The minor consists of three subjects and a project. The three subjects are each partly theory and partly assignments. The learning outcomes are described per subject:

Subject 1

• Can carry out and provide reasons for the following image acquisition processes on a PC/laptop: camera, lens, lighting and interfaces.
• Can apply the following enhancement operators in OpenCV: Image algebra, geometric operators, synthetic images and contrast manipulation.
• Can apply the following segmentation operators in OpenCV: thresholding, labelling and blob measurement.
• Can apply the following feature extraction operators in OpenCV: filters, edge detection, binary morphology and colour image processing.
• Can apply the following classification operators in OpenCV: blob analysis, neural networks, blob matchers.

• The student can implement a set of vision operators in ANSI-C programming language based on a functional description and considering limitations such as performance and memory use.
• The student can solve a vision problem with an embedded system using these self-implemented operators: the classification of the three figures - circle, square and triangle. The student demonstrates the solution.
• The student can describe in a short and concise PowerPoint presentation the functional working and technical realisation of a unique operator.
• The student can create a unique vision operator in ANSI-C programming language and demonstrate how it works.

Subject 2

• Knows what digital image processing is, knows the backgrounds, frequency bands and is aware of the fundamental steps for digital image processing.
• Is aware of digital image fundamentals relating to the human eye, light and the electromagnetic spectrum. Is familiar with various sensors for the purpose of image acquisition and a simple image formation model.
• Is familiar with physical characteristics of optical instruments and of light and can apply these.

• Can apply the concepts of image sampling and quantization. Knows the basic relationships between pixels. Can apply mathematical tools that are important for digital image processing.
• Is familiar with intensity transformations operators (e.g. image negatives, log transformations power_law (Gamma) transformations and piecewise-linear transformations) and can apply these.
• Is familiar with histogram processing (e.g. histogram equalization, histogram matching (specification), local histogram processing and using histogram statistics for image enhancement) and can apply these.
• Is familiar with the fundamentals of spatial filtering and different filters (e.g. smoothing spatial filters and sharpening spatial filters) and can apply these.
• Is familiar with morphological image processing operators (e.g. erosion, dilation, opening, closing) and can apply these.
• Is familiar with Image segmentation operators (e.g. point, line, and edge detection) and various methods to threshold (e.g. basic global thresholding, optimum global thresholding using Otsu’s method) and can apply these.
• Can describe the shape and boundaries of a segment using statistical moments.

Subject 3

• Knows the application of machine learning algorithms, their training, fine-tuning and performance analysis.
• Can use tools for designing, implementing and evaluating machine learning.
• Can prepare data, train an algorithm and evaluate the performances of machine learning applied to image processing, in particular object classification.

• Knows the application of deep learning algorithms, their training, fine-tuning and performance analysis.
• Can use tools for designing, implementing and evaluating deep learning.
• Can prepare data, train an algorithm and evaluate the performances of deep learning applied to image processing, in particular object classification.

Competences

In this minor you work on all Bachelor of Engineering competences:

C1 Analysing – level 3
C2 Designing – level 3
C3 Realising – level 3
C4 Administering – level 2
C5 Managing – level 2
C6 Advising – level 1
C7 Researching – level 2
C8 Professional development – level 2

You work within the professional task Developing Embedded Systems.