Image Processing
In cooperation with Alexandra Bodzás
01 – Introduction to Vision
Introduction to the vision library of NI – Labview.
http://www.ni.com/labview/vision/
02 – Image thresholding
03 – Convolution
Convolution, and convolution theorem on the image.
04 – Discrete Fourier transform
Application of Fourier transform in discrete form on the image, together with inverse transformation (DFT / IDFT)
05 – Filtration in frequency domain
Filtration based on frequency domains of image.
06 – Histogram equalization
07 – Geometric transformation
Scale, rotation, translation. Application of the affine transfrmation.
08 – Edge detection
Detection of the edges in the image.
09 – Object labeling
10 – Features computation
Computation of features based on the objects in original image
11 – Classification with etalons
Classification of the image based on the goldesn standard (etalon).
12 – K-measn classification
Self learning classification of the K-means