@Inbook{MathieuNicolasDelalandre2010,
author="Mathieu Nicolas Delalandre
and Jean-Yves Ramel
and Ernest Valveny
and Muhammad Muzzamil Luqman",
chapter="A Performance Characterization Algorithm for Symbol Localization",
title="Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers",
year="2010",
publisher="Springer Berlin Heidelberg",
volume="6020",
pages="260--271",
abstract="In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more {\textquoteleft}{\textquoteleft}reliable{\textquoteright}{\textquoteright} and {\textquoteleft}{\textquoteleft}open{\textquoteright}{\textquoteright} solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols).",
optnote="DAG",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2406), last updated on Wed, 16 Jan 2019 10:28:24 +0100",
isbn="978-3-642-13727-3",
issn="0302-9743",
doi="10.1007/978-3-642-13728-0_24"
}