ENHANCING MULTISCALE FRACTAL DESCRIPTORS USING FUNCTIONAL DATA ANALYSIS


Autoria(s): FLORINDO, Joao Batista; CASTRO, Mario De; BRUNO, Odemir Martinez
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

20/10/2012

20/10/2012

2010

Resumo

This work presents a novel approach in order to increase the recognition power of Multiscale Fractal Dimension (MFD) techniques, when applied to image classification. The proposal uses Functional Data Analysis (FDA) with the aim of enhancing the MFD technique precision achieving a more representative descriptors vector, capable of recognizing and characterizing more precisely objects in an image. FDA is applied to signatures extracted by using the Bouligand-Minkowsky MFD technique in the generation of a descriptors vector from them. For the evaluation of the obtained improvement, an experiment using two datasets of objects was carried out. A dataset was used of characters shapes (26 characters of the Latin alphabet) carrying different levels of controlled noise and a dataset of fish images contours. A comparison with the use of the well-known methods of Fourier and wavelets descriptors was performed with the aim of verifying the performance of FDA method. The descriptor vectors were submitted to Linear Discriminant Analysis (LDA) classification method and we compared the correctness rate in the classification process among the descriptors methods. The results demonstrate that FDA overcomes the literature methods (Fourier and wavelets) in the processing of information extracted from the MFD signature. In this way, the proposed method can be considered as an interesting choice for pattern recognition and image classification using fractal analysis.

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

CNPq[870336/1997-5]

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

CNPq[306628/2007-4]

CNPq[484474/2007-3]

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Identificador

INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, v.20, n.11, p.3443-3460, 2010

0218-1274

http://producao.usp.br/handle/BDPI/29850

10.1142/S0218127410027805

http://dx.doi.org/10.1142/S0218127410027805

Idioma(s)

eng

Publicador

WORLD SCIENTIFIC PUBL CO PTE LTD

Relação

International Journal of Bifurcation and Chaos

Direitos

restrictedAccess

Copyright WORLD SCIENTIFIC PUBL CO PTE LTD

Palavras-Chave #Functional data analysis #multiscale fractal dimension #shape analysis #shape descriptors #fractal descriptors #DIMENSION #Mathematics, Interdisciplinary Applications #Multidisciplinary Sciences
Tipo

article

original article

publishedVersion