Detalhes bibliográficos
Ano de defesa: |
2014 |
Autor(a) principal: |
Imada, Renata Nagima [UNESP] |
Orientador(a): |
Não Informado pela instituição |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Dissertação
|
Tipo de acesso: |
Acesso aberto |
Idioma: |
por |
Instituição de defesa: |
Universidade Estadual Paulista (Unesp)
|
Programa de Pós-Graduação: |
Não Informado pela instituição
|
Departamento: |
Não Informado pela instituição
|
País: |
Não Informado pela instituição
|
Palavras-chave em Português: |
|
Link de acesso: |
http://hdl.handle.net/11449/122215
|
Resumo: |
In this research, a method of recognition of building roof contours in high-resolution digital images which classi es them with respect to their form was studied. The method is based on Zernike moments, which are based on orthogonal Zernike polynomials and it creates a feature vector for each image region. The image segmentation has to be made rst to de ne di erent regions for its objects. This method for shape analysis is based on the object area of interest and the moments has the characteristic of being invariant under geometric transformations of rotation, translation and scaling, this makes it attractive to the proposed image analysis problem. Thus, a database containing sketches (or models) of possible appearances of building roof contours in a given scene was created, so a Zernike feature vector was also associated for these sketches. Therefore, the Euclidean distance between this vector and the feature vector calculated from a segmented region in the image lets say if the given region corresponds to a building contour or other object. The capacity of the proposed method in discriminating di erent building shapes and also in discriminating building shapes from non-building shapes was evaluated experimentally and it showed positive results. |