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Erschienen in:
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2015 | OriginalPaper | Buchkapitel

Application of Image Processing Techniques to the Identification of Phases in Steel Metallographic Specimens

verfasst von : Adarsh Kesireddy, Sara McCaslin

Erschienen in: New Trends in Networking, Computing, E-learning, Systems Sciences, and Engineering

Verlag: Springer International Publishing

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Abstract

Metallographic image processing focuses primarily on image segmentation, edge detection, and approximating grain size. This paper presents the results of applying a radial basis function neural network to the image texture data obtained from steel metallographic specimens to determine the feasibility of the automated recognition of steel phases.

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Vorheriges Kapitel Gravitation Search Training Algorithm for Asynchronous Distributed Multilayer Perceptron Model
Nächstes Kapitel Requirement and Interaction Analysis Using Aspect-Oriented Modeling
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Metadaten
Titel
Application of Image Processing Techniques to the Identification of Phases in Steel Metallographic Specimens
verfasst von
Adarsh Kesireddy
Sara McCaslin
Copyright-Jahr
2015
Buch
New Trends in Networking, Computing, E-learning, Systems Sciences, and Engineering

Print ISBN: 978-3-319-06763-6

Electronic ISBN: 978-3-319-06764-3

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-06764-3_53

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