Polynomial regression, area and length based filtering to remove misclassified pixels acquired in the crack segmentation process of 2D X-ray CT images of tested plaster specimens

Ujjal Kumar Bhowmik, Tyler Cork, Nick W. Hudyma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This work presents an effective and robust technique to remove misclassified pixels acquired in the crack segmentation process of 2D X-ray CT images of tested plaster specimens. Cracks have distinct properties, such as they are fairly piece-wise linear, and they have certain area and length ratios, which can be used to remove misclassified pixels from cracks segments. In this paper, a combination of polynomial regression and area-based, length-based filtering scheme is applied to remove undesired pixels from the 2D CT images of plaster specimen. With the help of experimental results the effectiveness and robustness of the proposed technique are verified.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 International Conference on Computational Science and Computational Intelligence, CSCI 2015
EditorsQuoc-Nam Tran, Leonidas Deligiannidis, Hamid R. Arabnia
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages437-442
Number of pages6
ISBN (Electronic)9781467397957
DOIs
StatePublished - Mar 2 2016
Externally publishedYes
EventInternational Conference on Computational Science and Computational Intelligence, CSCI 2015 - Las Vegas, United States
Duration: Dec 7 2015Dec 9 2015

Publication series

NameProceedings - 2015 International Conference on Computational Science and Computational Intelligence, CSCI 2015

Other

OtherInternational Conference on Computational Science and Computational Intelligence, CSCI 2015
CountryUnited States
CityLas Vegas
Period12/7/1512/9/15

Keywords

  • Area-based filtering
  • Computed tomography (CT)
  • Length-based filtering
  • Local entropy based thresholding
  • Polynomial regression based filtering

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing

Fingerprint Dive into the research topics of 'Polynomial regression, area and length based filtering to remove misclassified pixels acquired in the crack segmentation process of 2D X-ray CT images of tested plaster specimens'. Together they form a unique fingerprint.

Cite this