Nondestructive Diagnosis and Analysis of Computed Microtomography Images via Texture Descriptors

Sandro R. Fernandes, Joaquim T. de Assis, Vania Vieira Estrela, Navid Razmjooy, Anand Deshpande, P. Patavardhan, R. J. Aroma, K. Raimond, Hermes J. Loschi, Douglas A. Nascimento

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review


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.
Original languageEnglish
Title of host publicationAdvances in Multidisciplinary Medical Technologies ─ Engineering, Modeling and Findings
Subtitle of host publicationProceedings of the ICHSMT 2019
ISBN (Electronic)978-3-030-57552-6
Publication statusPublished - 2021
Externally publishedYes
EventInternational Congress on Health Sciences and Medical Technologies, ICHSMT 2019 - Tlemcen, Algeria
Duration: 5 Dec 20197 Dec 2019


ConferenceInternational Congress on Health Sciences and Medical Technologies, ICHSMT 2019

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