Skip to Main content Skip to Navigation
Conference papers

Segmentation using vector-attribute filters: Methodology and application to dermatological imaging

Abstract : Attribute-based filters can be involved in analysis and processing of images by considering attributes of various kinds (quantitative, qualitative, structural). Despite their potential usefulness, they are quite infrequently considered in the development of real applications. A cause of this underuse is probably the difficulty to determine correct parameters for non-scalar attributes in a fast and efficient fashion. This paper proposes a general definition of vector-attribute filters for grey-level images and describes some solutions to perform detection tasks using vector-attributes and parameters determined from a learning set. Based on these elements, an interactive segmentation method for dermatological application has been developed.
Complete list of metadata

https://hal.inria.fr/inria-00187232
Contributor : Benoît Naegel <>
Submitted on : Wednesday, November 14, 2007 - 9:00:27 AM
Last modification on : Thursday, July 19, 2018 - 3:34:01 PM
Long-term archiving on: : Monday, September 24, 2012 - 3:25:21 PM

File

fullpaper.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : inria-00187232, version 1

Collections

Citation

Benoît Naegel, Nicolas Passat, Nicolas Boch, Michel Kocher. Segmentation using vector-attribute filters: Methodology and application to dermatological imaging. International Symposium on Mathematical Morphology (ISMM), 2007, Rio de Janeiro, Brazil. pp.239-250. ⟨inria-00187232⟩

Share

Metrics

Record views

655

Files downloads

317