@InProceedings{Taschwer2015,
author = {Taschwer, Mario and Marques, Oge},
booktitle = {{CLEF} 2015 Working Notes},
title = {AAUITEC at ImageCLEF 2015: Compound Figure Separation},
year = {2015},
address = {Padova, Italy},
editor = {Capellato, Linda and Ferro, Nicola and Jones, Gareth and Juan, Eric},
month = {sep},
pages = {9},
publisher = {CLEF Association},
series = {CEUR Workshop Proceedings, ISSN 1613-0073},
volume = {1391},
abstract = {Our approach to automatically separating compound figures appearing in biomedical articles is split into two image processing algorithms: one is based on detecting separator edges, and the other tries to identify background bands separating sub gures. Only one algorithm is applied to a given image, according to the prediction of a binary classifier trained to distinguish graphical illustrations from other images in biomedical articles. Our submission to the ImageCLEF 2015 compound figure separation task achieved an accuracy of 49% on the provided test set of about 3400 compound images. This stays clearly behind the best submission of other participants (85% accuracy), but is by an order of magnitude faster than other approaches reported in the literature.},
language = {EN},
location = {Toulouse, France},
pdf = {https://www.itec.aau.at/bib/files/aauitec-fig-separation.pdf},
slides = {https://www.itec.aau.at/bib/files/poster-aauitec-fig-separation.pdf},
talkdate = {2015.09.09},
talktype = {poster},
url = {
http://ceur-ws.org/Vol-1391/25-CR.pdf}
}