Module Specification |
| The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module. |
| Title | Image Processing | ||
| Code | ELEC319 | ||
| Coordinator |
Dr AA Al Ataby Electrical Engineering and Electronics Ali.Al-Ataby@liverpool.ac.uk |
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| Year | CATS Level | Semester | CATS Value |
| Session 2022-23 | Level 6 FHEQ | First Semester | 7.5 |
Aims |
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To introduce the basic concepts of digital image processing and pattern recognition. |
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Pre-requisites before taking this module (other modules and/or general educational/academic requirements): |
| ELEC270 Signals and Systems |
Co-requisite modules: |
Learning Outcomes |
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(LO1) Knowledge and understanding of Human Vision |
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(LO2) Knowledge and understanding of Image Histogram and its application |
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(LO3) Knowledge and understanding of Image Transformation methods and their applications |
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(LO4) Knowledge and understanding of Shapes and Connectivity |
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(LO5) Knowledge and understanding of Morphologocal Operations and their applications |
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(LO6) Knowledge and understanding of Noise Filtering methods in Image Processing |
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(LO7) Knowledge and understanding of Image Enhancement techniques |
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(LO8) Knowledge and understanding of Image Segmentation and its applications |
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(LO9) Knowledge and understanding of Image Compression methods |
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(LO10) Knowledge and understanding of Frequency Domain Image Analysis |
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(S1) On successful completion of the module, students should be able to show experience and enhancement of the following key skills: Independent learning Problem solving and design skills |
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(S2) After successful completion of the module, the student should have: The ability to apply relevant image enhancement techniques to a given problem. The necessary mathematical skills to develop standard image processing algorithms. The necessary Software skills (using MATLAB) to apply image processing methods and techniques on images. |
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Syllabus |
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Introduction to Image Processing |
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Teaching and Learning Strategies |
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COVID-19 Era Teaching and Learning Methods: Option a. Hybrid delivery, with social distancing on campus Teaching Method 1 - Online Asynchronous Lectures Teaching Method 2 - On-campus Tutorials with social distancing Teaching Method 3 - Formative Assessment Option b. Fully on-line delivery and assessment Teaching Method 1 - Online Asynchronous Lectures Teaching Method 2 - Online Synchronous Tutorials Teaching Method 3 - Formative Assessment Option c. Standard on-campus delivery with minimal social distancing Teaching Method 1 - On-campus Lectures Teaching Method 2 - On-campus Tutorials Teaching Method 3 - Formative Assessment |
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Teaching Schedule |
| Lectures | Seminars | Tutorials | Lab Practicals | Fieldwork Placement | Other | TOTAL | |
| Study Hours |
20 |
2 |
22 | ||||
| Timetable (if known) | |||||||
| Private Study | 53 | ||||||
| TOTAL HOURS | 75 | ||||||
Assessment |
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| EXAM | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
| (319) Written Exam Standard UoL penalty applies for late submission. Assessment Schedule (When): January | 0 | 100 | ||||
| CONTINUOUS | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
Reading List |
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| Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module. | |