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Lecture: Introduction

Overview




Goals

  • hands-on image manipulation, cameras, etc.
  • common 2D image processing operations
  • computer vision techniques (segmentation, 3D, ...)
  • machine learning applied to images
  • standard tools: Python, NumPy (Matlab), OpenCV
Additional
  • high performance C/C++ programming
  • GPU computing
  • mobile imaging

Functions in the Gimp

  • linear signal processing
  • color space transformations
  • geometric transformations
  • thresholding
  • mathematical morphology
  • synthesis

Functions in ImageJ

  • FFT
  • edge detection
  • thresholding
  • mathematical morphology
  • counting and detection

Exercise

  • Familiarize yourself with Python.
  • Familiarize yourself with the Gimp.
  • Use Python (Python, NumPy, SciPy, Matplotlib) on the departmental machines or...
  • For development environments, you have several choices:
    • ipython interactive shell ("apt-get install ipython" on Ubuntu)
    • SageMath (download from sagemath.org for all platforms)
    • reinteract ("apt-get install reinteract" on Ubuntu)
    • DrPython ("apt-get install drpython" on Ubuntu)
    • Eclipse PyDev ("apt-get install eclipse-pydev" on Ubuntu)

Resources

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Nibal Nayef,
Apr 20, 2011, 11:02 PM
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