@inproceedings{Pinheiro-ICIAR2014,
  IS = { zkontrolovano 08 Jan 2015 },
UPDATE   = { 2014-12-19 },
author      = { Am{\' a}vel Pinheiro, Miguel and Kybic, Jan },
affiliation = { CMP, Dept. of Cybernetics, Faculty of Elec. Eng., Czech Technical Universi
ty in Prague },
title       = { {Path Descriptors for Geometric Graph Matching and Registration} },
authorship  = { 50-50 },
booktitle   = { International Conference on Image Analysis and Recognition },
pages       = { 3--11 },
book_pages  = { 518 },
editor      = { Campilho, Aur{\' e}lio and Kamel, Mohamed },
isbn        = { 978-3-319-11757-7 },
publisher   = { Springer },
address     = { Berlin, DE },
series = {LNCS},
volume      = { 8814 },
month       = { October },
year        = { 2014 },
day         = { 22--24 },
venue       = { Vilamoura, Portugal },
Project     = { SGS12/190/OHK3/3T/13, GACR P202/11/0111, SFRH/BD/77134/2011 },
keywords    = { geometric graph matching, image registration },
annote      = {Graph and tree-like structures such as blood vessels and neuronal networks 
are abundant in medical imaging. We present a method to calculate path descriptors in geometrical graphs, so that the similarity between paths in the graphs can be determined effic
iently. We show experimentally that our descriptors are more discriminative than existing 
alternatives. We further describe how to match two geometric graphs using our path descrip
tors. Our main application is registering images for which standard techniques are ineffic
ient, because the appearance of the images is too different, or there is not enough textur
e and no uniquely identifiable keypoints to be found. We show that our approach can regist
er these images with better accuracy than previous methods.},
Psurl       = {[Pinheiro-ICIAR2014.pdf]},
Url         = {ftp://cmp.felk.cvut.cz/pub/cmp/articles/amavemig/Pinheiro-ICIAR2014.pdf},
}