Segmentation-assisted detection of dirt impairments in archived film sequences

Jinchang Ren, T. Vlachos

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)
44 Downloads (Pure)


A novel segmentation-assisted method for film
dirt detection is proposed. We exploit the fact that film dirt
manifests in the spatial domain as a cluster of connected
pixels whose intensity differs substantially from that of its
neighborhood and we employ a segmentation-based
approach to identify this type of structure. A key feature of
our approach is the computation of a measure of confidence
attached to detected dirt regions which can be utilized for
performance fine tuning. Another important feature of our
algorithm is the avoidance of the computational complexity
associated with motion estimation. Our experimental
framework benefits from the availability of manually
derived as well as objective ground truth data obtained
using infrared scanning. Our results demonstrate that the
proposed method compares favorably with standard
spatial, temporal and multistage median filtering
approaches and provides efficient and robust detection for a
wide variety of test material.
Original languageEnglish
Pages (from-to)463-470
Number of pages8
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Issue number2
Publication statusPublished - 2007


  • film dirt detection
  • archive restoration


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