Run-Length Matrices For Texture Analysis
University of Pennsylvania
| Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/1374 |
Published in The Insight Journal - 2008 January - June.
Submitted by Nick Tustison on 05-27-2008.
Texture analysis provides quantitative information describing properties in images such as coarseness and smoothness. Two common quantification schemes are based on co-occurence matrices and run-length matrices. Although the co-occurence measures are readily available in the Insight Toolkit, no such set of classes exists for run-length measures. This submission is meant to remedy this deficiency by providing a set of classes which are modeled after the ITK co-occurence measures classes.
Code
Reviews
Great Contribution
by Katie D'aco on 2010-02-24 13:01:00 for revision #4 Statistics
| Global rating: | |
| Review rating: | |
| Code rating: | |
| Views: | 3128 |
| Downloads: | 932 |
Send a message to the author
Information
| Paper Id: | 231 |
| Categories: | Classification, Mathematics |
| Keywords: | run-length, texture, |
| Toolkit: | ITK |
| Revision: | 5 (07-14-2010) |
| See revision: | |
| Status: | Open for public review |
| View license
Loading license...
| |
Data
| Full download: | .zip |
| Paper: | view, .pdf |
| Source code : | Download |
Share
Associated Publications
| Stochastic Fractal Dimension Image | ||






