TYPE OF COURSE UNIT	Elective Course
LEVEL OF COURSE UNIT	Associate Degree
YEAR OF STUDY	-
SEMESTER	-
NUMBER OF ECTS CREDITS ALLOCATED	5
NAME OF LECTURER(S)	-
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Defines the image and learns the image acquisition methods. 2) Learns image processing algorithms. (Otsu algorithm, erosion-dilation) 3) Performs the analysis of the image in black and white and color. 4) It can output the histogram of the image. 5) Makes the analysis of the image in the frequency plane. Calculate the Fourier transform of the image. 6) Develop algorithms using Matlab program.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	None
COURSE DEFINITION	With the image processing course, students can process the obtained image, especially the basic image creation processes, determine the intermediate values by interpolation, feature extraction, dilation-erosion operations and black-and-white operations of an image, determining the image histogram and analyzing the graphic and using the frequency domain. Calculations such as the analysis of the image are computer-aided in Matlab environment and with Python.
COURSE CONTENTS	WEEK TOPICS 1st Week What is an image and examination of image acquisition methods, method of saving the image as a file and examination of file extensions 2nd Week Introduction to image processing algorithms - 1 3rd Week Introduction to image processing algorithms - 2 4th Week Introduction to image processing algorithms - 3 5th Week Introduction to image processing algorithms - 4 6th Week Numerical analysis of the image in black and white 7th Week Numerical analysis of the image in RGB-CMY color 8th Week Midterm 9th Week Extraction and analysis of the histogram of the image 10th Week Analysis of the image in the frequency plane and calculation of the Fourier transform 11th Week Application of image processing techniques on algorithm basis in MATLAB environment - 1 12th Week Application of image processing techniques on algorithm basis in MATLAB environment - 2 13th Week Mathematical processing of the image and its algorithms 14th Week 2D and 3D display, display, conversion and HMI-Display technologies
RECOMENDED OR REQUIRED READING	1) Digital Image Processing, Rafael Gonzalez and Richard E. Woods, 2014, Palme Publishing, 954 pages, ISBN: 9786053552123 2) Image Processing from Image to Data with Python and Its Applications, Bekir Aksoy, Nobel Academic Publishing, 188 pages, 2020, ISBN: 9786050332629 3) OpenCv: Image Processing and Machine Learning (with CD Gift), Birol Kuyumcu, Level Publishing, 320 pages, 2017, ISBN: 9786056567933 4) Digital Image Processing: A Signal Processing and Algorithmic Approach, D. Sundararajan, 2017, Springer, ISBN: 9789811061127 5) Remote Sensing and Image Interpretation, 736 pages, Palme Publishing, 2018, ISBN: 9786052820759 6) Matlab Education Set: Artificial Intelligence and Engineering Applications, Cemalettin Kubat, 2016, 792 pages, ISBN: 9786059129336
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Questions/Answers,Case Study,Problem Solving,Practice,Project,Presentation
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 40 Total(%) 40 Contribution of In-term Studies to Overall Grade(%) 40 Contribution of Final Examination to Overall Grade(%) 60 Total(%) 100
ECTS WORKLOAD	Activities Number Hours Workload Midterm exam 1 2 2 Preparation for Quiz Individual or group work 10 2 20 Preparation for Final exam 4 3 12 Course hours 14 3 42 Preparation for Midterm exam 4 3 12 Laboratory (including preparation) Final exam 1 2 2 Homework Total Workload 90 Total Workload / 30 3 ECTS Credits of the Course 5
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No