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Automatic Recognition of Leaves by Shape Detection Pre-Processing with Ica

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dc.contributor Universitat de Vic. Escola Politècnica Superior
dc.contributor Universitat de Vic. Grup de Recerca en Tecnologies Digitals
dc.contributor International Conference on Bio-inspired Systems and Signal Proceesing (2a: 2009: Porto)
dc.contributor BIOSIGNALS 2009
dc.contributor.author Solé-Casals, Jordi
dc.contributor.author Travieso, Carlos M.
dc.contributor.author Ferrer, Miguel A.
dc.contributor.author Alonso, Jesús B.
dc.contributor.author Briceno, Juan Carlos
dc.date.accessioned 2013-02-25T12:20:29Z
dc.date.available 2013-02-25T12:20:29Z
dc.date.created 2009
dc.date.issued 2009
dc.identifier.citation Solé Casals, J., Travieso, C.M., Ferrer, M.A., Alonso, J.B. & Briceno, J.C. 2009, "Automatic Recognition of Leaves by Shape Detection Pre-Processing with Ica", Biosignals 2009: Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing; 2nd International Conference on Bio-Inspired Systems and Signal Processing, eds. P. Encarnacao & A. Veloso, INSTICC-INST SYST TECHNOLOGIES INFORMATION CONTROL & COMMUNICATION, SETUBAL; AVENIDA D MANUEL L, 27A 2 ESQUERDO, SETUBAL, 2910-595, PORTUGAL, JAN 14-17, 2009, pp. 462. ca_ES
dc.identifier.isbn 78-989-8111-65-4
dc.identifier.uri http://hdl.handle.net/10854/2095
dc.description.abstract In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used to characterize the leaves. Independent Component Analysis (ICA) is then applied in order to study which is the best number of components to be considered for the classification task, implemented by means of an Artificial Neural Network (ANN). Obtained results with ICA as a pre-processing tool are satisfactory, and compared with some references our system improves the recognition success up to 80.8% depending on the number of considered independent components. ca_ES
dc.format application/pdf
dc.format.extent 6 p. ca_ES
dc.language.iso eng ca_ES
dc.publisher ca_ES
dc.publisher Springer
dc.rights (c) Springer (The original publication is available at www.springerlink.com)
dc.rights Tots els drets reservats ca_ES
dc.subject.other Percepció de les formes ca_ES
dc.title Automatic Recognition of Leaves by Shape Detection Pre-Processing with Ica ca_ES
dc.type info:eu-repo/semantics/conferenceObject ca_ES
dc.rights.accesRights info:eu-repo/semantics/openAccess ca_ES

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