| TSBB08 |
Digital Image Processing, 6 ECTS credits.
/Digital bildbehandling grundkurs/
For:
BME
D
I
Ii
IT
MED
U
Y
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Prel. scheduled
hours: 62
Rec. self-study hours: 98
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Area of Education: Technology
Main field of studies: Electrical Engineering
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Advancement level
(G1, G2, A): A
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Aim:
The course aims to provide basic knowledge in 2D signal processing and a systematic description about the classical methods and tools for digital image processing. This means that a student which has taken this course is expected to be able to:
- Describe basics regarding the generalization from 1-D to 2-D signal processing: Continuous and discrete Fourier transform with accompanying theorems, sampling and reconstruction, convolution, re-sampling and interpolation, scale space.
- Interpret the result of a 2-D Fourier transform of an image, such as what is a spatial frequency and be acquainted with the most common convolution kernels and describe their appearance in the spatial and Fourier domain, respectively.
- Describe most of the classical image processing methods in the course content, see below.
- Solve simple image processing problems using Matlab.
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Prerequisites: (valid for students admitted to programmes within which the course is offered)
1-D signal processing: deterministic signals, linear systems, convolution, continuous and discrete Fourier transform sampling and reconstruction, the sampling theorem, basic filters (low-pass, high-pass, and band-pass). Linear algebra: vector, matrix, determinant, scalar product, bases, the least square method. One- and multidimensional calculus. Programming in one of the following languages: C, C++, Java, Ada or Matlab.
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshhold requirements for progression within the programme, or corresponding.
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Supplementary courses:
Multidimensional signal analysis, Computer Vision, Image Sensors, Image and Audio Coding, Neural Networks and Learning Systems, Medical Image Analysis, Visual Object Recognition and Detection, Project courses regarding images.
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Organisation:
The course consists of lectures, lessons and laboratory assignments based on Matlab.
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Course contents:
The lectures:
- Concepts and definitions. From 1-D to 2-D Fourier transform. Continuous and discrete Fourier transform, DFT, FFT. Sampling and reconstruction. Convolution and filtering, translation, scaling, derivative, rotation, and other linear operations on digital images.
- Convolution kernels in the spatial and Fourier domain, low-pass,
derivative (sobel).
- Resampling and interpolation. Scale space.
- Color models. Color transformations. Color segmentation.
- Segmentation: Regional growing, watersheds, labeling. Operations on histogram. Thresholding: automatic, local and with hysteres.
- Binary image processing: Morphological operations, distance transform, connectivity preserving operations, feature extraction, chain code, polygon approximation and Fourier descriptors.
- Matched filters and pattern recognition. Edge detection with Sobel and Canny. Hough transform. Line detection. Corner detection. The structure tensor.
- Image restoration: Inverse filtering, wiener filtering.
- Non-linear filters: Homomorphic filtering, median filter, max- and min-filter, etc.
The computer exercises:
- 1) Operations on gray scale images. Linear filters in the spatial and Fourier domain.
- 2) Resampling and interpolation.
- 3) Operations on binary images. Histogram and color tables.
- 4) Automatic thresholding and simple OCR (Optical Character Recognition).
- 5) Segmentation of cells in microscopy images.
- 6) Automatic counting of blood cells.
- 7) Image restoration. Edge detection with Hough transform and Canny. Non-linear filters.
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Course literature:
- The book �?oDigital Image Processing�?� by Gonzalez and Woods.
- Laboratory instructions: Digital Image Processing.
- Power-Pointpresentations from the lectures.
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Examination: |
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A written examination
Laboratory work
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4 ECTS
2 ECTS
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Course language is Swedish/English.
Department offering the course: ISY.
Director of Studies: Klas Nordberg
Examiner: Maria Magnusson
Link to the course homepage at the department
Course Syllabus in Swedish
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