%0 Journal Article
%T Pseudo Bayesian and Linear Regression Global Thresholding
%A Khalid Aboura
%J International Journal of Electronics and Telecommunications
%D 2010
%I 
%R 10.2478/v10177-010-0008-1
%X 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.
%K Classification
%K Image Thresholding
%K Probability
%K Linear Regression
%U http://versita.metapress.com/content/03u0219802234u53/?p=53ad911483d7453a9aee5a84d9caafec&pi=7