DIGITAL IMAGE PROCESSING

BİL566

Course Code: BİL566
Semester: -
Theory+Practice: 3 + 0
ECTS: 10

Course Type

Elective Course

Course Level

Master's Degree Without Thesis

Year of Study

Semester

ECTS

Name of Lecturer(s)

Associate Professor Emre Sümer

Learning Outcomes

At the end of this course, the students;

Know the mid- and advanced-level image processing techniques.
Comprehend the wavelets and multi-resolution processing.
Get the fundamental knowledge about the image compression basics and its applications.
Learn the morphological image processing algorithms.
Know the image segmentation.
Know the representation and description.
Get an idea about the object recognition.
Gain the ability to develop an application for a specific problem.

Mode of Delivery

Face to face

Prerequisites

Recommended Optional Programme Components

BIL 421 - Image Processing

Course Description

Review of digital image fundamentals.Intensity transformations.Spatial filtering.Filtering in frequency domain.Review of image restoration and color image processing.Wavelets and multi-resolution processing. Image compression and some basic methods. Morphological image processing and some basic algorithms. Image segmentation. Representation and description, and introduction to object recognition.

Course Contents

WEEK	TOPICS
1^st Week	Introduction
2^nd Week	Digital Image Fundamentals
3^rd Week	Intensity Transformations
4^th Week	Spatial Filtering - I
5^th Week	Spatial Filtering - II
6^th Week	Filtering in the Frequency Domain
7^th Week	Image Restoration
8^th Week	Midterm Exam
9^th Week	Color Image Processing - I
10^th Week	Color Image Processing - II
11^th Week	Morphological Image Processing
12^th Week	Image Segmentation - I
13^th Week	Image Segmentation - II
14^th Week	Project Presentations - I
15^th Week	Project Presentations - II

Recommended or Required Reading

1. Gonzalez Rafael C., Woods Richard E., Digital Image
Processing, 3/E,ISBN: 0-13-505267-X, Pearson Education, 2008.
2. Gonzalez Rafael C., Woods Richard E., Eddins Steven
L., Digital Image Processing using MATLAB, 2/E, ISBN: 9780982085400, Pearson Education, 2009.

Planned Learning Activities and Teaching Methods

Lecture
Questions/Answers
Presentation
Experiment
Project
Problem Solving

Assessment Methods and Criteria

	Quantity	Percentage (%)
Mid-term	1	30
Assignment	1	15
Quiz	1	15
Total(%)		60
Contribution of In-term Studies to Overall Grade(%)		60
Contribution of Final Examination to Overall Grade(%)		40
Total(%)		100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Midterm exam	1	2	2
Preparation for Quiz
Individual or group work	14	11	154
Preparation for Final exam	1	69	69
Course hours	14	3	42
Preparation for Midterm exam	1	44	44
Laboratory (including preparation)
Final exam	1	2	2
Homework
Total Work Load			313
Total Work Load / 30 (h)			10.43
ECTS Credit of the Course			10

Language of Instruction

Turkish

Work Placement(s)

Programme Qualifications / Learning Outcomes

	LO1	LO2	LO3	LO4	LO5	LO6	LO7	LO8
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	LO1	LO2	LO3	LO4	LO5	LO6	LO7	LO8
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	LO1	LO2	LO3	LO4	LO5	LO6	LO7	LO8
K1	X
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