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ETDs @PUC-Rio
Estatística
Título: CURVATURE ESTIMATORS BASED ON PARAMETRIC CURVE FITTING
Autor: JOAO DOMINGOS GOMES DA SILVA JUNIOR
Colaborador(es): MARCOS CRAIZER - Orientador
HELIO CORTES VIEIRA LOPES - Coorientador
Catalogação: 06/ABR/2005 Língua(s): PORTUGUESE - BRAZIL
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=6223&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=6223&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.6223
Resumo:
Many applications in image processing and computer vision rely on geometric properties of curves, in particular their curvatures. Another important, but less exploited, property is the torsion for curves in space. Several methods of estimating the curvature of plane curves are known, most of them for digital curves. In this dissertation we survey these methods and propose a new method based on approximations by parabolic and cubic curves. We present a theoretical analysis of this method and also study the effect of noise. The new estimator is compared to other estimators and is seen to be very robust.
Descrição: Arquivo:   
COVER, ACKNOWLEDGEMENTS, RESUMO, ABSTRACT, SUMMARY AND LISTS PDF    
CHAPTER 1 PDF    
CHAPTER 2 PDF    
CHAPTER 3 PDF    
CHAPTER 4 PDF    
CHAPTER 5 PDF    
CHAPTER 6 PDF    
CHAPTER 7 PDF    
REFERENCES PDF