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A Thresholding Method to Estimate Quantities of Each Class
Kenta Azuma, Kohei Arai, Ishitsuka Naoki
Pages - 35 - 46     |    Revised - 15-11-2012     |    Published - 31-12-2012
Volume - 3   Issue - 2    |    Publication Date - November / December 2012  Table of Contents
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KEYWORDS
Thresholding, Classification, Image Processing, Quantity of a Class, Counting Accuracy, Synthetic Aperture Radar
ABSTRACT
Thresholding method is a general tool for classification of a population. Various thresholding methods have been proposed by many researchers. However, there are some cases in which existing methods are not appropriate for a population analysis. For example, this is the case when the objective of analysis is to select a threshold to estimate the total number of data (pixels) of each classified population. In particular, If there is a significant difference between the total numbers and/or variances of two populations, error possibilities in classification differ excessively from each other. Consequently, estimated quantities of each classified population could be very different from the actual one. In this report, a new method which could be applied to select a threshold to estimate quantities of classes more precisely in the above mentioned case is proposed. Then verification of features and ranges of application of the proposed method by sample data analysis is presented.
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Mr. Kenta Azuma
Saga University - Japan
kentazuma@yahoo.co.jp
Professor Kohei Arai
Saga University - Japan
Dr. Ishitsuka Naoki
National Institute for Agro-Enviromental Sciences - Japan