Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Pseudo Bayesian and Linear Regression Global Thresholding

Pseudo Bayesian and Linear Regression Global Thresholding Pseudo Bayesian and Linear Regression Global Thresholding Classification is an important task in image analysis. Simply recognizing an object in an image can be a daunting step for a computer algorithm. The methodologies are often simple but rely heavily on the thresholding of the image. The operation of turning a color or gray-scale image into a black and white image is a determining step in the effectiveness of a solution. Thresholding methods perform differently in various problems where they are often used locally. Global thresholding is a difficult task in most problems. We highlight a pseudo Bayesian and a linear regression global thresholding methods that performed well in an engineering problem. The same approaches can be used in biomedical applications where the environment is better controlled. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Electronics and Telecommunications de Gruyter

Pseudo Bayesian and Linear Regression Global Thresholding

Download PDF
10 pages

Loading next page...
 
/lp/de-gruyter/pseudo-bayesian-and-linear-regression-global-thresholding-htetJ01PGG

References (32)

Publisher
de Gruyter
Copyright
Copyright © 2010 by the
ISSN
0867-6747
DOI
10.2478/v10177-010-0008-1
Publisher site
See Article on Publisher Site

Abstract

Pseudo Bayesian and Linear Regression Global Thresholding Classification is an important task in image analysis. Simply recognizing an object in an image can be a daunting step for a computer algorithm. The methodologies are often simple but rely heavily on the thresholding of the image. The operation of turning a color or gray-scale image into a black and white image is a determining step in the effectiveness of a solution. Thresholding methods perform differently in various problems where they are often used locally. Global thresholding is a difficult task in most problems. We highlight a pseudo Bayesian and a linear regression global thresholding methods that performed well in an engineering problem. The same approaches can be used in biomedical applications where the environment is better controlled.

Journal

International Journal of Electronics and Telecommunications – de Gruyter

Published: Mar 1, 2010

There are no references for this article.