Industrial Vision and Processing
Necessity of digital image processing stems from the importance of the processing of a scene data for a human interpretation and for an autonomous machine perception. Digital image processing has a broad range of applications such as remote sensing, image and data storage for transmission and industrial automation.
This module aims to provide the fundamentals of digital signal processing, and develop students’ knowledge from basic signal processing techniques to advanced image processing. It covers the principles of image formation, sampling and quantization, which will allow them to investigate image-processing techniques. Students will be equipped with the knowledge related to image intensity transformations and spatial filtering to apply this knowledge in image enhancement domain in both spatial and frequency domains. Dealing with different types of noise models and achieving image restoration is covered. The module will familiarize students with morphological image processing, colour image processing and image segmentation to help students apply these techniques in real world problems.
Principal Learning Outcomes
By the end of the module, students will be able to:
- Demonstrate an understanding about image formation and the role of human visual system plays in perception of grey and colour image data.
- Analyse and implement image-processing algorithms on computers.
- Apply principles and techniques of digital image processing in image enhancement and image restoration.
- Design and create practical solutions to a range of common image processing problems and to critically assess the results of their solution, include shortcomings.