On searching for an optimal threshold for morphological image segmentation |
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Authors: | Francisco A Pujol Mar Pujol Ramón Rizo Maria José Pujol |
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Affiliation: | 1.Departamento de Tecnología Informática y Computación,Escuela Politécnica Superior, Universidad de Alicante,Alicante,Spain;2.Departamento de Ciencia de la Computación e Inteligencia Artificial,Escuela Politécnica Superior, Universidad de Alicante,Alicante,Spain;3.Departamento de Matemática Aplicada,Escuela Politécnica Superior, Universidad de Alicante,Alicante,Spain |
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Abstract: | Segmentation of images represents the first step in many of the tasks that pattern recognition or computer vision has to deal
with. Therefore, the main goal of our paper is to describe a new method for image segmentation, taking into account some Mathematical
Morphology operations and an adaptively updated threshold, what we call Morphological Gradient Threshold, to obtain the optimal segmentation. The key factor in our work is the calculation of the distance between the segmented
image and the ideal segmentation. Experimental results show that the optimal threshold is obtained when the Morphological Gradient Threshold is around the 70% of the maximum value of the gradient. This threshold could be computed, for any new image captured by the
vision system, using a properly designed binary metrics. |
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Keywords: | |
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