Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/75434
Title: Distance maps from unthresholded magnitudes
Authors: Antón Canalís,Luis 
HernÁndez-Tejera, Mario 
Sanchez-Nielsen, Elena
UNESCO Clasification: 1203 Ciencia de los ordenadores
120304 Inteligencia artificial
220990 Tratamiento digital. Imágenes
Keywords: Algorithm
Distance transform
Thresholding
Pseudodistances
Issue Date: 2011
Journal: Lecture Notes in Computer Science 
Conference: 5th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA) 
Abstract: A straightforward algorithm that computes distance maps from unthresholded magnitude values is presented, suitable for still images and video sequences. While results on binary images are similar to classic Euclidean Distance Transforms, the proposed approach does not require a binarization step. Thus, no thresholds are needed and no information is lost in intermediate classification stages. Experiments include the evaluation of segmented images using the watershed algorithm and the measurement of pixel value stability in video sequences.
URI: http://hdl.handle.net/10553/75434
ISBN: 978-3-642-21256-7
ISSN: 0302-9743
DOI: 10.1007/978-3-642-21257-4_12
Source: Vitrià J., Sanches J.M., Hernández M. (eds) Pattern Recognition and Image Analysis. IbPRIA 2011. Lecture Notes in Computer Science, [ISSN 0302-9743], vol 6669, p. 92-99. Springer, Berlin, Heidelberg.
Appears in Collections:Actas de congresos
Thumbnail
PDF
Adobe PDF (227,99 kB)
Show full item record

Page view(s)

92
checked on Jan 27, 2024

Download(s)

165
checked on Jan 27, 2024

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.