Iconic indexing by 2-D strings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Principles of pictorial information systems design
Principles of pictorial information systems design
Similarity retrieval of iconic image database
Pattern Recognition
2D C-string: a new spatial knowledge representation for image database systems
Pattern Recognition
Picture algebra for spatial reasoning of iconic images represented in 2D C-string
Pattern Recognition Letters
Split-and-merge image segmentation based on localized feature analysis and statistical tests
CVGIP: Graphical Models and Image Processing
Computer representation of planar regions by their skeletons
Communications of the ACM
Image Information Systems: Where Do We Go From Here?
IEEE Transactions on Knowledge and Data Engineering
An Intelligent Image Database System
IEEE Transactions on Software Engineering
Extended Symbolic Projections as a Knowledge Structure for Spatial Reasoning
Proceedings of the 4th International Conference on Pattern Recognition
An Application of Relaxation Labeling to Line and Curve Enhancement
IEEE Transactions on Computers
An accommodating edge follower
IJCAI'71 Proceedings of the 2nd international joint conference on Artificial intelligence
Virtual Images for Similarity Retrieval in Image Databases
IEEE Transactions on Knowledge and Data Engineering
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Spatial reasoning and similarity retrieval are two important functions of any image information system. Good spatial knowledge representation for images is necessary to adequately support these two functions. In this paper, we propose a new spatial knowledge representation, called the SK-set based on morphological skeleton theories. Spatial reasoning algorithms which achieve more accurate results by directly analysing skeletons are described. SK-set facilitates browsing and progressive visualization. We also define four new types of similarity measures and propose a similarity retrieval algorithm for performing image retrieval. Moreover, using SK-set as a spatial knowledge representation will reduce the storage space required by an image database significantly.