Data Structures For Image Analysis
Levels of image data representation
Traditional image data structures
Hierarchical data structures
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Levels Of Image Data Representation
Computer visual perception Determine the relation b/w input image and
models of real world Iconic image – original image data Segmented image – ROI in groups Geometric representation – higher level of
knowledge, such as shapes, etc. Relational model – relationships among
higher level abstraction
Image-based
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Traditional Image Data Structures
Matrices or N-dimensional arrays Chains – describing object borders Topological data structures – graphs,
maps Relational structures
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Matrices
Low-level image data representation Depict spatial relations –
neighborhood, etc. Grid – rectangular, hexagonal grids Pixel coordinates Brightness – intensity, gray level, color
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Matrices (II)
Binary image (0/1), multi-spectral image (gray-scaled, color), hierarchical image data structure (LOD: level of detail, varied resolutions)
Global information Histogram – probabilistic density of a
phenomenon Co-occurrence matrix – measures in
terms of brightness
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Co-occurrence Matrix
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Chains
Chains are used for the description of object borders in computer vision
Chains are composed of symbols in sequence – useful for syntactic pattern recognition
Chain codes (aks: Freeman codes) Run length coding
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Chain Codes
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Run Length Coding
((11144)(214)(52355))
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Topological Data Structures
Describe image as set of elements and their relations
Graph: G=(V,E); V denotes the set of nodes and E represents the set of edges Evaluated graph (or weighted graph) Region adjacency graph
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Region Adjacency Graph (RAG)
NodesNodes represent region; edgesedges or arcsarcs represent connectivity Nodes of degree 1 are cavitiescavities or holesholes Edges can be used to describe relations RAG can be created from a quadtree representation or from tracing
the borders of all regions in the region mapregion map (a result of segmentation)
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Region Merging Phenomenon
Region merging may create holes
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Relational structure
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Pyramids
M-pyramid (matrix-pyramid) – a sequence of images in reducing resolutions of the original image Disadvantage: Only one image in certain
resolution is available at a time T-pyramid (tree-pyramid) – use the
tree structures to represent M-pyramid
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T-Pyramids
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Quadtree
Similar to pyramid hierarchical representations. T-pyramids are balanced; the quadtree representation is not.