Abstract
A new distance mapping technique is introduced: weighted distance mapping (WDM). It is based on an adapted version of Fast Exact Euclidean Distance (FEED) transforms. It computes, after assigning a metric, a probability space for partly categorized or clustered data. This is visualized by gradual intensity changes as illustrated by the categorization of a color space based on clustered data points. In addition, edge detection of boundaries between categories can be done to find exact borders of clusters or categories. Hence, Voronoi diagrams can be created. The proposed WDMs, with or without exact edges, provide a new rich source for data analysis as well as an intuitive method of describing structure in data.
Original language | Undefined |
---|---|
Pages | 157-164 |
Number of pages | 8 |
DOIs | |
Publication status | Published - 4 Apr 2005 |
Event | IEE International Conference on Visual Information Engineering, VIE 2005 - Glasgow, Scotland, UK Duration: 4 Apr 2005 → 6 Apr 2005 |
Conference
Conference | IEE International Conference on Visual Information Engineering, VIE 2005 |
---|---|
Period | 4/04/05 → 6/04/05 |
Other | 4-6 April 2005 |
Keywords
- HMI-VRG: Virtual Reality and Graphics
- fast exact Euclidean distance
- data clusters
- data inspection
- data point distance
- data space description
- data space visualization
- EWI-21123
- probability space
- IR-79125
- Data Analysis
- FEED transform
- Edge detection
- Voronoi diagrams
- Weighted distance mapping