Per citar aquest document: http://ddd.uab.cat/record/123320
Swarm-based Descriptor Combination and its Application for Image Classification
Mansano, Alex Fernandes (Sâo Paulo State University. Department of Computing)
Matsuoka, Jessica Akemi (Sâo Paulo State University. Department of Computing)
Abiuzzi, Nikolas Mota (Sâo Paulo State University. Department of Computing)
Afonso, Luis Claudio Sugi (Sâo Paulo State University. Department of Computing)
Papa, Joao Paulo (São Paulo State University. Department of Computing)
Faria, Fábio A. (University of Campinas. Institute of Computing (Brasil))
Torres, Ricardo Silva (University of Campinas. Institute of Computing (Brasil))
Falcao, Alexandre Xavier (University of Campinas. Institute of Computing (Brasil))

Data: 2014
Resum: In this paper, we deal with the descriptor combination problem in image classification tasks. This problem refers to the definition of an appropriate combination of image content descriptors that characterize different visual properties, such as color, shape and texture. In this paper, we propose to model the descriptor combination as a swarm-based optimization problem, which finds out the set of parameters that maximizes the classification accuracy of the Optimum-Path Forest (OPF) classifier. In our model, a descriptor is seen as a pair composed of a feature extraction algorithm and a suitable distance function. Our strategy here is to combine distance scores defined by different descriptors, as well as to employ them to weight OPF edges, which connect samples in the feature space. An extensive evaluation of several swarm-based optimization techniques was performed. Experimental results have demonstrated the robustness of the proposed combination approach.
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Llengua: Anglès.
Document: article ; recerca ; publishedVersion
Publicat a: ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 13 Núm. 3 (2014) , p. 13-27 (Regular Issue) , ISSN 1577-5097

Adreça alternativa: http://www.raco.cat/index.php/ELCVIA/article/view/284233
DOI: 10.5565/rev/elcvia.566


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