Detecção de bordas em imagens digitais através de um processo de difusão anisotrópica não linear


Autoria(s): Dos Santos Galvanin, Edinéia Aparecida; Silva, Erivaldo Antonio da
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

27/05/2014

27/05/2014

01/12/2006

Resumo

The edges detection model by a non-linear anisotropic diffusion, consists in a mathematical model of smoothing based in Partial Differential Equation (PDE), alternative to the conventional low-pass filters. The smoothing model consists in a selective process, where homogeneous areas of the image are smoothed intensely in agreement with the temporal evolution applied to the model. The level of smoothing is related with the amount of undesired information contained in the image, i.e., the model is directly related with the optimal level of smoothing, eliminating the undesired information and keeping selectively the interest features for Cartography area. The model is primordial for cartographic applications, its function is to realize the image preprocessing without losing edges and other important details on the image, mainly airports tracks and paved roads. Experiments carried out with digital images showed that the methodology allows to obtain the features, e.g. airports tracks, with efficiency.

Formato

73-78

Identificador

http://www.seer.ufu.br/index.php/cieng/article/view/532

Ciencia y Engenharia/ Science and Engineering Journal, v. 15, p. 73-78.

0103-944X

http://hdl.handle.net/11449/69401

2-s2.0-77953898740

2-s2.0-77953898740.pdf

Idioma(s)

por

Relação

Ciencia y Engenharia/ Science and Engineering Journal

Direitos

openAccess

Palavras-Chave #Cartography #Non-linear anisotropic diffusion #Orbital images #Partial Differential Equations #Remote Sensing #Detection models #Digital image #Image preprocessing #Optimal level #Paved road #Selective process #Temporal evolution #Computational fluid dynamics #Diffusion #Image segmentation #Low pass filters #Mapping #Maps #Mathematical models #Optical anisotropy #Remote sensing #Partial differential equations
Tipo

info:eu-repo/semantics/article