TYPE OF COURSE UNIT	Elective Course
LEVEL OF COURSE UNIT	Master's Degree Without Thesis
YEAR OF STUDY	-
SEMESTER	-
NUMBER OF ECTS CREDITS ALLOCATED	10
NAME OF LECTURER(S)	Associate Professor Emre Sümer
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Know the mid- and advanced-level image processing techniques. 2) Comprehend the wavelets and multi-resolution processing. 3) Get the fundamental knowledge about the image compression basics and its applications. 4) Learn the morphological image processing algorithms. 5) Know the image segmentation. 6) Know the representation and description. 7) Get an idea about the object recognition. 8) Gain the ability to develop an application for a specific problem.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	BIL 421 - Image Processing
COURSE DEFINITION	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 1st Week Review of digital image fundamentals 2nd Week Intensity transformations 3rd Week Intensity transformations 4th Week Spatial filtering 5th Week Filtering in frequency domain 6th Week Filtering in frequency domain 7th Week Review of image restoration and color image processing. 8th Week Mid-term 9th Week Wavelets and multi-resolution processing 10th Week Image compression and some basic methods 11th Week Morphological image processing and some basic algorithms 12th Week Image segmentation 13th Week Image segmentation 14th Week Representation and description, and introduction to object recognition.
RECOMENDED 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 WORKLOAD	Activities Number Hours Workload 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 Workload 313 Total Workload / 30 10,43 ECTS Credits of the Course 10
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No