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Abstract
Limitations of some of the existing threshold selection techniques have been discussed. The approximate minimum error thresholding algorithm of Kittler and Illingworth has been modified considering a Poisson distribution for the grey level instead of the commonly used normal distribution. Justification in support of a Poisson distribution has also been given. The modified method is found to be much better from the point of view of both convergence and segmented output. Two algorithms based on a new conditional entropy measure of a partitioned image have been formulated. The proposed methods have been applied on a number of images and are found to produce good results.
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