Basics of Digital Image Processing: Course Overview and Objectives

 
 
CSE 307
CSE 307
 
Basics of 
Basics of 
Image Processing
Image Processing
 
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About this Course
 
Organizational Issues
 
2
 
About this Course (Cont.)
 
Organizational Issues
 
3
 
Main Objective
(s)
 of this Course
 
Organizational Issues
 
4
 
In this course it is intended to introduce the
basic concepts of digital image processing
and provide a foundation for implementing
commonly used image processing
algorithms.
 
Learning Outcomes of this Course
 
Organizational Issues
 
5
 
Upon successful completion of this course,
students will
Have a basic understanding of fundamental concepts of
digital image processing
Use basic image processing tools needed to analyze
images in spatial and frequency domain
Design and implement algorithms for the solution of broad
class of problems in digital image processing
Explain various image processing tools for smoothing,
reconstruction and enhancement of images
Understand the importance of strong mathematical tools for
image processing and analysis in different application areas
 
Course Content
 
Organizational Issues
 
6
 
This course studies the fundamental topics in
digital image processing like intensity
transformations, filtering both in spatial and in
frequency domain, image restoration and
reconstruction, point, line, edge detection,
morphological image processing, image
segmentation.
 
Resources
 
Organizational Issues
 
7
 
Resources
 (cont.)
 
Organizational Issues
 
8
 
Organizational Issues
 
9
 
Course Schedule (Weekly)
 
Organizational Issues
 
10
 
Course Schedule (Weekly) 
(Cont.)
 
Assessment
 (tentative)
 
Organizational Issues
 
11
 
Assessment (Cont.)
 
Organizational Issues
 
12
 
Final Grades will be determined according to
the 
Adnan Menderes
 University Associate
Degree, Bachelor Degree and Graduate
Degree Education and Examination
Regulation
 
Responsibilities of the Students
 
Organizational Issues
 
13
 
Obtaining the text book(s)
Coming to the course with a good preparation
Completing the exercises with individual
efforts unless told otherwise
Following the rules set by the responsibles
for the course and the implementation/lab.
s
tudies
HONESTY !!!
 
Plagiarism
 
Organizational Issues
 
14
 
Plagiarism will not be tolerated
Projects without references: a penalty of 20%
Submitting your own work that has been earlier
submitted to satisfy the requirements of another
course is (self)-plagiarism (also called double
dipping)
Copying a journal article or a section of a book
or code from an article or book
 and submitting it
as your own
 is plagiarism
 
Plagiarism
 (Cont.)
 
Organizational Issues
 
15
 
Using significant ideas from someone else,
but putting them in to your own words and not
acknowledging the source of the ideas
 is
plagiarism
Copying an essay
,
 
code, work etc. 
from
another student and submitting it as your own
is plagiarism
And PLAGIARISM is THEFT
So don’t steal (Nobody likes thieves)
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This course on digital image processing covers fundamental concepts, tools, and algorithms used in analyzing and enhancing images. Students will gain knowledge on spatial and frequency domain analysis, algorithm implementation, image reconstruction, and more. The main objective is to provide a strong foundation in image processing techniques and mathematical tools relevant to various application areas.

  • Digital Image Processing
  • Course Overview
  • Image Analysis
  • Algorithm Implementation
  • Spatial Domain

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  1. CSE 307 Basics of Image Processing Lecture #0 Organizational Issues Prepared & Presented by Asst. Prof. Dr. Samsun M. BA ARICI

  2. About this Course Course Code Course Hour/Week Course Title Semester ADU Credit ECTS Theory 2 Practice 2 Introduction to Computer Applications CSE 307 Fall 3 6 Course Type 1. Compulsory Courses 1.1. Programme Compulsory Courses 1.2. University Compulsory Courses (UFND) 1.3. Y K (Higher Education Council) Compulsory Courses 2. Elective Courses 2.1. Program Elective Courses X 2.2. University Elective Courses 3. Prerequisites Courses 3.1. Compulsory Prerequisites Courses 3.2. Elective Prerequisites Courses Organizational Issues 2

  3. About this Course (Cont.) Language of Instruction English Associate Degree (Short Cycle) Undergraduate (First Cycle) Graduate (Second Cycle) Doctoral Course (Third Cycle) Level of Course Special Pre-Conditions of the Course (compulsory) None Special Pre-Conditions of the Course (recommended) Mail: sbasarici@adu.edu.tr Web: http://akademik.adu.edu.tr/fakulte/muhendislik /personel/sbasarici/anasayfa Course Instructor(s) Dr. Samsun M. Ba ar c Organizational Issues 3

  4. Main Objective(s) of this Course In this course it is intended to introduce the basic concepts of digital image processing and provide a foundation for implementing commonly used algorithms. image processing Organizational Issues 4

  5. Learning Outcomes of this Course Upon successful completion of this course, students will Have a basic understanding of fundamental concepts of digital image processing Use basic image processing tools needed to analyze images in spatial and frequency domain Design and implement algorithms for the solution of broad class of problems in digital image processing Explain various image processing tools for smoothing, reconstruction and enhancement of images Understand the importance of strong mathematical tools for image processing and analysis in different application areas Organizational Issues 5

  6. Course Content This course studies the fundamental topics in digital image processing transformations, filtering both in spatial and in frequency domain, image reconstruction, point, line, edge detection, morphological image segmentation. like intensity restoration and processing, image Organizational Issues 6

  7. Resources Rafael C. Gonzalez, Richard E. Woods Digital Image Processing, 4th Ed. ; Pearson, 2018, ISBN: 978-1292223049 (DIP) Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins Digital Image Processing Using MATLAB ; Pearson, 2004, ISBN: 013-0085197 (DIPUM) Required Course Material (s) /Reading(s)/Text Book (s) Oge Marques, Practical Image and Video Processing Using MATLAB ; Wiley, 2011, ISBN: 978-0470048153 (PIVPUM) Organizational Issues 7

  8. Resources (cont.) Maria Petrou, Costas Petrou Image Processing: The Fundamentals, 2nd Ed. ; Wiley, 2010, ISBN: 978- 0470745861 Chris Solomon, Toby Breckon Fundamentals of Digital Image Processing: A Practical Approach with Examples in MATLAB ; Wiley, 2011, ISBN: 978- 0470844731 http://www.mathworks.com, main resource for MATLAB Recommended Course Material (s)/Reading(s)/Other Other sources will be announced during the course Organizational Issues 8

  9. Course Schedule (Weekly) Methodologyand Implementation (theory, practice, assignment etc) MATLAB Fundamentals Preliminary Preparation Week Topics Introducing image processing (IP) and MATLAB: historical background, the importance and application areas of IP DIP & DIPUM (Ch. 1), PIVPUM (Ch. 1-4) 1 IP Fundamentals: Definitions and basics DIP & DIPUM (Ch. 2), MATLAB Fundamentals (cont.) 2 PIVPUM (Ch. 2, 5, 6, 7) Intensity transformations and spatial filtering DIP & DIPUM (Ch. 3), PIVPUM (Ch. 8-10) Histogram and neighborhood operations (implementing various filters) Histogram and neighborhood operations (implementing various filters) (cont.) Implementing low-pass, high-pass filter, FFT & DFT 3 Intensity transformations and spatial filtering (cont.) DIP & DIPUM (Ch. 3), PIVPUM (Ch. 8-10) 4 Frequency domain filtering DIP & DIPUM (Ch. 4), PIVPUM (Ch. 11) 5 Frequency domain filtering (cont.) DIP & DIPUM (Ch. 4), PIVPUM (Ch. 11) - Implementing low-pass, high-pass filter, FFT & DFT (cont.) MIDTERM 6 MIDTERM EXAM 7 Organizational Issues 9

  10. Course Schedule (Weekly) (Cont.) Preliminary Preparation Methodologyand Implementation (theory, practice, assignmentetc) Week Topics Image restoration and reconstruction DIP & DIPUM (Ch. 5), PIVPUM (Ch. 12) Implementation of noise and noise models and various filters 8 Image restoration and reconstruction (cont.) DIP & DIPUM (Ch. 5), Implementation of noise and noise models and various filters (cont.) Implementation of basic morphological tools like dilation, erosion etc. and grayscale morphology Implementation of basic morphological tools like dilation, erosion etc. and grayscale morphology (cont.) Implementation of derivative edge filtering (LoG, Canny etc.), intensity- and region based filtering algorithms and watershed Implementation of derivative edge filtering (LoG, Canny etc.), intensity- and region based filtering algorithms and watershed (cont.) Color models and implementation of pseudo- and full-color IP algorithms 9 PIVPUM (Ch. 12) DIP & DIPUM (Ch. 9), PIVPUM (Ch. 13) Morphological image processing 10 Morphological image processing (cont.) DIP & DIPUM (Ch. 9), PIVPUM (Ch. 13) 11 Edge detection and image segmentation DIP & DIPUM (Ch. 10), PIVPUM (Ch. 14-15) 12 Edge detection and image segmentation (cont.) DIP & DIPUM (Ch. 10), PIVPUM (Ch. 14-15) 13 Color image processing DIP & DIPUM ((Ch. 6), PIVPUM (Ch. 16) 14 Image representation, description and feature extraction and recognition DIP & DIPUM (Ch. 11-12), PIVPUM (Ch. 18-19) Implementation of feature extraction and representation and pattern classification algorithms 15 Organizational Issues 10

  11. Assessment (tentative) SemesterActivities/ Studies NUMBER WEIGHT in % 1 - 2 4 1 - - - 20 - 20 Mid- Term Attendance Quiz Assignment (s) Project Laboratory Field Studies (Technical Visits) Presentation/ Seminar (20 see below) 20 - - - - - Practice (Laboratory, Virtual Court, Studio Studies etc.) - - Other (Placement/Internship etc.) 60 TOTAL 60 Contribution of Semester Activities/Studies to the Final Grade 40 (The written final exam will be 20% and the assignments will also count 20%) Contribution of Final Examination/Final Project/ Dissertation to the Final Grade 100 TOTAL Organizational Issues 11

  12. Assessment (Cont.) Final Grades will be determined according to the Adnan Menderes University Associate Degree, Bachelor Degree Degree Education Regulation and Graduate Examination and Organizational Issues 12

  13. Responsibilities of the Students Obtaining the text book(s) Coming to the course with a good preparation Completing the exercises with individual efforts unless told otherwise Following the rules set by the responsibles for the course and the implementation/lab. studies HONESTY !!! Organizational Issues 13

  14. Plagiarism Plagiarism will not be tolerated Projects without references: a penalty of 20% Submitting your own work that has been earlier submitted to satisfy the requirements of another course is (self)-plagiarism (also called double dipping) Copying a journal article or a section of a book or code from an article or book and submitting it as your own is plagiarism Organizational Issues 14

  15. Plagiarism (Cont.) Using significant ideas from someone else, but putting them in to your own words and not acknowledging the source of the ideas is plagiarism Copying an essay, code, work etc. from another student and submitting it as your own is plagiarism And PLAGIARISM is THEFT So don t steal (Nobody likes thieves) Organizational Issues 15

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