Conference proceeding
The vectorial Minimum Barrier Distance
Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), pp.792-795
International Conference on Pattern Recognition (ICPR), 21 (Tsukuba, Japan, 11/11/2012 - 11/15/2012)
11/2012
Abstract
We introduce the vectorial Minimum Barrier Distance (MBD), a method for computing a gray-weighted distance transform while also incorporating information from vectorial data. Compared to other similar tools that use vectorial data, the proposed method requires no training and does not assume having only one background class. We describe a region-growing algorithm for computing the vectorial MBD efficiently. The method is evaluated on two types of multichannel images: color images and textural features. Different path-cost functions for calculating the multidimensional path-cost distance are also compared. The results show that by combining multi-channel images into vectorial information the performance of the vectorial MBD segmentation is improved compared to when one channel is used. This implies that the method can be a good way of incorporating multichannel information in interactive segmentation.
Details
- Title: Subtitle
- The vectorial Minimum Barrier Distance
- Creators
- A Karsnas - Uppsala UniversityR Strand - Uppsala UniversityP. K Saha - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), pp.792-795
- Conference
- International Conference on Pattern Recognition (ICPR), 21 (Tsukuba, Japan, 11/11/2012 - 11/15/2012)
- Publisher
- IEEE
- ISSN
- 1051-4651
- eISSN
- 1051-4651
- Language
- English
- Date published
- 11/2012
- Academic Unit
- Electrical and Computer Engineering; Radiology
- Record Identifier
- 9984197907202771
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