An initial study of interference coloration for quantifying the texture and fabric of ice

Cody C. Owen*, Hayo Hendrikse

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
73 Downloads (Pure)


The manual application of universal (Rigsby) stage techniques is commonly used to determine the fabric of thin sections of ice viewed with crossed-polarized light. This process can require hours of focus in cold conditions to identify the c-axis of each grain in a thin section. Automated ice texture and fabric methods of several forms exist but are rarely implemented beyond the field of glaciology. The present study introduces a method based on the theory of interference coloration for automated ice texture and quarter fabric analysis by using in-plane conventional photography of an ice thin section as input. The method is compatible with universal stages and polariscopes, and is not restricted by the planar-face dimensions of the thin section, allowing for thin section analysis of any size when sufficient digital camera resolution is available. Light source color temperature and chromatic adaptation are considered in the interference coloration theory, and ice fabrics are simulated for reference in identifying ice types. Sample thin section texture and quarter fabric analyses from freshwater lake and laboratory-grown ice are presented to demonstrate the applications of the method. The method is compared with the Rigsby stage technique, which yielded mean (standard deviation of) azimuth and inclination errors of 2.9 (1.0) and 11.5 (8.0) degrees, respectively, thereby demonstrating accuracy sufficient for quantifying quarter fabrics when considering a mean standard deviation in inclination of 5.4 degrees with the Rigsby stage technique.

Original languageEnglish
Article number103735
JournalCold Regions Science and Technology
Publication statusPublished - 2023


  • Birefringence
  • c-axis
  • Grain boundary
  • Ice microstructure
  • Image processing


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