'Computer Vision is the science and engineering of creating hardware and software which can analyse and understand images and video. Below is a list of related topics.
How Images Are Interpreted[]
- Signal approach
- Matrix Approach
- Hyperplane
Basic Image Operation[]
- Rotation, scaling, translation
- quantization
- Edge detection
- boolean operations
- component analysis
- histogram processing
- scale space representation
- Pixel neighbourhood
Frequency Domain[]
- introduction to frequency domain
- PSD
- FFT
- zero padding
- windowing (Hanning, Blackman, raised cosine)
- circular convoultion
- inverse filtering
- weiner filtering
Morphology[]
- dilation, erosion
- opening and closing
- grayscale
- idempotency
- skelatonization
Fractals[]
- Introduction
- Fractal Compression
Compression[]
Statistical Filtering[]
- Median Filter
- Anistropic Diffusion
- Symmetric nearest neighbor mean filtering
Non linear filtering[]
- Gaussian filtering
- Salt and pepper noise
Feature Extraction[]
- Gabor filtering
- Texture analysis
Optical flow[]
- Optical flow
Stereo vision[]
- Machine vision
- Stereo vision
Tracking[]
Motion estimation[]
Object recognition[]
- Probability overview (bayes, dempster shaefer, etc)
- Feature generation
- Classifiers and Discriminants
- High level analysis.
Color[]
- Colorspaces
- Extraction, constancy
Implementation[]
- Languages
- Libraries
- Optimization techniques
- Specialized hardware
Cameras[]
- Types: CCD, cmos
- Calibration
- Color constancy