Application of gradient-based Hough transform to the detection of corrosion pits in optical images

Yafei Wang, Guangxu Cheng

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)


In this paper, we introduce a circle detection technique named Hough transform to automatically recognize the corrosion pits in microscopic images. All the points in the input image are transformed into a parameter space, which is represented by a two-dimensional accumulative array with the same size of the original image. Local extreme values in the accumulative array, which represent the candidates of corrosion pits, are located using a maxima searching algorithm. The accuracy of detecting the number, radius and coordinate of pits from simulated images was examined. The results show that more than 95% of pits were successfully detected and the average errors of radius and coordinate are less than 10%, while these errors have negligible effect on the pit size distribution. The introduced method can also differentiate pits from scratches or inclusions, as indicated by the 100% accuracy of pit detection, from the simulated images presented in this study. Therefore, it is believed that the gradient-based Hough transform is a powerful method for the recognition of corrosion pits in microscopic images, making the statistical analysis of pit size and pit locations easier and more efficient.

Original languageEnglish
Pages (from-to)9-18
Number of pages10
JournalApplied Surface Science
Publication statusPublished - Mar 15 2016
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • Condensed Matter Physics
  • General Physics and Astronomy
  • Surfaces and Interfaces
  • Surfaces, Coatings and Films


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