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Nondestructive Diagnosis and Analysis of Computed Microtomography Images via Texture Descriptors

Copyright © Fernandes S.R. et al. (2021) Nondestructive Diagnosis and Analysis of Computed Microtomography Images via Texture Descriptors. In: Khelassi A., Estrela V.V. (eds) Advances in Multidisciplinary Medical Technologies ─ Engineering, Modeling and Findings. Springer, Cham. https://doi.org/10.1007/978-3-030-57552-6_16

Abstract

X-ray computed microtomography (μCT or micro-CT) allows a nondestructive analysis of samples, which helps their reuse. The X-ray μCT equipment offers the user several configuration options that change the quality of the images obtained, thus affecting the expected result. In this study, a methodology for analyzing X-ray μCT images generated by the SkyScan 1174 Compact Micro-CT equipment was developed. The basis of this analysis methodology is texture descriptors. Three sets of images were used, and then degradations and noise were applied to the original images, generating new images. Subsequently, the following texture descriptors assisted in scrutinizing the sets: maximum probability, the moment of difference, the inverse difference moment, entropy, and uniformity. Experiments show the outcomes of some tests.

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