CIS 601 Spring 2008
Computer Graphics and Image Processing
Instructor: Rolf Lakaemper
Office hours: Tu 5:30 to 7pm and by appointment (Phone: 215 204 7996, email: lakamper@temple.edu), or just come in.
The course will give a thorough introduction to classical methods of Computer Vision. The students will be introduced to image manipulation using methods of linear and non linear signal processing as well as statistical methods of image processing. The course will build on theoretical foundation as well as on hands on experience using MATLAB as programming language. The first part of the course will mostly be in lecture style. The second part will consist of student (group) presentations of projects. Grading will be based on class participation (incl. in class mini quizzes), homework assignments, projects, project presentation and final exam.
I expect you to suggest projects of your interest to me. Of course i will help finding an appropriate project in cooperation with you. Project suggestions in the form of a 1-2 page description have to be handed in before spring break. You will have to make a short presentation (15 minutes) of the current state of the project in week 10, by appointment in my office. The final project presentation must be a full 45 minute presentation with power point (or similar) slides.
CLICK HERE FOR SCORES
Office hours: Tu 5:30 to 7pm and by appointment (Phone: 215 204 7996, email: lakamper@temple.edu), or just come in.
Schedule:
Tuesday 7:25 - 9:55 PM Tuttleman Learning Center 302
Textbook:
- Gonzales/Woods: Digital Image Processing Third Edition, Prentice Hall ISBN-13:978-0-13-168728-8
- Different Research Articles
Course Overview
The course will give a thorough introduction to classical methods of Computer Vision. The students will be introduced to image manipulation using methods of linear and non linear signal processing as well as statistical methods of image processing. The course will build on theoretical foundation as well as on hands on experience using MATLAB as programming language. The first part of the course will mostly be in lecture style. The second part will consist of student (group) presentations of projects. Grading will be based on class participation (incl. in class mini quizzes), homework assignments, projects, project presentation and final exam.
Course Schedule
- Week 01 (Jan 22): Introduction to Image Processing & MATLAB. [Chpater 1,2 of Textbook]
- Week 02 (Jan 29): Intensity Transforms & Spatial Filtering [Chapter 3]
- Week 03 (Feb 05): Morphological Image Processing [chpater 9]
- Week 04 (Feb 12): Image Processing in the Frequency Domain, 1D fourier filtering, applications in Object detection and recognition [chapter 4]
- Week 05 (Feb 19): Image Processing in the Frequency Domain, 2D fourier filtering
- Week 06 (Feb 26): Image Restoration and Reconstruction, Color Image Processing [chapter 5,6]
- Week 07 (March 04): Wavelets [chapter 7]
- Week 08 (March 11): (spring break)
- Week 09 (March 18): Image Compression: jpg, gif, ... [chapter 8]
- Week 10 (March 25): Segmentation [chapter 10 & different research articles]
- Week 11 (April 01): Different Representations & Statistical Approaches to Computer Vision [chapter 11, parts of chapter 12, different research articles]
- Week 12 (April 08): The previous topic continued, catching up.
- Week 13 (April 15): Presentations 1-2, discussion
- Week 14 (April 22): Presentations 3-4, discussion
- Week 15 (April 29): Presentation 5, discussion, review for final exam
Student Projects
I expect you to suggest projects of your interest to me. Of course i will help finding an appropriate project in cooperation with you. Project suggestions in the form of a 1-2 page description have to be handed in before spring break. You will have to make a short presentation (15 minutes) of the current state of the project in week 10, by appointment in my office. The final project presentation must be a full 45 minute presentation with power point (or similar) slides.
Slides
- Introduction
- MATLAB Overview
- Image Fundamentals
- Spatial Image Enhancement
- Spatial II & Frequency Domain (FFT)
- 3D Patch detection using extended EM
- Shape Recognition Part I
- Shape Recognition Part II
MATLAB Demo Files
PAPERS
- Belongie/Malik: Shape Context
- Sketch Based Retrieval using Angular Partitioning
- Rotation Invariant Shape Context
- Zhang, Lu: A Comparative Study on Shape Retrieval Using Fourier Descriptors with Different Shape Signatures
- L. J. Latecki and R. Lakaemper: Application of Planar Shape Comparison to Object Retrieval in Image Databases. Pattern Recognition (PR), pp. 15-29, 35 (1), 2002.
- Paper on Vantage Object Selection
- more papers will be added during the course
- Sketch Based Retrieval using Angular Partitioning
Quizzes
HOMEWORK
- Homework must be sent as zipped email-attachment to lakamper@temple.edu
- Please name the zip-file: hwXX_NNNNN, XX=number of assignment, NNNNNN=your name
- The attachment must include a single folder with all necessary files
- Please make the subject of the email: homework 601/XX All homework assignments are 1 week assignments.
- Moving Object Detection
- Find the Gears
- Image Retrieval by Sketch
- Paper Revision
- Circle Detection using Hough Transform
- Find the Gears
Scores
CLICK HERE FOR SCORES