Spatio-structural Symbol Description with Statistical Feature Add-on

Abstract : In this paper, we present a method for symbol description based on both spatio-structural and statistical features computed on elementary visual parts, called 'vocabulary'. This extracted vocabulary is grouped by type (e.g., circle, corner ) and serves as a basis for an attributed relational graph where spatial relational descriptors formalise the links between the vertices, formed by these types, labelled with global shape descriptors. The obtained attributed relational graph description has interesting properties that allows it to be used efficiently for recognising structure and by comparing its attribute signatures. The method is experimentally validated in the context of electrical symbol recognition from wiring diagrams.
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Chapitre d'ouvrage
Young-Bin Kwon, Jean-Marc Ogier. Graphics Recognition. New Trends and Challenges, 7423, Springer-Verlag Berlin Heidelberg, pp.228-237, 2013, Lecture Notes in Computer Science, 978-3-642-36823-3 (Print) 978-3-642-36824-0 (Online). 〈10.1007/978-3-642-36824-0_22〉
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https://hal.inria.fr/hal-00789268
Contributeur : Santosh K.C. <>
Soumis le : dimanche 17 février 2013 - 20:05:08
Dernière modification le : jeudi 11 janvier 2018 - 06:25:25
Document(s) archivé(s) le : samedi 18 mai 2013 - 04:04:03

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Santosh K.C., Bart Lamiroy, Laurent Wendling. Spatio-structural Symbol Description with Statistical Feature Add-on. Young-Bin Kwon, Jean-Marc Ogier. Graphics Recognition. New Trends and Challenges, 7423, Springer-Verlag Berlin Heidelberg, pp.228-237, 2013, Lecture Notes in Computer Science, 978-3-642-36823-3 (Print) 978-3-642-36824-0 (Online). 〈10.1007/978-3-642-36824-0_22〉. 〈hal-00789268〉

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