Journal article
Implementation, Interpretation, and Analysis of a Suboptimal Boundary Finding Algorithm
IEEE transactions on pattern analysis and machine intelligence, v PAMI-4(2), pp 167-182
01 Mar 1982
PMID: 21869023
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper presents a suboptimal boundary estimation algorithm for noisy images which is based upon an optimal maximum likelihood problem formulation. Both the maximum likelihood formulation and the resulting algorithm are described in detail, and computational results are given. In addition, the potential power of the likelihood formulation is demonstrated through the presentation of three simple but insightful analyses of algorithm performance. These analyses are based on a technique we have developed for comparing the accuracies of different boundary finding algorithms. This technique also helps in understanding the interplay of object shape and data models in the relative performances of boundary finders. Some of the algorithm design considerations resulting from the use of our analysis technique are new and, at first, surprising. Our technique appears to be the only one developed for comparing the accuracies of different boundary finding algorithms.
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Details
- Title
- Implementation, Interpretation, and Analysis of a Suboptimal Boundary Finding Algorithm
- Creators
- Howard Elliott - Colorado State UniversityDavid B. Cooper - Brown UniversityFernand S. Cohen - Brown UniversityPeter F. Symosek - Brown University
- Publication Details
- IEEE transactions on pattern analysis and machine intelligence, v PAMI-4(2), pp 167-182
- Publisher
- IEEE
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:A1982NE95700013
- Scopus ID
- 2-s2.0-0019910812
- Other Identifier
- 991020532001404721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic