WXGE6103

Digital Image Processing

Semester 2, Session 2013/2014

Agenda

Lecturer Information.Course Overview / Requirements.Introduction to Image Processing.

Contact Information

Lecturer: Mogeeb MoslehEmail: MogeebMosleh@Gmail.com

Course Description

Course Code: Course Title: Digital Image

Processing.Course Type: Core Course for (Telecommunication

Department)

Course Contents Introduction to DIP. Digital Image Fundamentals (1). Digital Image Fundamentals (2). Image Enhancement in the Spatial Domain. Image Enhancement in the Frequency Domain. Image Restoration. Color Image Processing. Image Compression. Morphological Image Processing. Image Segmentation. Representation and Description Pattern & Object Recognition.

Course ObjectivesThis module aims to: Develop a theoretical foundation of fundamental

Digital Image Processing concepts. Provide mathematical foundations for digital

manipulation of images; image acquisition; preprocessing; segmentation; Fourier domain processing; and compression.

Gain experience and practical techniques to write programs using MATLAB language for digital manipulation of images; image acquisition; preprocessing; segmentation; Fourier domain processing; and compression.

Expected Learning Outcomes1- Knowledge and understanding: Have a clear understanding of the principals the Digital Image

Processing terminology used to describe features of images. Have a good understanding of the mathematical foundations for

digital manipulation of images; image acquisition; preprocessing; segmentation; Fourier domain processing, compression and analysis.

Be able to write programs using Matlab language for digital manipulation of images; image acquisition; preprocessing; segmentation; Fourier domain processing; and compression.

Have knowledge of the Digital Image Processing Systems. Be able to understand the documentation for, and make use of,

the MATLAB library and MATLAB Digital Image Processing Toolbox (IPT).

Learn and understand the Image Enhancement in the Spatial Domain.

Learn and understand the Image Enhancement in the Frequency Domain.

Understand the Image Restoration, Compression, Segmentation, Recognition, Representation and Description.

Expected Learning Outcomes2- Cognitive skills (thinking and analysis): Be able to use different digital image processing

algorithms. Be able to design, code and test digital image processing

applications using MATLAB language. Be able to use the documentation for, and make use of,

MATLAB library and MATLAB Digital Image Processing Toolbox (IPT).

Analyze a wide range of problems and provide solutions related to the design of image processing systems through suitable algorithms, structures, diagrams, and other appropriate methods.

Practice self-learning by using the e-courses and web materials.

Expected Learning Outcomes3- Communication skills (personal and

academic). Display personal responsibility by working to multiple

deadlines in complex activities. Be able to work effectively alone or as a member of a small

group working on some programming tasks.

4- Practical and subject specific skills (Transferable Skills) Plan and undertake a major individual image processing

project. Be able to work effectively alone or as a member of a small

group working on some programming tasks. Prepare and deliver coherent and structured verbal and

written technical reports Use laboratory equipment effectively. Use the scientific literature effectively.

Course Resources1. “Digital Image Processing”, 3rd

edition, Rafael C. Gonzalez, Richard E. Woods, Prentice Hall

2. “Digital Image Processing Using Matlab”, Rafael C. Gonzalez, Richard E. Woods, Prentice Hall

3. “Digital Image Processing”, 2nd edition, K.R. Castleman, Prentice Hall

4. “Computer Vision & Image Processing”, Scott E. Umbaugh, Prentice Hall

Course Requirements - Recap

5%15%

10%

20%

50%

Grade 5% •Attendance/ Participation

15% •Assignments / Tutorial

10% •Mid term Exam

20% •Group Project/ Presentation

50% •Final Exam

Evaluation & Weightage

Continuous Assessments : 50% Attendance / Participation: 5%Assignments/Tutorials: 15%Mid Semester Exam: 10%Group Project/ Presentations: 20%

Final Examination: 50%

Attendance/ParticipationAttendance

Attendance must be 80% or more.Absent – please provide a letter.Absent > 3 times – provide a reasonable

reasons.Bar from exam.Switch off hand phone during lecture.

ParticipationActive Student.

5%

Assignments/Tutorials

You will be assigned a number of related tutorials.

You will need to read and answer them and return soft and hard copies of your answers.

Tutorial tasks are very important for understanding the concepts and applying them in real scenarios.

Projects and assignments – on time

15%

Mid Term Exam

You will be given ONE MID TERM EXAM on certain topics that will be covered in the lectures.

Format will be discussed later.Topics covered will be announced later.Time: After Mid Semester Break.

10%

Group Project/Presentation Self-select into groups (2-3 students each) Each group will be hired to develop a system. You will have to explore the assigned system and

follow the software engineering process in developing your system.

You can use any programming language and/or tool to implement and develop the assigned system.

Your group project MUST be documented well and a report must be submitted in soft and hard copies.

Prepare a 20 to 25 minutes presentation and demo. 20%

Format of SubmissionHard copyWord-processed Include the following information:

Title of assignment & (due date)Your name + (Matrics number)Your e-mail addressLecturer’s name

To be submitted to me during class.

Final ExamGive certain scenario and apply concepts that

have been learnt throughout the semester.Includes material from entire semester? All materials are important for the final

exam

50%

Any Questions?