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Image processing is a method tobring out some meaningful information and ro perform certain opertaions on an image to get more enhanced image. This type of image processing in which image is an input and the enhaced image with some new features and characteristics is an output is signal processing. Image processing includes the basic steps which are listed below:-
- Importing the image via image acquisition tools;
- Analysing and manipulating the image;
- Output in which result can be altered image or report that is based on image analysis.
There are basically two types of image processing i.e. analogue and digital image processing. Analogue image processing can be used for the hard copies like printouts and photographs. Digital image processing techniques help in manipulation of the digital images by using computers. There are three general phases from which every digital processing has to go using digital techniques- pre-processing, enhancement, and display, information extraction.
The process of image processing mainly includes the following :-
- image enhancement,
- encoding, and
Image processing also includes the important related fields such as Signal processing Image processing Computer/Machine/Robot vision Biological vision Artificial intelligence Machine learning and Pattern recognition.
COMP3072 - Image Processing
- digital image,film,digital camera
- Data types,2d representation of digital images
- grey level digital images,Discrete sampling model,Quantisation
- Noise processes,Image attributes,Segmentation
- Thresholding ,thresholding algorithms
- Performance evaluation,ROC analysis,Connected components labelling
- Region growing ,region adjacency graph ,RAG,Split
- merge algorithms,Image transformations
- Grey level transformations,Histogram equalization
- Geometric transformations,Affine transformations
- Polynomial warps,Morphological operation,Erode,dilate
- operators on BINARY images,Open transforms,close transforms
- thinning transforms,Medial axis transform,grey level morphology
- Image filtering,Fourier descriptors,Linear,non linear filtering operations
- Image convolutions,Separable convolutions,Sub sampling ,interpolation as convolution operations
- Feature characterisation,Calculation of region properties
- Moment features,Boundary coding line descriptors
- boundary coding ,moments,Image search ,multi resolution algorithms
- EEdge ,corner detection,Edge enhancement by differentiation
- Effect of noise,edge detection ,Canny implementation
- Edge detector performance evaluation,Image structure tensor
- Relationship to image auto correlation,Characterisation
- Harris corner detector,Colour images,colour in digital images
- Colour metrics,Pixel wise operations,Colour invariants
- Finlayson colour constancy algorithm,TeTemplate matching
- advanced topics,Similarity ,dissimilarity matching metrics,L2 metric
- relationship to cross correlation,2D object detection,recognition,location
- Sub pixel accuracy,performance evaluation