'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.

Contents 1 How Images Are Interpreted 2 Basic Image Operation 3 Frequency Domain 4 Morphology 5 Fractals 6 Compression 7 Statistical Filtering 8 Non linear filtering 9 Feature Extraction 10 Optical flow 11 Stereo vision 12 Tracking 13 Motion estimation 14 Object recognition 15 Color 16 Implementation 17 Cameras

How Images Are InterpretedEdit

• Signal approach
• Matrix Approach
• Hyperplane

Basic Image OperationEdit

• Rotation, scaling, translation
• quantization
• Edge detection
• boolean operations
• component analysis
• histogram processing
• scale space representation
• Pixel neighbourhood

Frequency DomainEdit

• introduction to frequency domain
• PSD
• FFT
• zero padding
• windowing (Hanning, Blackman, raised cosine)
• circular convoultion
• inverse filtering
• weiner filtering

MorphologyEdit

• dilation, erosion
• opening and closing
• grayscale
• idempotency
• skelatonization

FractalsEdit

• Introduction
• Fractal Compression

CompressionEdit

• Introduction
• Huffman
• Artimatic
• jpeg
• png
• Mu-law
• Symbol Based

Statistical FilteringEdit

• Median Filter
• Anistropic Diffusion
• Symmetric nearest neighbor mean filtering

Non linear filteringEdit

• Gaussian filtering
• Salt and pepper noise

Feature ExtractionEdit

• Gabor filtering
• Texture analysis

Optical flowEdit

• Optical flow

Stereo visionEdit

• Machine vision
• Stereo vision

TrackingEdit

• Tracking

Motion estimationEdit

• Motion estimation
• Motion segmentation

Object recognitionEdit

• Probability overview (bayes, dempster shaefer, etc)
• Feature generation
• Classifiers and Discriminants
• High level analysis.

ColorEdit

• Colorspaces
• Extraction, constancy

ImplementationEdit

• Languages
• Libraries
• Optimization techniques
• Specialized hardware

CamerasEdit

• Types: CCD, cmos
• Calibration
• Color constancy