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Course Catalog 2010-2011
MIT-3216 Measurement Based on Digital Image 1, 5 cr |
Person responsible
Heimo Ihalainen, Kalle Marjanen
Lessons
Study type | P1 | P2 | P3 | P4 | Summer | Implementations | Lecture times and places |
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Requirements
Exercises, assignments and exam.
Principles and baselines related to teaching and learning
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Learning outcomes
This course provides basic understanding of methods for measurements based on digital image, digital image processing and statistical analysis of image information. Exercises and assignments focus on the computational methods for measurements based on digital image.
Content
Content | Core content | Complementary knowledge | Specialist knowledge |
1. | Various imaging systems and their properties. Representation and compression of digital images. | Basic optics, properties of radiation and noise. Reversible and irreversible packing. | Basic noise statistics. |
2. | Image preprocessing methods. Using color images. | Background correction, digital filtering. Color representation. | Bayer-matrix for color images. |
3. | Methods developed for machine vision e.g. edge detection, segmentation. | Object location. Edge locations. | |
4. | Statistical image analysis and texture analysis. | Basic statistics. Analysis based on histograms. | Analysis based on 2D-spectrum. |
5. | Computer exercises and assignments cover the above topics in practice. |
Evaluation criteria for the course
Exercises, assignments and exam.
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Study material
Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
Book | Digital Image Processing | Gonzales, Rafael C. & Woods, Richard E. | English |
Prerequisite relations (Requires logging in to POP)
Correspondence of content
There is no equivalence with any other courses
Additional information
Suitable for postgraduate studies
More precise information per implementation
Implementation | Description | Methods of instruction | Implementation |