Cart (Loading....) | Create Account
Close category search window
 

Online incremental image classification by use of human assisted fuzzy similarity

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
$31 $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

1 Author(s)
Vachkov, G. ; Dept. of Reliability-based Inf. Syst. Eng., Kagawa Univ., Takamatsu, Japan

In this paper we propose a computational scheme for online incremental type classification of images, based on human assisted fuzzy similarity analysis. First of all, two main parameters from each image are extracted in the form of a center-of-gravity and a generalized volume of the image model.. Then their differences for each pair of images are taken as respective features F1 and F2, which serve as inputs of the fuzzy inference system for similarity analysis. This system uses special asymmetrical Gaussian membership functions that are later tuned by using a predefined list of human decisions (similarities). The list includes fixed number of available pairs of images and the objective is to minimize the discrepancy between the human and the computer similarity decision. The proposed online incremental classification scheme starts with an Image Base consisting of several Core Images that are compared with the new sequentially coming images. With a predetermined threshold, the new images are judged as members of an existing class from the Image Base or as new members thus creating a new class that is added to the Image Base. The flexibility and applicability of the proposed human assisted incremental classification is illustrated on an example of 16 flower images and the results are discussed in the paper.

Published in:

Information and Automation (ICIA), 2010 IEEE International Conference on

Date of Conference:

20-23 June 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.