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2013 | OriginalPaper | Chapter

Crack’s Detection, Measuring and Counting for Resistance’s Tests Using Images

Authors : Carlos Briceño, Jorge Rivera-Rovelo, Narciso Acuña

Published in: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Publisher: Springer Berlin Heidelberg

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Currently, material resistance research is looking for biomaterials where mechanical properties (like fatigure resistance) and biocompatibility are the main characteristics to take into account. To understand the behavior of materials subject to fatigue, usually we analyze how the material responds to cyclic forces. Failures due to fatigue are the first cause of cracks in materials. Normally, failures start with a superficial deficiency and produce micro cracks, which grow until a total break of the material. In this work we deal with the early detection of micro cracks on the surface of bone cement, while they are under fatigue tests, in order to characterize the material and design better and more resistant materials according to where they would be applied. The method presented for crack detection consists in several stages: noise reduction, shadow elimination, image segmentation and path detection for crack analysis. At the end of the analysis of one image, the number of cracks and the length of each one can be obtained (based on the maximum length of crack candidates). If a video is analyzed, the evolution of cracks in the material can be observed.

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Metadata
Title
Crack’s Detection, Measuring and Counting for Resistance’s Tests Using Images
Authors
Carlos Briceño
Jorge Rivera-Rovelo
Narciso Acuña
Copyright Year
2013
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-41827-3_18

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