By Topic

Dempster-Shafer's theory as an aid to color information processing. Application to melanoma detection in dermatology

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
P. Vannoorenberghe ; Lab. of Perception Syst. Inf., Rouen Univ., Mont-Saint-Aignan, France ; O. Colot ; D. De Brucq

In this paper, we first propose a color image segmentation method based on the Dempster-Shafer theory. The tristimuli R, G and B are considered as three independent information sources which can be very limited or weak. The basic idea consists of modeling the color information in order to have the features of each region in the image. This model, obtained on training sets extracted from the intensity, allows us to reduce the classification errors concerning each pixel of the image. The proposed segmentation algorithm has been applied to biomedical images in order to detect a kind of skin cancer (melanoma). In a second step, features concerning the lesion are extracted using color information. These features are used in order to classify the benign lesions (naevus) from the other. Results, including the management of false alarms and no detections, allow us to demonstrate the effectiveness of the proposed methodology

Published in:

Image Analysis and Processing, 1999. Proceedings. International Conference on

Date of Conference: