Publicação:
ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

dc.contributor.authorLulio, Luciano C.
dc.contributor.authorTronco, Mario L. [UNESP]
dc.contributor.authorPorto, Arthur J. V.
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:24:50Z
dc.date.available2014-05-27T11:24:50Z
dc.date.issued2010-11-29
dc.description.abstractThe main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.en
dc.description.affiliationMechanical Engineering Department Engineering School of Sao Carlos University of Sao Paulo, CEP 13566-590
dc.description.affiliationDepartment of Computer Science and Statistics State University of Sao Paulo, CEP 15054-000
dc.description.affiliationUnespDepartment of Computer Science and Statistics – UNESP, IBILCE
dc.format.extent1771-1776
dc.identifierhttp://dx.doi.org/10.1109/ICMA.2010.5588694
dc.identifier.citation2010 IEEE International Conference on Mechatronics and Automation, ICMA 2010, p. 1771-1776.
dc.identifier.doi10.1109/ICMA.2010.5588694
dc.identifier.scopus2-s2.0-78649235689
dc.identifier.urihttp://hdl.handle.net/11449/71974
dc.language.isoeng
dc.relation.ispartof2010 IEEE International Conference on Mechatronics and Automation, ICMA 2010
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectArtificial neural networks
dc.subjectComputer vision
dc.subjectImage recognition and processing
dc.subjectMobile robots
dc.subjectApplication area
dc.subjectArtificial Neural Network
dc.subjectComputational platforms
dc.subjectHSV space
dc.subjectMobile Robot Navigation
dc.subjectMulti layer perceptron
dc.subjectNavigation problem
dc.subjectOmnidirectional vision system
dc.subjectRecognition methods
dc.subjectSegmentation techniques
dc.subjectSegmented images
dc.subjectSIMULINK environment
dc.subjectStatistical images
dc.subjectBackpropagation algorithms
dc.subjectImage recognition
dc.subjectImage segmentation
dc.subjectMechatronics
dc.subjectNavigation
dc.subjectNeural networks
dc.subjectWireless networks
dc.titleANN statistical image recognition method for computer vision in agricultural mobile robot navigationen
dc.typeTrabalho apresentado em evento
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dspace.entity.typePublication
unesp.campusUniversidade Estadual Paulista (Unesp), Instituto de Biociências Letras e Ciências Exatas, São José do Rio Pretopt
unesp.departmentCiências da Computação e Estatística - IBILCEpt

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