@Inbook{LluisPeredelasHeras2014,
author="Lluis Pere de las Heras
and David Fernandez
and Alicia Fornes
and Ernest Valveny
and Gemma Sanchez
and Josep Llados",
chapter="Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans",
title="Graphics Recognition. Current Trends and Challenges",
year="2014",
publisher="Springer Berlin Heidelberg",
volume="8746",
pages="135--146",
optkeywords="Graphics recognition",
optkeywords="Graphics retrieval",
optkeywords="Image classification",
abstract="This paper proposes a runlength histogram signature as a perceptual descriptor of architectural plans in a retrieval scenario. The style of an architectural drawing is characterized by the perception of lines, shapes and texture. Such visual stimuli are the basis for defining semantic concepts as space properties, symmetry, density, etc. We propose runlength histograms extracted in vertical, horizontal and diagonal directions as a characterization of line and space properties in floorplans, so it can be roughly associated to a description of walls and room structure. A retrieval application illustrates the performance of the proposed approach, where given a plan as a query, similar ones are obtained from a database. A ground truth based on human observation has been constructed to validate the hypothesis. Additional retrieval results on sketched building{\textquoteright}s facades are reported qualitatively in this paper. Its good description and its adaptability to two different sketch drawings despite its simplicity shows the interest of the proposed approach and opens a challenging research line in graphics recognition.",
optnote="DAG; ADAS; 600.045; 600.056; 600.061; 600.076; 600.077",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2536), last updated on Wed, 16 Dec 2015 09:42:30 +0100",
isbn="978-3-662-44853-3",
issn="0302-9743",
doi="10.1007/978-3-662-44854-0_11"
}