Edge detection using a new definition of entropy

Author

Vitulano, S. ; Nappi, M. ; Vitulano, D. ; Masuovito, C.

Author_Institution

Inst. of Internal Med., Cagliari Univ., Italy

Volume

2

fYear

1996

fDate

25-29 Aug 1996

Firstpage

141

Abstract

The paper describes a possible model of the human perceptive process. In this paper the relation between the entropy of an image domain and the entropy of its subdomains is explored as a uniformity predicate. Such entropy is obtained from the analysis of the image histogram associating a Gaussian distribution to the maximum frequency of grey levels. With the aim of implementing the model, we have introduced a well known technique of problem solving. The most important roles of our model are played by the evaluation function (EF) and the control strategy. So the EF is related to the ratio between the entropy of one region or zone of the picture and the entropy of the entire picture. The control strategy determines the optimal path in the quadtree so that the nodes of the optimal path have minimal entropy. The paper shows some comparisons between the method and classical edge detection techniques

Keywords

Chebyshev approximation; Gaussian distribution; computer vision; edge detection; image segmentation; maximum entropy methods; problem solving; quadtrees; Chebyshev distance; Gaussian distribution; clustering; edge detection; entropy; evaluation function; grey level image; image analysis; image histogram; image segmentation; optimal path; problem solving; quadtree; uniformity predicate; Biomedical imaging; Chebyshev approximation; Entropy; Frequency; Histograms; Humans; Image edge detection; Image segmentation; Shape; Smoothing methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 1996., Proceedings of the 13th International Conference on

Conference_Location

Vienna

ISSN

1051-4651

Print_ISBN

0-8186-7282-X

Type

conf

DOI

10.1109/ICPR.1996.546740

Filename

546740