Announcements

  1. (Sep 14) Course page is online.
  2. (Sep 14) Syllabus is available.
  3. (Sep 19) Slides for introduction are available.

Personnel

Instructor: Selim Aksoy (Office: EA 422, Email: )
TA: TBD

Course Information

Schedule: Wed 8:40-10:30, Fri 10:40-12:30 (EB 204)
Office hours: Selim Aksoy: TBD
TA: TBD
Catalog description: Image acquisition, sampling and quantization. Spatial domain processing. Image enhancement. Texture analysis. Edge detection. Frequency domain processing. Color image processing. Mathematical morphology. Image segmentation and region representations. Statistical and structural scene descriptions. Applications.
Prerequisites: Good background on high-level programming, data structures, linear algebra, and vector calculus. No prior knowledge of image processing or computer vision is assumed.
Syllabus: Make sure you read the syllabus for course details.

Texts

Lectures

Topics

Contents

Introduction

[ Slides ]

Topics:
  • Overview
  • Example applications
Demos:

Digital Image Fundamentals

Topics:
  • Acquisition, sampling, quantization
  • Image enhancement
  • Image formats
  • Linear algebra and MATLAB review
Readings:
  • SS Ch 1, 2
  • GW Ch 1, 2, 3.1-3.4
References:
  • R. C. Gonzales, R. E. Woods, "Review material and slides on linear algebra, probability, and linear systems," 2002.
Software:

Binary Image Analysis

Topics:
  • Pixels and neighborhoods
  • Mathematical morphology
  • Connected components analysis
  • Automatic thresholding
Readings:
  • SS Ch 3.1-3.5, 3.8
  • GW Ch 2.5, 9.1-9.5, 10.3
References:
Software:

Filtering

Topics:
  • Spatial domain filtering
  • Frequency domain filtering
  • Image enhancement
Readings:
  • SS Ch 5.1-5.5, 5.10-5.11
  • GW Ch 3.5-3.8, 4
Software:

Edge Detection

Topics:
  • Edges, lines, arcs
  • Hough transform
Readings:
  • SS Ch 5.6-5.8, 10.3-10.4
  • GW Ch 10.1-10.2
References:
Software:

Local Feature Detectors

Topics:
  • Corners and other interest points
  • Invariants
References:
Software:

Color Image Processing

Topics:
  • Color spaces and conversions
Readings:
  • SS Ch 6.1-6.5
  • GW Ch 6

Texture Analysis

Topics:
  • Statistical approaches
  • Structural approaches
Readings:
  • SS Ch 7
  • GW Sec 11.3.3

Image Segmentation

Topics:
  • Histogram-based approaches
  • Clustering-based approaches
  • Region growing
  • Split-and-merge
  • Morphological approaches
  • Graph-based approaches
Readings:
  • SS Ch 10.1
  • GW Ch 10.4-10.5
References:
Software:

Representation and Description

Topics:
  • Image representations and descriptors
  • Region representations and descriptors
Readings:
  • SS Ch 10.2, 3.7
  • GW Ch 11
References:

Pattern Recognition Overview

Topics:
  • Brief introduction to pattern recognition
Readings:
  • SS Ch 4
  • GW Ch 12.1-12.2
References:
Software:

Case Studies

Topics:
  • Image retrieval
  • Image classification
  • Object recognition
References:

Exams

Homework

  1. Homework assignment 1 (Due: TBD as online submission)
  2. Homework assignment 2 (Due: TBD as online submission)
  3. Homework assignment 3 (Due: TBD as online submission)

Please make sure you fully understand the honor code in the syllabus as well as the Bilkent University Policy on Academic Honesty (in Turkish) and the Rules and Regulations of the Higher Education Council (YOK) (in Turkish). Cheating and plagiarism on exams, quizzes, and assignments will be punished according to these regulations.

Project

TBD

Grading Policy

Homework:35%
Quiz:10%
Exam:25%
Project:25%
Class participation:5%

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