © 2002 R. C. Gonzalez & R. E. Woods Chapter 12 Object Recognition Chapter 12 Object Recognition.
Working with Special Layer Functions
PREPARING PUBLICATIONS Using Color in Publications.
Creating Snow. Step 1 Begin opening an image on photoshop.
© 2011 Delmar, Cengage Learning Chapter 8 Working with Special Layer Functions.
Adobe Photoshop CS Design Professional LAYER FUNCTIONS WORKING WITH SPECIAL.
1 After completing this lesson, you will be able to: Identify the key differences between analog and digital technologies. Define digital camera terms,
Digital Image Processing Contrast Enhancement: Part I
COMPANY PUBLICATIONS Using Color in Publications.
Fingerprint Image Enhancement 程广权. Introduction Problems – Image contrast – Adverse physical factors Minimize the undesired effects Some intermediate.
Digital Image Processing, 3rd ed. © 1992–2008 R. C. Gonzalez & R. E. Woods Gonzalez & Woods Chapter 12 Object Recognition.
Digital Image Processing (DIP) Lecture # 5 Dr. Abdul Basit Siddiqui Assistant Professor-FURC 1FURC-BCSE7.
CSC/FAR 020, Computer Graphics, September 24, 2014 Dr. Dale E. Parson Outline for week 5.
Water Reflection Effect. Step 1: Duplicate The Background Layer.
Are you colour blind?
1 Eye Detection in Images Introduction To Computational and biological Vision Lecturer : Ohad Ben Shahar Written by : Itai Bechor.
EnvyLight: An interface for editing Natural Illumination Valentin JANIAUT Author: Fabio Pellacini (Darmouth College)
Photo Retouching Some concepts and approaches. Stages 1. Evaluation 2. Scanning 3. Big fixes first.. Cropping Adjusting 4.Get good blk & wht or Color.
HOW TO CROP PICTURE STEP 1.. Select the Basic Fixes tab and click on the Crop button.
Using Color in Publications. Color in a publication can: Elicit feelings Emphasize important text Attract attention Choose one or two colors Use “spot.
Masks and Channels Digital Imaging. Masks  Let you isolate and protect parts of an image  Based on a selection The area not selected is masked or protected.
Thresholding and Segmenting Objects The overall objective of image processing operations is to extract the objects of interest and to distinguish them.
Digital Image Processing Week V Thurdsak LEAUHATONG.
 Step 1 : First we need a background, I use this beautiful back-and-white photo, which has inspired me a lot:
 Step 1 Create a new Photoshop documents with the size 200 x 600px. Open up the image you wish to use as your reflection and copy and paste the image.
Image from
Compare and Contrast.
Lecture Six Figures from Gonzalez and Woods, Digital Image Processing, Second Edition, Copyright 2002.
Image Processing Objectives To understand pixel based image processing
How to Convert Pictures into Numbers
Watercolor and ink wash face tutorial
SELECTIVE COLOUR 1)Select one area and Image Adjustments black and White. Or 2)Right click Duplicate layer. Turn to black and white. Select one area and.
Using Color in Publications
Image Enhancement.
CIS 601 – 03 Image ENHANCEMENT SPATIAL DOMAIN Longin Jan Latecki
Images in Binary.
Histogram Histogram is a graph that shows frequency of anything. Histograms usually have bars that represent frequency of occuring of data. Histogram has.
Transform Color to Black & White Using the Channel Mixer
Fundamentals of Image Processing A Seminar on By Alok K. Watve
Two-Dimensional Signal and Image Processing Chapter 8 - pictures
Photo Album 2 by Your Name Set photo album to 1 picture per slide
Image Enhancement in the
Chapter 2: Digital Image Fundamentals
Chapter 2: Digital Image Fundamentals
CSC 381/481 Quarter: Fall 03/04 Daniela Stan Raicu
Image Processing Ch3: Intensity Transformation and spatial filters
COMS 161 Introduction to Computing
Lecture Four Chapter Three
Visual Literacy.
Edge Detection in Computer Vision
Happy Dussehra by Dr Nitin Paranjape.
(Large centered box here is 127/255. V = Vertical Size)
Cabunyag-fuerzas-agala-gaspar
Creating an Image Using a Text File
IT523 Digital Image Processing
The Image The pixels in the image The mask The resulting image 255 X
Intensity Transform Contrast Stretching Y ← u0+γ*(Y-u)/s
Statistical Operations
Morphological Operators
CSC/FAR 020, Computer Graphics, October 2, 2013
Successive contrast Simultaneous contrast
DIGITAL IMAGE PROCESSING Elective 3 (5th Sem.)
The “white gray sign.” Axial high-resolution 3D inversion recovery fast-spoiled gradient-echo T1-weighted image demonstrates decreased gray-white contrast.
CSC/FAR 020, Computer Graphics, October 5-7, 2009
Presentation transcript:

Digital image Levels of gray levels, quality: 1 byte = 8 bit 0 = Black 255 = White

Digital image Levels of gray levels, quality: 1 byte = 8 bit 0 = Black 255 = White

Basic transformations Reverse 0 = Black 255 = White

Basic transformations Brightness b = 100 0 = Black 255 = White

Basic transformations Contrast c = 1.3 0 = Black 255 = White

Image analysis Amplifier a = 100 0 = Black 255 = White

Image analysis Amplifier a = 200 0 = Black 255 = White a = 100

Image analysis Amplifier a = 255 0 = Black 255 = White a = 200

Image analysis Amplifier a = 128 0 = Black 255 = White

Image analysis Example: defect recognition a = 128 0 = Black 255 = White

Image analysis Center of gravity (mass center) 0 = Black 255 = White

Image analysis Center of gravity (mass center) 0 = Black 255 = White

Image analysis Bounds Foreground 0 = Black Part Background 255 = White Gradient Mask

Recognition of bounds Gradient f f

Recognition of points and lines Gradient x = 95 y = 90

Recognition of points and lines Gradient

Recognition of points and lines Gradient x = 200 y = 150

Recognition of points and lines Gradient x y

Recognition of points and lines Gradient

Recognition of points and lines Mask

Recognition of points and lines Mask