Title
Knowledge-Based Interpretation of Road Maps Based on Symmetrical Skeletons
Abstract
f' scanner raw.dataS ' 5 The objective of our research reported here is to show the various processing steps on all levels of a computer vision system required to interpret and describe road maps. First, the foundation for the recognition process is laid by comput- ing two sets of distance skeletons. They are termed endo- and exo-skeleton and are symmetrical with respect to the boundary between foreground and background of a binary raster image. The skeletons are derived from a novel im- plementation of Blum's concept of the MAT in the semi- continuum which preserves important features such as Eu- clidean metric and correct topology. To eliminate noise and quantization effects a new regularization method has been devised based on which the MAT is pruned to its stable inner branches. After the removal of artefacts and further simpli- firation of the skeleton the recognition of meaningful com- plex structures is accomplished in several steps with the aid of a growing amount of domain-specific knowledge. Scene knowledge helps to verify (local) hypotheses in a larger con- text and to arrive at a consistent interpretation throughout thr scenr. The selection of the object-oriented programming paradigm proved to be very effective.
Year
Venue
Keywords
1990
MVA
object oriented programming,computer vision,knowledge base
Field
DocType
Citations 
Computer vision,Raster graphics,Pattern recognition,Programming paradigm,Computer science,Euclidean distance,Regularization (mathematics),Scanner,Artificial intelligence,Quantization (signal processing),Binary number
Conference
3
PageRank 
References 
Authors
0.59
2
2
Name
Order
Citations
PageRank
Markus Ilg1103.68
robert l ogniewicz2185.17