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Active Contour Multigrid Model for Segmentation and Automatic Quantification of Material Phases of Cast Iron
Author(s) -
Pattan Prakash,
V. D. Mytri,
P. S. Hiremath
Publication year - 2010
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/1372-1849
Subject(s) - computer science , cast iron , segmentation , active contour model , artificial intelligence , pattern recognition (psychology) , computer vision , image segmentation , materials science , composite material
critical and important stage in microstructure image analysis is segmentation, because the segmentation method has direct impact on the end results of analysis. The main aim of this paper is to determine appropriate segmentation method for microstructure image analysis and quantification. In this work, some popular segmentation methods, namely, Otsu's automatic threshold, watershed, uni-grid active contour method and multi-grid active contour methods have been investigated. The reliability of the segmentation methods is tested by determining the volume fraction of phases present in microstructure images of materials of known chemical composition. The experimentation is done using microstructure images of cast iron of various compositions. The experimental results are compared with expected values of volume fraction. The active contour multi-grid segmentation model is found to yield better results within the practical limits as compared to manual and other automated methods.

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