Toward efficient morphological shape representation

Authors:
Joseph M. Reinhardt;William E. Higgins
Affiliations:
Department of Electrical and Computer Engineering, The Pennsylvania State University, University Park, PA;Department of Electrical and Computer Engineering, The Pennsylvania State University, University Park, PA
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: image and multidimensional signal processing - Volume V
Year:
1993

Citing 3
Cited 0

Morphological Shape Decomposition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Analysis and Mathematical Morphology

Image Analysis and Mathematical Morphology
Problem-Solving Methods in Artificial Intelligence

Problem-Solving Methods in Artificial Intelligence

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Abstract

Because mathematical morphology is well-suited to capturing geometric information, morphology-based approaches have been popular for shape representation. The morphological skeleton and recently proposed morphological shape decomposition (MSD) are the primary competing morphology-based approaches for shape representation. Unfortunately, little has been done for these schemes to reduce representation redundancy and exploit tolerable representation error. We propose a shape representation scheme that is typically more computationally efficient than the morphological skeleton and MSD. Our method greatly augments the MSD. We introduce new constituent component types and incorporate a cost-based search strategy for finding an efficient representation. Further, if some representation error is tolerable, our technique can give still more efficient representations.