UBI621 – Digital Image Processing

Course Unit Title	Digital Image Processing
Course Unit Code	UBI 621
Course Time:	Friday [09:00-12:00]
Course Room:	UBE, Room 103
Level of Course Unit	PhD
Number of ECTS Credits Allocated	7,5
Theoretical	3
Semester	Fall
Lecturer	Assoc. Prof. Dr.Muhammed Cinsdikici,
Contact Info	cinsdikici@gmail.com, office phone: 3205
Mode of Delivery	Face-To-Face
Language	Turkish
Assistant
Prerequisities	Matlab Coding, C# coding, Linear Algebra,  No prior knowledge of vision is assumed.
Objectives of the Course	– to make the student identify image processing methods,- comprehend importance of using computer in image processing,- construct basic image implementations with MATLAB program packet- develop image processing algorithms.
Textbook(s)	Computer Vision: A modern Approach (2nd edt), David A. Forsyth, Jean Ponce, Prentice Hall, ISBN: 978-0136085928, 2011 Computer Vision: Algorithms and Applications , Richard Szeliski, ISBN: 978-1-84882-934-3, Springer, 2011 Digital Image Processing 3rd Edition (DIP/3e), Rafael C. Gonzalez, Richard E. Woods, Prentice Hall, ISBN:978-0135052679, 2008. Practical Image and Video Processing, Oge Marques, Wiley, ISBN: 978-0470048153 ,2011
Learning Outcomes	At the end of this course, a student should be able to: Calculate image histograms and gray-scale transformation for image enhancement, explain histogram equilazation method Identify filtering methods in spatial and frequency domains and develop algorithms Calculate 2-dimensional Fourier Transformation of an image; calculate and analyse 2-dimensional convolution and apply it for the filtering purpose Comprehend mathematical morphology fundamentals and apply them for image processing purposes Recall basic MATLAB instructions and functions for basic image processing operations Apply image processing algorithms for real life problems Have the motivation to propose new solutions for image processing problems Realize the advantages of MATLAB program packet in algorithm development and develop image processing algorithms in MATLAB environment
Course Contents	Objectives of this course are; to make the student identify image processing methods, comprehend importance of using computer in image processing, construct basic image implementations with MATLAB program packet and develop image processing algorithms.
Grading & Projects	%30 HomeWorks + %20 MidTerm + %20 Final Exam + %30 Final Project Late submission of the homeworks and projects are not going to be accepted. The assessment principals are;————————————-On time submission are scored as max.100/100One week late submissions are scored as max. 80/100Two weeks late submissions are scored as max. 60/100Others are scored as 0.

 

ekly Detailed Course Contents

WEEK NAME   SUBJECTS     Theoretical Slides Laboratory Suplementary Materials 1 Introduction /Fundementals  Image Representation, Image Reading/Writing, Indexing Images, Converting Image Classes  Research Allignment  PinHole Camera (Obscura) 2 Intensity Transformations & Spatial Filtering  Image Intensity Transformations, Histogram Processing, Equalization/Matching, Linear/NonLinear Filtering a. Lecture-2-Filtering_Derivative_Noise   b. Intensity Transformations   c1. Histogram Equalization   c2. Histogram Equalization with Step by Step Exp Base Paper Definition + Literatur Searching  a. Histogram Equalization Open Matlab Code   b. Local Histogram Equalization Open Matlab Code 3 Edge Detectors Primitive Detectors, Marr Hilderith, Canny Edge Detectors  Lecture-3-EdgeDetection Hmw#1: Histogram Matching a.  Marr Hilderith MatlabCode_Mohamed Athiqb. Canny Edge Detector Code Explanationc. Canny Edge Detector with Javad. Canny Edge Detector Tutorial Pagee. Canny Edge Detector without Matlabs functions 4 Image Features  Harris Corners, SIFT Features, SURF FEatures a.Lecture-4-Harris Corner Detection_Interest Points   b. Lecture-5-SIFT Hmw#2: Detecting Corners with Harris Operator  a. Harris Corner Detector Logic   b. Edge & Corner Detection Lecture   c. Original SIFT code   d. SIFT Tutorial by Utkarsh Sinhae. ASIFT Method   f. SIFT Matlab Code 5 Frequency Domain Processing  Fundemental Concepts, BandPass (Low, High, Specified Intervals) Filters, Fourier Transforms a.Chapter 5 – Fourier Transformb. FFT Tutorial Video   c. Fourier for Beginners. Hmw#3: SIFT Feature detection  a. Fourier Series and Transformation – Part 2   b. Fourier Series and Transformation – Part 3   c. Fourier Series Simpler Explanation Part I   d. Fourier Series Simpler Explanation Part II 6 Image Restoration Adding Noise, Noise Characteristics, Noise Filtering, Wiener Filtering, Geometric Transformations 7   Midterm     8 Color Image Processing  Color Spaces (RGB, HSI, HSV, Lab) 9 Wavelet  Wavelet Transform, Inverse Wavelet 10 Image Compression  Huffman Codes (Encoding/Decoding), Color Compression, JPEG Compression 11 Morphological Image Procesing  Dilation, Erosion, Opening, Closing, Mophological Reconstruction 12 Image Segmentation  Point/Line/Edge Detection, Hough Transform, Thresholding, Region-Based Segmentation 13 Object Recognition  Distance Measure, Shape/Pattern Matching 14 Case Studies 15   Final Exam

Additional  Reading

Video & Image Processing Tutorial Using C#/VS.Net, http://www.cogitance.com/files/videoprocessing/videoprocessing.htm