| Image Processing and Computer Vision Background; Image Processing and Computer Vision Applications; Digital Image Processing Hierarchy: Human Perception of Pictures, Digital Image Processing Hardware, Digital Image Characterisation and 2-D Linear Processing: Image Model; Amplitude Digitisation, Intensity Quantisation; Spatial Co-ordinate Digitisation: Image Sampling; Image Quality; Image Pixel Relationships; Linear Operators; 2-D Transforms, Image Enhancement: Spatial Domain Methods; Frequency Domain Methods, Image Restoration: Inverse Filtering; Wiener Filtering (Least Mean Square), Edge Detection Methods: Edge Liking and Boundary Detection; Thresholding Methods, Region-oriented Methods,Image Representation and Description: Representation Schemes; Description, Pattern Recognition: Introduction and Basic Definitions; Decision Theoretic Method for Recognition, Object recognition: Computational representations ,Models and model matching, Image Compression: Introduction; Redundancy Types; Lossless Compression; Lossy Compression; Image Compression Standards, Color processing: RGB and HSV models. Colour space, Other Image Features: Shape and Texture |
Administrative assistant: Mrs. SEEWOOGOBIN NIVEDITA DIMPLE
Telephone: 4037400
Email: aofoe-exams@uom.ac.mu |
