Study Guide@lith
 

Linköping Institute of Technology

 
 
Valid for year : 2017
 
TSBB08 Digital Image Processing, 6 ECTS credits.
/Digital bildbehandling grundkurs/

For:   BME   D   I   Ii   IT   MED   U   Y  

 

Prel. scheduled hours: 62
Rec. self-study hours: 98

  Area of Education: Technology

Main field of studies: Electrical Engineering

  Advancement level (G1, G2, A): A

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.


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.

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.

Organisation:
The course consists of lectures, lessons and laboratory assignments based on Matlab.

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.


Course literature:
  • The book �?oDigital Image Processing�?� by Gonzalez and Woods.
  • Laboratory instructions: Digital Image Processing.
  • Power-Pointpresentations from the lectures.


Examination:
A written examination
Laboratory work
4 ECTS
2 ECTS
 



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

Linköping Institute of Technology

 


Contact: TFK , val@tfk.liu.se
Last updated: 03/03/2017