Lab 1. Basic Image Processing Algorithms Fall 2017

Size: px
Start display at page:

Download "Lab 1. Basic Image Processing Algorithms Fall 2017"

Transcription

1 Lab 1 Basic Image Processing Algorithms Fall 2017

2 Lab practices - Wednesdays 8:15-10:00, room 219: excercise leaders: Csaba Benedek, Balázs Nagy instructor: Péter Bogdány 8:15-10:00, room 220: excercise leader: Miklós Koller instructor: Ágnes Szabó 10:15-12:00, room 422: excercise leader: Márton Bese Naszlady instructor: Bendegúz Tamás Módli 2

3 Lab practices - requirements the attendance is obligatory; there will be a programming task that you have to complete and submit to an SVN server; you have to understand your code and be able to explain it; if you are unable to finish until the end of the lab practice, you have to finish it at home and submit before the next Tuesday s 23:59; (except today) submitting all tasks in time is a requirement of passing the course. To have account on the SVN server: please fill the following form NOW: 3

4 Lab 1: revising MATLAB 7 exercises will be given; the usage of these matlab commands should be confident during the rest of the semester. The SVN repository will be created at the beginning of the next week: please bring your solution of Lab1 with yourself to the next class (next lab, 27 Sept.), and we will upload it together to the SVN server. To have SVN-client at home: please install Tortoise SVN. 4

5 Test images for the course All of the test images used for the following tasks can be found at: 5

6 Exercise 1 Create a function that: reads in a colored image (use imread()), displays it with imshow(), check if the input image has 3 channels (use size()), converts it to grayscale (use rgb2gray()), displays the grayscale image, save the gray image (with imwrite()), the parameters of this function should be as follows: input1: path to the image file; input2: output file path; output: grayscale image (as an array). Create a script that: calls the previously written function with the appropriate parameters (eg. AlfredoBorba_TuscanLandscape.jpg), displays with imshow() the returned image. 6

7 Exercise 2 Create a function that: reads in a colored image, rotates it with 45 degrees (imrotate), flips the image vertically (flipud), flips the image horizontally (fliplr), saves all the images (name is the original name with postfix, use fileparts), before saving check the existence of the output dir (exist(some_path, 'dir')), parameters: input1: path to the image file, input2: absolute path of the output folder, output1: array of the rotated image, output2: array of the vertically flipped image, output3: array of the horizontally flipped image. 7

8 Exercise 2 Create a script that: calls the previously written function with the appropriate parameters, displays the returned images in one figure, with multiple subplot-s (output parameters): 8

9 Exercise 3 Create a function that: reads in a colored image, mixes up channel R with channel B (do it pixel-by-pixel with a for loop), measures the runtime with tic/toc, and prints it with disp, saves the image (name is the original name with postfix, use fileparts), parameters: input1: path to the image file, input2: absolute path of the output folder, output1: array of the mixed up image, implements the channel mix-up without for loop (think about the colon operator : at the array-indexing), and measure the runtime again. 9

10 Exercise 3 Create a script that: calls the previously written function with the appropriate parameters, displays the returned image: 10

11 Exercise 4 Create a function that: reads in an image, converts it to grayscale if necessary, binarizes the image with a threshold (each pixel above the threshold will become white and the others black), saves the image with an appropriate postfix, parameters: input1: path to the image file, input2: absolute path of the output folder, input3: threshold (if there is no 3rd input use the mean intensity level as threshold; to check the input parameters use varargin), output1: binary image. Create a script that: calls the previously written function with the appropriate parameters, displays the returned image. 11

12 Exercise 5 Create a function that: reads in an image, converts it to grayscale if necessary, creates a 10 pixel wide border for the image: create a matrix that is 20 pixel larger in both dimensions (use ones()), and place the image in the middle, saves the image with an appropriate postfix, parameters: input1: path to the image file, input2: absolute path of the output folder, output1: array of the framed image. Create a script that: calls the previously written function with the appropriate parameters, displays the returned image. 12

13 Exercise 6 Create a function that: reads in an image, converts it to grayscale if necessary, displays the image in the upper subplot of a figure, plots the pixel intensity values of the i-th row of the image (use plot function) in the lower subplot of a figure, puts labels on the axis (xlabel, ylabel, title), saves the figure (saveas) with an appropriate postfix, parameters: input1: path to the image file, input2: absolute path of the output folder, input3: value of i (which row to plot), input4: optionally index for an other row --- plot this other row as well with a different color, use hold on/off and varargin, no output. 13

14 Exercise 6 Create a script that: calls the previously written function with the appropriate parameters. 14

15 Exercise 7 Create a function that: reads in 2 images, converts them to grayscale if necessary, converts them into the same size (imresize), creates a 3D array of one image fading into the other (3rd dim: time), parameters: input1: path to the first image file, input2: path to the second image file, input3: number of frames to create, output: the 3D transition array At the generation of the individual frames, you have to think about the type-conversions (double, uint8). 15

16 Exercise 7 Create a script that: calls the previously written function with the appropriate parameters, displays the video with the built-in implay() function. 16

Matlab for CS6320 Beginners

Matlab for CS6320 Beginners Matlab for CS6320 Beginners Basics: Starting Matlab o CADE Lab remote access o Student version on your own computer Change the Current Folder to the directory where your programs, images, etc. will be

More information

EGR 111 Image Processing

EGR 111 Image Processing EGR 111 Image Processing This lab shows how MATLAB can represent and manipulate images. New MATLAB Commands: imread, imshow, imresize, rgb2gray Resources (available on course website): secret_image.bmp

More information

CS/NEUR125 Brains, Minds, and Machines. Due: Wednesday, February 8

CS/NEUR125 Brains, Minds, and Machines. Due: Wednesday, February 8 CS/NEUR125 Brains, Minds, and Machines Lab 2: Human Face Recognition and Holistic Processing Due: Wednesday, February 8 This lab explores our ability to recognize familiar and unfamiliar faces, and the

More information

MATLAB Image Processing Toolbox

MATLAB Image Processing Toolbox MATLAB Image Processing Toolbox Copyright: Mathworks 1998. The following is taken from the Matlab Image Processing Toolbox users guide. A complete online manual is availabe in the PDF form (about 5MB).

More information

Digital Image processing Lab

Digital Image processing Lab Digital Image processing Lab Islamic University Gaza Engineering Faculty Department of Computer Engineering 2013 EELE 5110: Digital Image processing Lab Eng. Ahmed M. Ayash Lab # 2 Basic Image Operations

More information

Brief Introduction to Vision and Images

Brief Introduction to Vision and Images Brief Introduction to Vision and Images Charles S. Tritt, Ph.D. January 24, 2012 Version 1.1 Structure of the Retina There is only one kind of rod. Rods are very sensitive and used mainly in dim light.

More information

DSP First Lab 06: Digital Images: A/D and D/A

DSP First Lab 06: Digital Images: A/D and D/A DSP First Lab 06: Digital Images: A/D and D/A Pre-Lab and Warm-Up: You should read at least the Pre-Lab and Warm-up sections of this lab assignment and go over all exercises in the Pre-Lab section before

More information

EELE 5110 Digital Image Processing Lab 02: Image Processing with MATLAB

EELE 5110 Digital Image Processing Lab 02: Image Processing with MATLAB Prepared by: Eng. AbdAllah M. ElSheikh EELE 5110 Digital Image Processing Lab 02: Image Processing with MATLAB Welcome to the labs for EELE 5110 Image Processing Lab. This lab will get you started with

More information

MatLab for biologists

MatLab for biologists MatLab for biologists Lecture 5 Péter Horváth Light Microscopy Centre ETH Zurich peter.horvath@lmc.biol.ethz.ch May 5, 2008 1 1 Reading and writing tables with MatLab (.xls,.csv, ASCII delimited) MatLab

More information

A PROPOSED ALGORITHM FOR DIGITAL WATERMARKING

A PROPOSED ALGORITHM FOR DIGITAL WATERMARKING A PROPOSED ALGORITHM FOR DIGITAL WATERMARKING Dr. Mohammed F. Al-Hunaity dr_alhunaity@bau.edu.jo Meran M. Al-Hadidi Merohadidi77@gmail.com Dr.Belal A. Ayyoub belal_ayyoub@ hotmail.com Abstract: This paper

More information

Lecture 1: Introduction to Matlab Programming

Lecture 1: Introduction to Matlab Programming What is Matlab? Lecture 1: Introduction to Matlab Programming Math 490 Prof. Todd Wittman The Citadel Matlab stands for. Matlab is a programming language optimized for linear algebra operations. It is

More information

ECE 619: Computer Vision Lab 1: Basics of Image Processing (Using Matlab image processing toolbox Issued Thursday 1/10 Due 1/24)

ECE 619: Computer Vision Lab 1: Basics of Image Processing (Using Matlab image processing toolbox Issued Thursday 1/10 Due 1/24) ECE 619: Computer Vision Lab 1: Basics of Image Processing (Using Matlab image processing toolbox Issued Thursday 1/10 Due 1/24) Task 1: Execute the steps outlined below to get familiar with basics of

More information

MATLAB 6.5 Image Processing Toolbox Tutorial

MATLAB 6.5 Image Processing Toolbox Tutorial MATLAB 6.5 Image Processing Toolbox Tutorial The purpose of this tutorial is to gain familiarity with MATLAB s Image Processing Toolbox. This tutorial does not contain all of the functions available in

More information

L2. Image processing in MATLAB

L2. Image processing in MATLAB L2. Image processing in MATLAB 1. Introduction MATLAB environment offers an easy way to prototype applications that are based on complex mathematical computations. This annex presents some basic image

More information

Lab P-8: Digital Images: A/D and D/A

Lab P-8: Digital Images: A/D and D/A DSP First, 2e Signal Processing First Lab P-8: Digital Images: A/D and D/A Pre-Lab: Read the Pre-Lab and do all the exercises in the Pre-Lab section prior to attending lab. Verification: The Warm-up section

More information

Introduction to DSP ECE-S352 Fall Quarter 2000 Matlab Project 1

Introduction to DSP ECE-S352 Fall Quarter 2000 Matlab Project 1 Objective: Introduction to DSP ECE-S352 Fall Quarter 2000 Matlab Project 1 This Matlab Project is an extension of the basic correlation theory presented in the course. It shows a practical application

More information

Image processing in MATLAB. Linguaggio Programmazione Matlab-Simulink (2017/2018)

Image processing in MATLAB. Linguaggio Programmazione Matlab-Simulink (2017/2018) Image processing in MATLAB Linguaggio Programmazione Matlab-Simulink (2017/2018) Images in MATLAB MATLAB can import/export several image formats BMP (Microsoft Windows Bitmap) GIF (Graphics Interchange

More information

EP375 Computational Physics

EP375 Computational Physics EP375 Computational Physics Topic 13 IMAGE PROCESSING Department of Engineering Physics University of Gaziantep Apr 2016 Sayfa 1 Content 1. Introduction 2. Nature of Image 3. Image Types / Colors 4. Reading,

More information

6.098/6.882 Computational Photography 1. Problem Set 1. Assigned: Feb 9, 2006 Due: Feb 23, 2006

6.098/6.882 Computational Photography 1. Problem Set 1. Assigned: Feb 9, 2006 Due: Feb 23, 2006 6.098/6.882 Computational Photography 1 Problem Set 1 Assigned: Feb 9, 2006 Due: Feb 23, 2006 Note The problems marked with 6.882 only are for the students who register for 6.882. (Of course, students

More information

Mech 296: Vision for Robotic Applications. Vision for Robotic Applications

Mech 296: Vision for Robotic Applications. Vision for Robotic Applications Mech 296: Vision for Robotic Applications Lecture 1: Monochrome Images 1.1 Vision for Robotic Applications Instructors, jrife@engr.scu.edu Jeff Ota, jota@scu.edu Class Goal Design and implement a vision-based,

More information

CS Game Programming, Fall 2014

CS Game Programming, Fall 2014 CS 38101 Game Programming, Fall 2014 Recommended Text Learn Unity 4 for ios Game Development, Philip Chu, 2013, Apress, ISBN-13 (pbk): 978-1-4302-4875-0 ISBN-13 (electronic): 978-1-4302-4876-7, www.apress.com.

More information

We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists. International authors and editors

We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists. International authors and editors We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists 3,900 116,000 120M Open access books available International authors and editors Downloads Our

More information

Implementing Sobel & Canny Edge Detection Algorithms

Implementing Sobel & Canny Edge Detection Algorithms Implementing Sobel & Canny Edge Detection Algorithms And comparing the results with built-in functions of Matlab Ariyan Zarei 2/23/2017 Abstract This is the report for the second project of the Image Processing

More information

Data Analysis in MATLAB Lab 1: The speed limit of the nervous system (comparative conduction velocity)

Data Analysis in MATLAB Lab 1: The speed limit of the nervous system (comparative conduction velocity) Data Analysis in MATLAB Lab 1: The speed limit of the nervous system (comparative conduction velocity) Importing Data into MATLAB Change your Current Folder to the folder where your data is located. Import

More information

Computer Programming ECIV 2303 Chapter 5 Two-Dimensional Plots Instructor: Dr. Talal Skaik Islamic University of Gaza Faculty of Engineering

Computer Programming ECIV 2303 Chapter 5 Two-Dimensional Plots Instructor: Dr. Talal Skaik Islamic University of Gaza Faculty of Engineering Computer Programming ECIV 2303 Chapter 5 Two-Dimensional Plots Instructor: Dr. Talal Skaik Islamic University of Gaza Faculty of Engineering 1 Introduction Plots are a very useful tool for presenting information.

More information

Princeton ELE 201, Spring 2014 Laboratory No. 2 Shazam

Princeton ELE 201, Spring 2014 Laboratory No. 2 Shazam Princeton ELE 201, Spring 2014 Laboratory No. 2 Shazam 1 Background In this lab we will begin to code a Shazam-like program to identify a short clip of music using a database of songs. The basic procedure

More information

International Journal of Advance Engineering and Research Development. Implementation of Digital Image Basic and Editing functions using MATLAB

International Journal of Advance Engineering and Research Development. Implementation of Digital Image Basic and Editing functions using MATLAB Scientific Journal of Impact Factor(SJIF): 3.134 e-issn(o): 2348-4470 p-issn(p): 2348-6406 International Journal of Advance Engineering and Research Development Volume 2,Issue 6, June -2015 Implementation

More information

Finger print Recognization. By M R Rahul Raj K Muralidhar A Papi Reddy

Finger print Recognization. By M R Rahul Raj K Muralidhar A Papi Reddy Finger print Recognization By M R Rahul Raj K Muralidhar A Papi Reddy Introduction Finger print recognization system is under biometric application used to increase the user security. Generally the biometric

More information

Play with image files 2-dimensional array matrix

Play with image files 2-dimensional array matrix Previous class: Play with sound files Practice working with vectors Now: Play with image files 2-dimensional array matrix A picture as a matrix 2-dimensional array 1458-by-2084 150 149 152 153 152 155

More information

Lab S-4: Convolution & FIR Filters. Please read through the information below prior to attending your lab.

Lab S-4: Convolution & FIR Filters. Please read through the information below prior to attending your lab. DSP First, 2e Signal Processing First Lab S-4: Convolution & FIR Filters Pre-Lab: Read the Pre-Lab and do all the exercises in the Pre-Lab section prior to attending lab. Verification: The Exercise section

More information

ECE 5670/6670 Lab 7 Brushless DC Motor Control with 6-Step Commutation. Objectives

ECE 5670/6670 Lab 7 Brushless DC Motor Control with 6-Step Commutation. Objectives ECE 5670/6670 Lab 7 Brushless DC Motor Control with 6-Step Commutation Objectives The objective of the lab is to implement a 6-step commutation scheme for a brushless DC motor in simulations, and to expand

More information

Contents. An introduction to MATLAB for new and advanced users

Contents. An introduction to MATLAB for new and advanced users An introduction to MATLAB for new and advanced users (Using Two-Dimensional Plots) Contents Getting Started Creating Arrays Mathematical Operations with Arrays Using Script Files and Managing Data Two-Dimensional

More information

Image representation, sampling and quantization

Image representation, sampling and quantization Image representation, sampling and quantization António R. C. Paiva ECE 6962 Fall 2010 Lecture outline Image representation Digitalization of images Changes in resolution Matlab tutorial Lecture outline

More information

Installation. Binary images. EE 454 Image Processing Project. In this section you will learn

Installation. Binary images. EE 454 Image Processing Project. In this section you will learn EEE 454: Digital Filters and Systems Image Processing with Matlab In this section you will learn How to use Matlab and the Image Processing Toolbox to work with images. Scilab and Scicoslab as open source

More information

Lab for Working with Adobe Photoshop

Lab for Working with Adobe Photoshop Lab for Working with Adobe Photoshop Try the tasks listed with one of the sample images supplied (You will find them in the Course Materials section of Blackboard as the file sample_images.zip. You will

More information

Lane Detection in Automotive

Lane Detection in Automotive Lane Detection in Automotive Contents Introduction... 2 Image Processing... 2 Reading an image... 3 RGB to Gray... 3 Mean and Gaussian filtering... 6 Defining our Region of Interest... 10 BirdsEyeView

More information

CS 484, Fall 2018 Homework Assignment 1: Binary Image Analysis

CS 484, Fall 2018 Homework Assignment 1: Binary Image Analysis CS 484, Fall 2018 Homework Assignment 1: Binary Image Analysis Due: October 31, 2018 The goal of this assignment is to find objects of interest in images using binary image analysis techniques. Question

More information

(ans: Five rows require a 3-bit code and ten columns a 4-bit code. Hence, each key has a 7 bit address.

(ans: Five rows require a 3-bit code and ten columns a 4-bit code. Hence, each key has a 7 bit address. Chapter 2 Edited with the trial version of Foxit Advanced PDF Editor Sensors & Actuators 2.1 Problems Problem 2.1 (Music icon address What screen-row-column address would the controller assign to the music

More information

Integrated Image Processing Functions using MATLAB GUI

Integrated Image Processing Functions using MATLAB GUI Integrated Image Processing Functions using MATLAB GUI Nassir H. Salman a, Gullanar M. Hadi b, Faculty of Computer science, Cihan university,erbil, Iraq Faculty of Engineering-Software Engineering, Salaheldeen

More information

Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science Circuits & Electronics Spring 2005

Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science Circuits & Electronics Spring 2005 Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science 6.002 Circuits & Electronics Spring 2005 Lab #2: MOSFET Inverting Amplifiers & FirstOrder Circuits Introduction

More information

MRI Grid. The MRI Grid is a tool in MRI Cell Image Analyzer, that can be used to associate measurements with labeled positions on a board.

MRI Grid. The MRI Grid is a tool in MRI Cell Image Analyzer, that can be used to associate measurements with labeled positions on a board. Abstract The is a tool in MRI Cell Image Analyzer, that can be used to associate measurements with labeled positions on a board. Illustration 2: A grid on a binary image. Illustration 1: The interface

More information

MIT CSAIL Advances in Computer Vision Fall Problem Set 6: Anaglyph Camera Obscura

MIT CSAIL Advances in Computer Vision Fall Problem Set 6: Anaglyph Camera Obscura MIT CSAIL 6.869 Advances in Computer Vision Fall 2013 Problem Set 6: Anaglyph Camera Obscura Posted: Tuesday, October 8, 2013 Due: Thursday, October 17, 2013 You should submit a hard copy of your work

More information

Computer Exercises in. Communication Theory SMS016

Computer Exercises in. Communication Theory SMS016 Luleå Tekniska Universitet Avd. för Signalbehandling Jan-Jaap van de Beek Frank Sjöberg Computer Exercises in Communication Theory SMS016 November 2001 Computer Exercises to be carried out in groups of

More information

Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science Electronic Circuits Spring 2007

Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science Electronic Circuits Spring 2007 assachusetts Institute of Technology Department of Electrical Engineering and Computer Science 6.002 Electronic Circuits Spring 2007 Lab 2: OSFET Inverting Amplifiers & FirstOrder Circuits Handout S07034

More information

(ans: Five rows and five columns accommodate 25 switch locations. )

(ans: Five rows and five columns accommodate 25 switch locations. ) Chapter 2 Sensors & Actuators 2.1 Problems Problem 2.1 (Music icon address What screen-row-column address would the controller assign to the music icon shown in Figure 2.10 if the icon is located on the

More information

MATLAB 2-D Plotting. Matlab has many useful plotting options available! We ll review some of them today.

MATLAB 2-D Plotting. Matlab has many useful plotting options available! We ll review some of them today. Class15 MATLAB 2-D Plotting Matlab has many useful plotting options available! We ll review some of them today. help graph2d will display a list of relevant plotting functions. Plot Command Plot command

More information

INTRODUCTION TO MATLAB by. Introduction to Matlab

INTRODUCTION TO MATLAB by. Introduction to Matlab INTRODUCTION TO MATLAB by Mohamed Hussein Lecture 5 Introduction to Matlab More on XY Plotting Other Types of Plotting 3D Plot (XYZ Plotting) More on XY Plotting Other XY plotting commands are axis ([xmin

More information

INTRODUCTION TO MATLAB

INTRODUCTION TO MATLAB INTRODUCTION TO MATLAB MATLAB is an interactive program for numeric computation and data visualization. Fundamentally, MATLAB is built upon a foundation of sophisticated matrix software for analyzing linear

More information

TIS Vision Tools A simple MATLAB interface to the The Imaging Source (TIS) FireWire cameras (DFK 31F03)

TIS Vision Tools A simple MATLAB interface to the The Imaging Source (TIS) FireWire cameras (DFK 31F03) A simple MATLAB interface to the The Imaging Source (TIS) FireWire cameras (DFK 31F03) 100 Select object to be tracked... 90 80 70 60 50 40 30 20 10 20 40 60 80 100 F. Wörnle, Aprit 2005 1 Contents 1 Introduction

More information

Sharpening Spatial Filters ( high pass)

Sharpening Spatial Filters ( high pass) Sharpening Spatial Filters ( high pass) Previously we have looked at smoothing filters which remove fine detail Sharpening spatial filters seek to highlight fine detail Remove blurring from images Highlight

More information

Lab 4 Fourier Series and the Gibbs Phenomenon

Lab 4 Fourier Series and the Gibbs Phenomenon Lab 4 Fourier Series and the Gibbs Phenomenon EE 235: Continuous-Time Linear Systems Department of Electrical Engineering University of Washington This work 1 was written by Amittai Axelrod, Jayson Bowen,

More information

Digital Image Processing. Digital Image Fundamentals II 12 th June, 2017

Digital Image Processing. Digital Image Fundamentals II 12 th June, 2017 Digital Image Processing Digital Image Fundamentals II 12 th June, 2017 Image Enhancement Image Enhancement Types of Image Enhancement Operations Neighborhood Operations on Images Spatial Filtering Filtering

More information

GE U111 HTT&TL, Lab 1: The Speed of Sound in Air, Acoustic Distance Measurement & Basic Concepts in MATLAB

GE U111 HTT&TL, Lab 1: The Speed of Sound in Air, Acoustic Distance Measurement & Basic Concepts in MATLAB GE U111 HTT&TL, Lab 1: The Speed of Sound in Air, Acoustic Distance Measurement & Basic Concepts in MATLAB Contents 1 Preview: Programming & Experiments Goals 2 2 Homework Assignment 3 3 Measuring The

More information

Lane Detection in Automotive

Lane Detection in Automotive Lane Detection in Automotive Contents Introduction... 2 Image Processing... 2 Reading an image... 3 RGB to Gray... 3 Mean and Gaussian filtering... 5 Defining our Region of Interest... 6 BirdsEyeView Transformation...

More information

Problem Set 1 (Solutions are due Mon )

Problem Set 1 (Solutions are due Mon ) ECEN 242 Wireless Electronics for Communication Spring 212 1-23-12 P. Mathys Problem Set 1 (Solutions are due Mon. 1-3-12) 1 Introduction The goals of this problem set are to use Matlab to generate and

More information

Previous Lecture: Today s Lecture: Announcements: 2-d array examples. Image processing

Previous Lecture: Today s Lecture: Announcements: 2-d array examples. Image processing Previous Lecture: 2-d array examples Today s Lecture: Image processing Announcements: Discussion this week in Upson B7 lab Prelim 1 to be returned at of lecture. Unclaimed papers (and those on which student

More information

High Level Computer Vision SS2015

High Level Computer Vision SS2015 High Level Computer Vision SS2015 Exercise 2: Object Identification (Released on 8th May, due on 15th May. Send your solution to walon@mpi-inf.mpg.de with adding [hlcv] to the caption) Question 1: Image

More information

Lab 6: Sampling, Convolution, and FIR Filtering

Lab 6: Sampling, Convolution, and FIR Filtering Lab 6: Sampling, Convolution, and FIR Filtering Pre-Lab and Warm-Up: You should read at least the Pre-Lab and Warm-up sections of this lab assignment and go over all exercises in the Pre-Lab section prior

More information

Midterm is on Thursday!

Midterm is on Thursday! Midterm is on Thursday! Project presentations are May 17th, 22nd and 24th Next week there is a strike on campus. Class is therefore cancelled on Tuesday. Please work on your presentations instead! REVIEW

More information

2014 Texas Instruments Motor Control Training Series. -V th. Dave Wilson

2014 Texas Instruments Motor Control Training Series. -V th. Dave Wilson 2014 Texas Instruments Motor Control Training Series -V th Lab Exercise 1: Field Oriented Speed Control In the Lab Exercises folder, open the file 03 FOC Speed Control, and follow the directions in the

More information

ECE411 - Laboratory Exercise #1

ECE411 - Laboratory Exercise #1 ECE411 - Laboratory Exercise #1 Introduction to Matlab/Simulink This laboratory exercise is intended to provide a tutorial introduction to Matlab/Simulink. Simulink is a Matlab toolbox for analysis/simulation

More information

Bayesian Foreground and Shadow Detection in Uncertain Frame Rate Surveillance Videos

Bayesian Foreground and Shadow Detection in Uncertain Frame Rate Surveillance Videos ABSTRACT AND FIGURES OF PAPER PUBLISHED IN IEEE TRANSACTIONS ON IMAGE PROCESSING VOL. 17, NO. 4, 2008 1 Bayesian Foreground and Shadow Detection in Uncertain Frame Rate Surveillance Videos Csaba Benedek,

More information

TDI2131 Digital Image Processing (Week 4) Tutorial 3

TDI2131 Digital Image Processing (Week 4) Tutorial 3 TDI2131 Digital Image Processing (Week 4) Tutorial 3 Note: All images used in this tutorial belong to the Image Processing Toolbox. 1. Spatial Filtering (by hand) (a) Below is an 8-bit grayscale image

More information

Exercise NMCGJ: Image Processing

Exercise NMCGJ: Image Processing Exercise NMCGJ: Image Processing A digital picture (or image) is internally stored as an array or a matrix of pixels (= picture elements), each of them containing a specific color. This exercise is devoted

More information

Chapter 4 MASK Encryption: Results with Image Analysis

Chapter 4 MASK Encryption: Results with Image Analysis 95 Chapter 4 MASK Encryption: Results with Image Analysis This chapter discusses the tests conducted and analysis made on MASK encryption, with gray scale and colour images. Statistical analysis including

More information

1. (a) Explain the process of Image acquisition. (b) Discuss different elements used in digital image processing system. [8+8]

1. (a) Explain the process of Image acquisition. (b) Discuss different elements used in digital image processing system. [8+8] Code No: R05410408 Set No. 1 1. (a) Explain the process of Image acquisition. (b) Discuss different elements used in digital image processing system. [8+8] 2. (a) Find Fourier transform 2 -D sinusoidal

More information

EE/GP140-The Earth From Space- Winter 2008 Handout #16 Lab Exercise #3

EE/GP140-The Earth From Space- Winter 2008 Handout #16 Lab Exercise #3 EE/GP140-The Earth From Space- Winter 2008 Handout #16 Lab Exercise #3 Topic 1: Color Combination. We will see how all colors can be produced by combining red, green, and blue in different proportions.

More information

Digital Signal Processing Laboratory 1: Discrete Time Signals with MATLAB

Digital Signal Processing Laboratory 1: Discrete Time Signals with MATLAB Digital Signal Processing Laboratory 1: Discrete Time Signals with MATLAB Thursday, 23 September 2010 No PreLab is Required Objective: In this laboratory you will review the basics of MATLAB as a tool

More information

A graph is an effective way to show a trend in data or relating two variables in an experiment.

A graph is an effective way to show a trend in data or relating two variables in an experiment. Chem 111-Packet GRAPHING A graph is an effective way to show a trend in data or relating two variables in an experiment. Consider the following data for exercises #1 and 2 given below. Temperature, ºC

More information

9'1 -c,f' -,;; Y DEC COURSE OUfLINE COURSE TITLE: INTRODUCTION TO AUTOCAD CODE NO : CAD 120 SEMESTER: I ARCHITECTURAL TECHNICIAN

9'1 -c,f' -,;; Y DEC COURSE OUfLINE COURSE TITLE: INTRODUCTION TO AUTOCAD CODE NO : CAD 120 SEMESTER: I ARCHITECTURAL TECHNICIAN SAULT STE. MARIE, ON SAULT COLLEGE OF APPLIED ARTS AND TECHNOLOGY COURSE OUfLINE COURSE TITLE: INTRODUCTION TO AUTOCAD CODE NO : SEMESTER: I PROGRAM: ARCHITECTURAL TECHNICIAN INSTRUCTOR: H. PIETRZAKOWSKI

More information

INTRODUCTION TO IMAGE PROCESSING

INTRODUCTION TO IMAGE PROCESSING CHAPTER 9 INTRODUCTION TO IMAGE PROCESSING This chapter explores image processing and some of the many practical applications associated with image processing. The chapter begins with basic image terminology

More information

ELEC MatLab Introductory Lab. Performed: Monday January 20 th Submitted: Monday January 27 th 2014

ELEC MatLab Introductory Lab. Performed: Monday January 20 th Submitted: Monday January 27 th 2014 ELEC 1908 MatLab Introductory Lab Performed: Monday January 20 th 2014 Submitted: Monday January 27 th 2014 Performed By Name, Student # Name, Student # Teaching Assistant Svetlana Demptchenko Introduction

More information

SECTION I - CHAPTER 2 DIGITAL IMAGING PROCESSING CONCEPTS

SECTION I - CHAPTER 2 DIGITAL IMAGING PROCESSING CONCEPTS RADT 3463 - COMPUTERIZED IMAGING Section I: Chapter 2 RADT 3463 Computerized Imaging 1 SECTION I - CHAPTER 2 DIGITAL IMAGING PROCESSING CONCEPTS RADT 3463 COMPUTERIZED IMAGING Section I: Chapter 2 RADT

More information

Computer Vision using MatLAB and the Toolbox of Image Processing. Technical Report B Abstract

Computer Vision using MatLAB and the Toolbox of Image Processing. Technical Report B Abstract Computer Vision using MatLAB and the Toolbox of Image Processing Technical Report B-05-09 Erik Cuevas 1,2, Daniel Zaldivar 1,2, and Raul Rojas 1 1 Freie Universität Berlin, Institut für Informatik Takusstr.

More information

IMAGE PROCESSING Vedat Tavşanoğlu

IMAGE PROCESSING Vedat Tavşanoğlu Vedat Tavşano anoğlu Image Processing A Revision of Basic Concepts An image is mathematically represented by: where I( x, y) x y is the vertical spatial distance; is the horizontal spatial distance, both

More information

SMS045 - DSP Systems in Practice. Lab 1 - Filter Design and Evaluation in MATLAB Due date: Thursday Nov 13, 2003

SMS045 - DSP Systems in Practice. Lab 1 - Filter Design and Evaluation in MATLAB Due date: Thursday Nov 13, 2003 SMS045 - DSP Systems in Practice Lab 1 - Filter Design and Evaluation in MATLAB Due date: Thursday Nov 13, 2003 Lab Purpose This lab will introduce MATLAB as a tool for designing and evaluating digital

More information

BASIC OPERATIONS IN IMAGE PROCESSING USING MATLAB

BASIC OPERATIONS IN IMAGE PROCESSING USING MATLAB BASIC OPERATIONS IN IMAGE PROCESSING USING MATLAB Er.Amritpal Kaur 1,Nirajpal Kaur 2 1,2 Assistant Professor,Guru Nanak Dev University, Regional Campus, Gurdaspur Abstract: - This paper aims at basic image

More information

Statistics 101: Section L Laboratory 10

Statistics 101: Section L Laboratory 10 Statistics 101: Section L Laboratory 10 This lab looks at the sampling distribution of the sample proportion pˆ and probabilities associated with sampling from a population with a categorical variable.

More information

Embedded Systems CSEE W4840. Design Document. Hardware implementation of connected component labelling

Embedded Systems CSEE W4840. Design Document. Hardware implementation of connected component labelling Embedded Systems CSEE W4840 Design Document Hardware implementation of connected component labelling Avinash Nair ASN2129 Jerry Barona JAB2397 Manushree Gangwar MG3631 Spring 2016 Table of Contents TABLE

More information

Previous Lecture: Today s Lecture: Announcements: 2-d array examples. Working with images

Previous Lecture: Today s Lecture: Announcements: 2-d array examples. Working with images Previous Lecture: 2-d array examples Today s Lecture: Working with images Announcements: Discussion this week in the UP B7 computer lab Prelim 1 to be returned at of lecture. Unclaimed papers (and those

More information

SIGNALS AND SYSTEMS: 3C1 LABORATORY 1. 1 Dr. David Corrigan Electronic and Electrical Engineering Dept.

SIGNALS AND SYSTEMS: 3C1 LABORATORY 1. 1 Dr. David Corrigan Electronic and Electrical Engineering Dept. 2012 Signals and Systems: Laboratory 1 1 SIGNALS AND SYSTEMS: 3C1 LABORATORY 1. 1 Dr. David Corrigan Electronic and Electrical Engineering Dept. corrigad@tcd.ie www.mee.tcd.ie/ corrigad The aims of this

More information

######################################################################

###################################################################### Write a MATLAB program which asks the user to enter three numbers. - The program should figure out the median value and the average value and print these out. Do not use the predefined MATLAB functions

More information

LAB 2 SPECTRUM ANALYSIS OF PERIODIC SIGNALS

LAB 2 SPECTRUM ANALYSIS OF PERIODIC SIGNALS Eastern Mediterranean University Faculty of Engineering Department of Electrical and Electronic Engineering EENG 360 Communication System I Laboratory LAB 2 SPECTRUM ANALYSIS OF PERIODIC SIGNALS General

More information

You Can Make a Difference! Due November 11/12 (Implementation plans due in class on 11/9)

You Can Make a Difference! Due November 11/12 (Implementation plans due in class on 11/9) You Can Make a Difference! Due November 11/12 (Implementation plans due in class on 11/9) In last week s lab, we introduced some of the basic mechanisms used to manipulate images in Java programs. In this

More information

Lab P-10: Edge Detection in Images: UPC Decoding. Please read through the information below prior to attending your lab.

Lab P-10: Edge Detection in Images: UPC Decoding. Please read through the information below prior to attending your lab. DSP First, 2e Signal Processing First Lab P-10: Edge Detection in Images: UPC Decoding Pre-Lab: Read the Pre-Lab and do all the exercises in the Pre-Lab section prior to attending lab. Verification: The

More information

Outline. Nested Loops. Nested loops. Nested loops. Nested loops TOPIC 7 MODIFYING PIXELS IN A MATRIX NESTED FOR LOOPS

Outline. Nested Loops. Nested loops. Nested loops. Nested loops TOPIC 7 MODIFYING PIXELS IN A MATRIX NESTED FOR LOOPS TOPIC 7 MODIFYING PIXELS IN A MATRIX NESTED FOR LOOPS 1 2 2 Outline Using nested loops to process data in a matrix (2- dimensional array) More advanced ways of manipulating pictures in Java programs Notes

More information

Visual Media Processing Using MATLAB Beginner's Guide

Visual Media Processing Using MATLAB Beginner's Guide www.allitebooks.com Visual Media Processing Using MATLAB Beginner's Guide Learn a range of techniques from enhancing and adding artistic effects to your photographs, to editing and processing your videos,

More information

CMPS 12A Introduction to Programming Programming Assignment 5 In this assignment you will write a Java program that finds all solutions to the n-queens problem, for. Begin by reading the Wikipedia article

More information

PASS Sample Size Software. These options specify the characteristics of the lines, labels, and tick marks along the X and Y axes.

PASS Sample Size Software. These options specify the characteristics of the lines, labels, and tick marks along the X and Y axes. Chapter 940 Introduction This section describes the options that are available for the appearance of a scatter plot. A set of all these options can be stored as a template file which can be retrieved later.

More information

The Formula for Sinusoidal Signals

The Formula for Sinusoidal Signals The Formula for I The general formula for a sinusoidal signal is x(t) =A cos(2pft + f). I A, f, and f are parameters that characterize the sinusoidal sinal. I A - Amplitude: determines the height of the

More information

k y 2k y,max k x 2k x,max

k y 2k y,max k x 2k x,max EE225E/BIOE265 Spring 2012 Principles of MRI Miki Lustig Assignment 5 Due Feb 26, 2012 1. Finish reading Nishimura Ch. 5. 2. For the 16 turn spiral trajectory, plotted below, what is the a) Spatial resolution,

More information

Making 2D Plots in Matlab

Making 2D Plots in Matlab Making 2D Plots in Matlab Gerald W. Recktenwald Department of Mechanical Engineering Portland State University gerry@pdx.edu ME 350: Plotting with Matlab Overview Plotting in Matlab Plotting (x, y) data

More information

Liquid Camera PROJECT REPORT STUDY WEEK FASCINATING INFORMATICS. N. Ionescu, L. Kauflin & F. Rickenbach

Liquid Camera PROJECT REPORT STUDY WEEK FASCINATING INFORMATICS. N. Ionescu, L. Kauflin & F. Rickenbach PROJECT REPORT STUDY WEEK FASCINATING INFORMATICS Liquid Camera N. Ionescu, L. Kauflin & F. Rickenbach Alte Kantonsschule Aarau, Switzerland Lycée Denis-de-Rougemont, Switzerland Kantonsschule Kollegium

More information

Knowledge Integration Module 2 Fall 2016

Knowledge Integration Module 2 Fall 2016 Knowledge Integration Module 2 Fall 2016 1 Basic Information: The knowledge integration module 2 or KI-2 is a vehicle to help you better grasp the commonality and correlations between concepts covered

More information

Department of Electrical Engineering. Laboratory Manual Digital Signal Processing

Department of Electrical Engineering. Laboratory Manual Digital Signal Processing Department of Electrical Engineering Laboratory Manual Digital Signal Processing ABASYN UNIVERSITY ISLAMABAD CAMPUS Lab Instructor: Asim Ul Haq Abasyn University Islamabad Campus Digital Signal Processing

More information

CSE 260 Digital Computers: Organization and Logical Design. Lab 4. Jon Turner Due 3/27/2012

CSE 260 Digital Computers: Organization and Logical Design. Lab 4. Jon Turner Due 3/27/2012 CSE 260 Digital Computers: Organization and Logical Design Lab 4 Jon Turner Due 3/27/2012 Recall and follow the General notes from lab1. In this lab, you will be designing a circuit that implements the

More information

MATLAB - Lecture # 5

MATLAB - Lecture # 5 MATLAB - Lecture # 5 Two Dimensional Plots / Chapter 5 Topics Covered: 1. Plotting basic 2-D plots. The plot command. The fplot command. Plotting multiple graphs in the same plot. MAKING X-Y PLOTS 105

More information

CSC 110 Lab 4 Algorithms using Functions. Names:

CSC 110 Lab 4 Algorithms using Functions. Names: CSC 110 Lab 4 Algorithms using Functions Names: Tic- Tac- Toe Game Write a program that will allow two players to play Tic- Tac- Toe. You will be given some code as a starting point. Fill in the parts

More information

EE368/CS232 Digital Image Processing Winter Homework #3 Released: Monday, January 22 Due: Wednesday, January 31, 1:30pm

EE368/CS232 Digital Image Processing Winter Homework #3 Released: Monday, January 22 Due: Wednesday, January 31, 1:30pm EE368/CS232 Digital Image Processing Winter 2017-2018 Lecture Review and Quizzes (Due: Wednesday, January 31, 1:30pm) Please review what you have learned in class and then complete the online quiz questions

More information

P202/219 Laboratory IUPUI Physics Department THIN LENSES

P202/219 Laboratory IUPUI Physics Department THIN LENSES THIN LENSES OBJECTIVE To verify the thin lens equation, m = h i /h o = d i /d o. d o d i f, and the magnification equations THEORY In the above equations, d o is the distance between the object and the

More information