Skip to content
Technical NotePublished

Técnica de Segmentação de Imagens por Entropia Relativa não Extensiva

M. Portes de Albuquerque; Marcelo P. de Albuquerque; Dário Oliveira; Maysa Macedo; Israel A. Esquef

Publication details

Authors
M. Portes de Albuquerque; Marcelo P. de Albuquerque; Dário Oliveira; Maysa Macedo; Israel A. Esquef
Type
Technical Note
Status
Published
Publication date
28/09/2010
Description
Image analysis usually refers to processing of images with the goal of finding objects in the image. Image segmentation is one of the most critical tasks in automatic image analysis. The non-extensive entropy is a recent development in statistical mechanics and has been considered as a useful measure in describing termostatistical properties of physical systems. In this formalism a real quantity q was introduced as parameter for physical systems that presents long range interactions, long time memories and fractal-type structures. In image processing, one of the most efficient techniques for image segmentation is entropy-based thresholding. This approach uses relative entropy from the information theory considering the gray level image histogram and a theoretical one as probabilities distributions. In this work, we applied non-extensive entropy as formalism for information theory. It was proposed an image thresholding method using relative entropy basis. Some typical results using this method are presented and illustrate the influence of the q in the thresholding process. Palavra-chave: Segmentação de imagens, entropia não-extensiva e entropia relativa generalizada.
Year
2006
Number
CBPF-NT-003/06
Linked to a thesis
No
Linked to a grant
No
© 2004–2026 Brazilian Center for Research in Physics · Developed by COTEC · v2.0.13