| Publication Type |
thesis |
| School or College |
College of Engineering |
| Department |
Computing |
| Author |
Linton, Trevor Forbes |
| Title |
Semantic feature analysis in raster maps |
| Date |
2009-06-15 |
| Description |
The extraction of semantic features from images of geographic maps is a difficult and interesting problem. Such features may be robustly segmented through the use of Gestalt principles such as similarity and continuity as realized through the use of tensor voting methods and color histogram analysis, respectively. A framework is developed implementing these Gestalt principles through various algorithms. Linear feature segmentation and intersection detection methods are given, and their performance is demonstrated on a set of real and synthetic map images. |
| Type |
Text |
| Publisher |
University of Utah |
| Subject |
Gestalt principles |
| Dissertation Institution |
University of Utah |
| Dissertation Name |
MS |
| Language |
eng |
| Relation is Version of |
Digital reproduction of "Semantic feature analysis in raster maps" J. Willard Marriott Library Special Collections GA2.5 2009 .L56 |
| Rights Management |
© Trevor Forbes Linton |
| Format Medium |
application/pdf |
| Format Extent |
83,411 bytes |
| Identifier |
us-etd2,119194 |
| Source |
Original: University of Utah J. Willard Marriott Library Special Collections |
| Conversion Specifications |
Original scanned on Epson GT-30000 as 400 dpi to pdf using ABBYY FineReader 9.0 Professional Edition |
| ARK |
ark:/87278/s6mc9dns |
| Setname |
ir_etd |
| ID |
193897 |
| Reference URL |
https://collections.lib.utah.edu/ark:/87278/s6mc9dns |
