MEng Mechatronic Engineering with Industrial Experience / Course details

Year of entry: 2024

Course unit details:
Digital Image Processing

Course unit fact file
Unit code EEEN40161
Credit rating 15
Unit level Level 4
Teaching period(s) Semester 1
Available as a free choice unit? No

Overview

  • Introduction to digital image processing: light, cameras and the human visual system; digital systems for image capture and processing. (JPO)
  • Colour representation and encoding: RGB; YUV; HSV. (JPO)
  • The 2D Discrete Fourier Transform and Discrete Cosine Transform. (HY)
  • Image encoding: quantization and image compression; relevant standards, e.g. JPEG; H264 and HDTV. (HY)
  • Basic filtering operations: image smoothing; noise reduction and sharpening. (HY)
  • Image enhancement: histogram-based equalisation; noise smoothing; edge detection; Hough Transform; morphological operators (erosion and dilation). (JPO)
  • Applications: Object detection, recognition and tracking; motion estimation and 3-D reconstruction. (JPO)
  • Real-time Implementation: Hardware and software platforms. (JPO)

Aims

The course unit aims to:

  • Provide a thorough and complete introduction to the subject of modern digital image processing.
  • Emphasise the links between the theoretical foundations of the subject and the essentially practical nature of its realisation.
  • Encourage and understanding through the use of algorithms and real world examples,
  • Provide useful skills through detailed practical laboratories, which explore digital image processing software and hardware.

Learning outcomes

Students will be able to:

Knowledge and understanding

Demonstrate a mastery and detailed knowledge of the founding principles of digital image processing, and understand how the various fundamental equations both operate and are constructed.

Intellectual skills

To recognise the different classes of problem in digital image processing, and to decide upon appropriate methodologies in their solution.

Practical skills

Program and debug existing image processing hardware platforms, and devise, code and test off-line and real-time image processing algorithms, both using PCs and dedicated image processing hardware.

Transferable skills and personal qualities

Perform literature searching; scientific report writing; use of graphing and presentation packages; project planning; team work; use of the Blackboard system discussion forum.

Assessment methods

Unseen Written Examination

The form of the examination: 4 questions, answer all questions

Length of examination: 3 hours

Calculators are permitted

The unseen written examination forms 70% of the total unit assessment

Course Work- Laboratories

The number of laboratories: 3

The length of laboratory: 6 hours

Two of these laboratories are assessed by a lab report

Maximum mark for the laboratories forms 30% of the overall unit mark

 

Study hours

Scheduled activity hours
Lectures 26
Practical classes & workshops 18
Tutorials 6
Independent study hours
Independent study 100

Teaching staff

Staff member Role
Hujun Yin Unit coordinator

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