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

Robust recognition of white blood cell images

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

3 Author(s)
Kovalev, V.A. ; Inst. of Math., Acad. of Sci., Gomel, Byelorussia ; Grigoriev, A.Y. ; Hyo-Sok Ahn

The objective of this work is to investigate the white blood cell (WBC) image recognition problem at all stages. A robust and effective method for automatic WBC differentiation, based on both statistical pattern recognition and neural net approaches, is presented. We demonstrate well-evaluated results ranging from image scene segmentation techniques to recognition details. Recognition accuracy on the test set of 662 images of five WBC types obtained by different imaging systems from 22 bloodstains is not less than 98%

Published in:

Pattern Recognition, 1996., Proceedings of the 13th International Conference on  (Volume:4 )

Date of Conference:

25-29 Aug 1996

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.