Symbolic Construction of a 2D Scale-Space Image.
Abstract
The shapes of naturally occurring objects characteristically involve spatial events occurring at many scales. It is important to make explicit the multiscale structure of a shape object in order to effectively perform shape recognition or to engage in other forms of reasoning about shape. Currently available techniques for multiscale shape analysis include image blurring and contour smoothing; each of these techniques involves uniform application of a smoothing operator to the entire image array or contour. This paper offers a new, symbolic, approach to constructing a primitive shape description across scales for 2d binary (silhouette) shape images. Under this approach, grouping operations are performed over collections of tokens residing on a Scale-Space Blackboard. Two types of grouping operations are identified that, respectively: (1) aggregate edge primitives at one scale into edge primitives at a coarser scale, and (2) group edge primitives into partial-region assertions, including curved-contours, primitive-corners, and bars. Algorithms to perform these computations are presented. Keywords: Scale space; Symbolic token grouping; Shape representation; Scale space blackboard; Image processing; Feature extraction; Machine vision. (jhd)
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 01, 1988
- Accession Number
- ADA195926
Entities
People
- Eric Saund
Organizations
- Massachusetts Institute of Technology