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Optical engineering and machine vision are collective terms for using optical signals to solve tasks of information retrieval for technical and other application. They comprise the propagation of light in optical systems, the acquisition of image signals using optical imaging and cameras, the processing of the recorded image signals using (digital) image processing and the evaluation of the image data to obtain useful information from the recorded images.

The module teaches the basics, procedures and exemplary applications of optical engineering and image processing.

The module include in detail:

• Optical Imaging
  • Imaging with a pinhole camera, central projection
  • Imaging using a (single) lens
• Color
  • Photometry
  • Color perception and color spaces
  • Filters
• Sensors for Image Acquisition
  • CCD, CMOS sensors
  • Color sensors and color cameras
  • Quality criteria for image sensors
• Methods of Image Acquisition
  • Measuring optical properties
  • 3D shape capturing
• Image Signals
  • Mathematical model of image signals
  • Systems theory
  • Two-dimensional Fourier transform
  • Noise of digital imaging sensors (EMVA 1288)
• Preprocessing and Image Enhancement
  • Simple image enhancement methods
  • Reduction of systematic errors
  • Attenuation of random disturbances
• Segmentation
  • Region-based segmentation
  • Edge-oriented methods
• Morphological Image Processing
  • Binary morphology
  • Gray-scale morphology
• Texture analysis
  • Types of textures
  • Model-based texture analysis
  • Feature-based texture analysis
• Detection
  • Detection of known objects by linear filters
  • Detection of unknown objects (defects)
  • Detection of straight lines (Radon and Hough transform)

Further information

For further information, please contact Daniel Leyer.