COURSE UNIT TITLE

: INTRODUCTION TO DIGITAL IMAGE PROCESSING

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CME 4412 INTRODUCTION TO DIGITAL IMAGE PROCESSING ELECTIVE 2 2 0 6

Offered By

Computer Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR ERCAN AVŞAR

Offered to

Computer Engineering

Course Objective

This is an introductory course to the fundamentals of digital image processing. It emphasizes general principles of image processing, rather than specific applications. Course aims to to cover topics such as color, point operations, segmentation, morphological image processing, linear image filtering and correlation, image transforms.

Learning Outcomes of the Course Unit

1   Discriminate general characteristics of digital images
2   Apply Intensity Transformations, Spatial and Frequency Domain Filtering
3   Evaluate image restoration/reconstruction, segmentation and color image processing methods.
4   Apply image compression and morphological image processing methods.
5   Develop image processing algorithms using MATLAB.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to Image Processing - MATLAB Review
2 Digital Image Processing Fundamentals
3 Image Enhancement
4 Histogram Equalization and Matching
5 Spatial Filtering
6 Frequency Domain Filtering
7 Midterm
8 Image Restoration
9 Image Restoration - Geometric Transformations
10 Color Image Processing
11 Color Image Processing
12 Image Compression
13 Morphology
14 Segmentation

Recomended or Required Reading

Main Book: Gonzalez R. C., Woods R. E., (2002), Digital Image Processing, 2nd Edition, Prentice Hall
Subsidiary Book: Lim J. S., (1990), Two-Dimensional Signal and Image Processing, Prentice Hall.

Planned Learning Activities and Teaching Methods

Presentation, Problem solving, Term project, Laboratory applications and Homeworks.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 LAB LABORATORY
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + LAB * 0.20 + FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + LAB * 0.20 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Midterm and Final exams would be used to evaluate Learning outcomes 1-4.
Laboratuary applications, homeworks and term project would be used to evaluate all learning outcomes.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Asst. Prof. Dr. Ercan Avşar
ercan.avsar@cs.deu.edu.tr

Office Hours

Office hours
Tuesday: 13:00-14:00
Friday: 11:00-12:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 2 28
Tutorials 14 2 28
Preparation for midterm exam 0 8 0
Preparation for final exam 1 8 8
Design Project 1 20 20
Preparations before/after weekly lectures 14 2 28
Preparation for midterm exam 1 4 4
Lab Preparation 6 4 24
Project Final Presentation 1 2 2
Final 1 2 2
Midterm 1 1 1
TOTAL WORKLOAD (hours) 145

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.133
LO.25333
LO.35333
LO.45333
LO.53333

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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