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TITLE Introduction to Digital Image Processing

LEVEL 02 - Years 2, 3 in Modular Undergraduate Course


DEPARTMENT Artificial Intelligence

DESCRIPTION This study-unit is about the fundamentals of computational image analysis and it will be explored in terms of image enhancement and image information extraction. We will study various image enhancement and linear filtering techniques. The unit will be useful for students interested in image analysis related to areas such as visual quality inspection, image databases, multimedia management, animation, GIS, computer graphics, medical imaging, remote sensing and robotics.

Hands on experience with Matlab and/or Python will be gained by the implementation of several important image analysis techniques which may be applied in different applications. Insight on how the brain processes visual information will also be given during the lectures.

Specific topics include, but are not limited to:
- Color spaces
- Image enhancement (e.g. thresholding, histogram equalization, enhancement of edges) based on point processing
- Image sharpening
- Smoothing using average Gaussian filter
    - spatial and frequency domain
- Morpholoigcal operations (dilation, erosion, opening, closing, ...)
- Keypoint detection in scale space

Study-unit Aims:

The aims of this study-unit are to:
- Introduce students to the basic image processing techniques that are widely used in the ever increasing computer vision applications.
- Expose students to how visual information is processed by the brain and to how computer scientists attempt to simulate parts of its properties.
- Provide hands-on experience to students with popular tools, such as Matlab and Python for image processing. The VLFeat and OpenCV libraries will be used.
- Provide the fundamentals upon which computer graphics and computer vision are built.

Learning Outcomes:

1. Knowledge & Understanding:

By the end of the study-unit the student will be able to:
- Explain in simple terms the mechanism and rationale of basic image processing tools.
- Explain the basic understanding of how the visual cortex of the brain processes visual information.
- Identify which techniques are mostly appropriate for a given application.
- Understand the trade-off between the effectiveness and efficiency of the covered techniques.

2. Skills:

By the end of the study-unit the student will be able to:
- Use any of the techniques covered to process images coming from different applications.
- Compare the appropriateness of a number of image processing techniques to solve simple problems.
- Implement basic image processing functions using state of the art technologies.
- Proceed with advanced image processing and computer vision techniques in the third year.

Main Text/s and any supplementary readings:

Digital Image Processing (3rd Edition) Hardcover – August 31, 2007
by Rafael C. Gonzalez (Author), Richard E. Woods (Author)
ISBN-13: 978-0131687288 ISBN-10: 013168728X Edition: 3rd

ADDITIONAL NOTES Pre-requisite Qualifications: Pure Mathematics (Intermediate Level)

STUDY-UNIT TYPE Lecture and Tutorial

Assessment Component/s Resit Availability Weighting
Presentation Yes 30%
Project Yes 70%

LECTURER/S George Azzopardi (Co-ord.)
Adam Gauci

The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints.
Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the study-unit description above applies to the academic year 2017/8, if study-unit is available during this academic year, and may be subject to change in subsequent years.
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