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FIT3081 Image processing - Semester 1, 2014

This unit covers fundamental techniques in image processing. Topics include image representation and enhancement, thresholding, image algebra, neighbourhood operations on images, Fourier methods, edge detection, feature extraction and representation, shape, texture, segmentation, classification, restoration, image compression, and colour and multiband image processing.

Mode of Delivery

Malaysia (Day)

Workload Requirements

Minimum total expected workload equals 12 hours per week comprising:

(a.) Contact hours for on-campus students:

  • Two hours of lectures
  • One 2-hour laboratory

(b.) Additional requirements (all students):

  • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

Unit Relationships

Prohibitions

CSE3314

Prerequisites

FIT2004 (or CSE2304) and FIT2014 (or CSE2303)

Chief Examiner

Campus Lecturer

Malaysia

Dr Anuja Dharmaratne

Consultation hours: Mon 2-5, Wed 2-5

Tutors

Malaysia

Dr Anuja Dharmaratne

Consultation hours: Mon 2-5, Wed 2-5

Your feedback to Us

Monash is committed to excellence in education and regularly seeks feedback from students, employers and staff. One of the key formal ways students have to provide feedback is through the Student Evaluation of Teaching and Units (SETU) survey. The University’s student evaluation policy requires that every unit is evaluated each year. Students are strongly encouraged to complete the surveys. The feedback is anonymous and provides the Faculty with evidence of aspects that students are satisfied and areas for improvement.

For more information on Monash’s educational strategy, see:

www.monash.edu.au/about/monash-directions/ and on student evaluations, see: www.policy.monash.edu/policy-bank/academic/education/quality/student-evaluation-policy.html

Previous Student Evaluations of this Unit

Based on previous student feedback this unit is considered to be well structured and students are satisfied with the delivery of lectures as well as the unit content. For this semester lecture slides have been shortened, updated and re-organized.

 The following subtopics have been added:

  1. Color Models (RGB, HSV, etc)
  2. Image Noise, Noise types and noise removal
  3. Hough transform for straight line detection
  4. Morphological operations
  5. Connected Component labeling
  6. Size filter

The content on the following subtopics have been reduced:

  1. Image acquisition methodologies
  2. Segmentation
  3. Image representation & Description
  4. Organization of visual systems in the brain

If you wish to view how previous students rated this unit, please go to
https://emuapps.monash.edu.au/unitevaluations/index.jsp

Academic Overview

Learning Outcomes

At the completion of this unit students will have -Developed the ability to:
  • understand the processes of image formation, acquisition, processing and analysis;
  • develop programs for manipulating grey level, colour and multi-spectral images; and
  • use standard image processing software;
  • undertake computer analysis of medical, remotely-sensed, document, and other images.
Developed attitudes that enable them to:
  • understand the role of visual information processing and analysis;
  • apply the theory and methods in practical problem solving.
Developed the skills to:
  • write programs to carry out basic image processing tasks such as image denoising, image filtering and segmentation of an image in its constituent parts or objects;
  • write programs to carry out advanced image processing and analysis tasks such as image segmentation, image, image classification, image data mining, and robotic vision;
  • build a software system for processing and analysis of image data.
Demonstrated the communication and teamwork skills necessary to:
  • function as an image processing specialist in a group which is involved in developing a major software system;
  • produce appropriate documentation.

Unit Schedule

Week Activities Assessment
0   No formal assessment or activities are undertaken in week 0
1 Course overview, Why digital image processing is important  
2 Human Visual Perception, Image Processing using Java  
3 Introduction to Image Processing algorithms  
4 Image enhancement in Spatial domain  
5 Edge Sharpening, Edge detection  
6 Edge detection (continued), Hough transform Assignment 1 due Friday
7 Image enhancement in frequency domain  
8 Image segmentation  
9 Boundary extraction  
10 Edge thinning, Skeletonization, Medial axis transformation  
11 Image compression, Texture analysis  
12 Recap Assignment 2 due Friday
  SWOT VAC No formal assessment is undertaken in SWOT VAC
  Examination period LINK to Assessment Policy: http://policy.monash.edu.au/policy-bank/
academic/education/assessment/
assessment-in-coursework-policy.html

*Unit Schedule details will be maintained and communicated to you via your learning system.

Teaching Approach

Lecture and tutorials or problem classes
This teaching and learning approach provides facilitated learning, practical exploration and peer learning

Assessment Summary

Examination (3 hours): 70%; In-semester assessment: 30%

Assessment Task Value Due Date
Assignment 1 10% Week 6, Friday
Assignment 2 20% Week 12, Friday
Examination 1 70% To be advised

Assessment Requirements

Assessment Policy

Assessment Tasks

Participation

  • Assessment task 1
    Title:
    Assignment 1
    Description:
    Writing a proposal - a computer vision system needs to be implemented for a real life problem as the first assignment. A complete proposal together with the higher level system design has to be prepared. It should highlight the Image processing algorithms that can be used in the implementation.
    Weighting:
    10%
    Criteria for assessment:

    1. Satisfactory documenting according to the requirements of the assignment

    2. Acceptable Higher level system design

    3. The implementation plan

    4. Demonstrate the use of Image processing algorithms

    Due date:
    Week 6, Friday
  • Assessment task 2
    Title:
    Assignment 2
    Description:
    Programming and Analysis for Image Processing Tasks
    Weighting:
    20%
    Criteria for assessment:

    1. Satisfactory implementation according to the requirements of the assignment

    2. Structure, modularity and efficiency of code

    3. Ease of use of program user interface

    4. Evidence of testing

    Due date:
    Week 12, Friday

Examinations

  • Examination 1
    Weighting:
    70%
    Length:
    3 hours
    Type (open/closed book):
    Closed book
    Electronic devices allowed in the exam:
    None

Learning resources

Reading list

R. C. Gonzalez and R. E. Woods, Digital Image Processing using MATLAB, Prentice Hall, 2004.

A. K. Jain, Fundamentals of Digital Image Processing, Prentice-Hall, 1990.

W. Niblack, An Introduction to Digital Image Processing, PHI, 1986.

D. H. Ballard and C. M. Brown, Computer Vision, Prentice-Hall, 1982.

M. D. Levine, Vision in Man and Machine, McGraw-Hill, 1995.

R. Jain, R. Kasturi, and B. G. Schunck, Machine Vision, McGraw-Hill, 1995.

C. Watkins, A. Sadun, and S. S. Marenka, Modern Image Processing: Warping, Morphing, and Classical Techniques, Academic Press, 1993.

H. R. Myer and A. R. Weeks, The Pocket Handbook of Image Processing Algorithms in C, Prentice-Hall, 1993.

S. E. Umbaugh, Computer Vision and Image Processing: a practical approach using CVIPtools, Prentice Hall PTR, 1998.

Monash Library Unit Reading List (if applicable to the unit)
http://readinglists.lib.monash.edu/index.html

Faculty of Information Technology Style Guide

Feedback to you

Examination/other end-of-semester assessment feedback may take the form of feedback classes, provision of sample answers or other group feedback after official results have been published. Please check with your lecturer on the feedback provided and take advantage of this prior to requesting individual consultations with staff. If your unit has an examination, you may request to view your examination script booklet, see http://intranet.monash.edu.au/infotech/resources/students/procedures/request-to-view-exam-scripts.html

Types of feedback you can expect to receive in this unit are:

  • Informal feedback on progress in labs/tutes
  • Graded assignments with comments

Extensions and penalties

Returning assignments

Assignment submission

It is a University requirement (http://www.policy.monash.edu/policy-bank/academic/education/conduct/student-academic-integrity-managing-plagiarism-collusion-procedures.html) for students to submit an assignment coversheet for each assessment item. Faculty Assignment coversheets can be found at http://www.infotech.monash.edu.au/resources/student/forms/. Please check with your Lecturer on the submission method for your assignment coversheet (e.g. attach a file to the online assignment submission, hand-in a hard copy, or use an online quiz). Please note that it is your responsibility to retain copies of your assessments.

Online submission

If Electronic Submission has been approved for your unit, please submit your work via the learning system for this unit, which you can access via links in the my.monash portal.

Required Resources

Please check with your lecturer before purchasing any Required Resources. Limited copies of prescribed texts are available for you to borrow in the library, and prescribed software is available in student labs.

Software

  • Java Development Kit
  • Netbeans

These are freely available from:

JDK - http://www.oracle.com/technetwork/java/javase/downloads/jdk6-jsp-136632.html

Netbeans - http://netbeans.org/

Prescribed text(s)

Limited copies of prescribed texts are available for you to borrow in the library.

Gonzalez and Woods. (2001). Digital Image Processing. (2nd Edition) Prentice-Hall.

Examination material or equipment

Writing tools.

Other Information

Policies

Monash has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and to provide advice on how they might uphold them. You can find Monash’s Education Policies at: www.policy.monash.edu.au/policy-bank/academic/education/index.html

Key educational policies include:

Faculty resources and policies

Important student resources including Faculty policies are located at http://intranet.monash.edu.au/infotech/resources/students/

Graduate Attributes Policy

Student Charter

Student services

Monash University Library

Disability Liaison Unit

Students who have a disability or medical condition are welcome to contact the Disability Liaison Unit to discuss academic support services. Disability Liaison Officers (DLOs) visit all Victorian campuses on a regular basis.