Binary tree classifier and context classifier
| dc.contributor.author | Joo, Hyonam | en |
| dc.contributor.department | Electrical Engineering | en |
| dc.date.accessioned | 2015-06-23T19:08:27Z | en |
| dc.date.available | 2015-06-23T19:08:27Z | en |
| dc.date.issued | 1985 | en |
| dc.description.abstract | Two methods of designing a point classifier are discussed in this paper, one is a binary decision tree classifier based on the Fisher's linear discriminant function as a decision rule at each nonterminal node, and the other is a contextual classifier which gives each pixel the highest probability label given some substantially sized context including the pixel. Experiments were performed both on a simulated image and real images to illustrate the improvement of the classification accuracy over the conventional single-stage Bayes classifier under Gaussian distribution assumption. | en |
| dc.description.degree | Master of Science | en |
| dc.format.extent | vi, 93 leaves | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.uri | http://hdl.handle.net/10919/53076 | en |
| dc.language.iso | en_US | en |
| dc.publisher | Virginia Polytechnic Institute and State University | en |
| dc.relation.isformatof | OCLC# 12655126 | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject.lcc | LD5655.V855 1985.J67 | en |
| dc.subject.lcsh | Pattern recognition systems | en |
| dc.subject.lcsh | Image processing -- Experiments | en |
| dc.title | Binary tree classifier and context classifier | en |
| dc.type | Thesis | en |
| dc.type.dcmitype | Text | en |
| thesis.degree.discipline | Electrical Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | masters | en |
| thesis.degree.name | Master of Science | en |
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