Image Processing

In cooperation with Alexandra Bodzás

01 – Introduction to Vision

Introduction to the vision library of NI – Labview.

02 – Image thresholding

Simple thresholding processed on image.


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03 – Convolution

Convolution, and convolution theorem on the image.

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04 – Discrete Fourier transform

Application of Fourier transform in discrete form on the image, together with inverse transformation (DFT / IDFT)


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05 – Filtration in frequency domain

Filtration based on frequency domains of image.

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06 – Histogram equalization

Equalization of the image based on the histogram of the image.


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07 – Geometric transformation

Scale, rotation, translation. Application of the affine transfrmation.

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08 – Edge detection

Detection of the edges in the image.

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09 – Object labeling

Labeling of the objects in the image


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10 – Features computation

Computation of features based on the objects in original image

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11 – Classification with etalons

Classification of the image based on the goldesn standard (etalon).

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12 – K-measn classification

Self learning classification of the K-means

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