Face filtering - Insights from real-world data

Yohannes Biadgligne, Ognjen Arandelovic

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

2 Citations (Scopus)


Digital image processing filters continue to be used widely for the normalization of illumination effects in face recognition, both in research and in practice. Their appeal stems from their simplicity, efficiency, predictable and well-understood behaviour, and importantly, lack of catastrophic failure modes. Notwithstanding this widespread use, no work to date has performed a comparative analysis of different filters in challenging, realistic conditions expected in practice - filters in previous work are either adopted in isolation or evaluated in constrained conditions unrepresentative of real-world challenges. In this paper we perform, report, and discuss a comparative evaluation of a number of popular filters on a challenging, real-world data set which contains major changes in illumination, pose (yaw and pitch), camera-user distance, image resolution, and (often neglected) camera type. Our results demonstrate that relative performances of different filters in realistic imaging conditions such as those examined in this paper are vastly different than when the same filters are evaluated in a controlled setting as in previous work. Therefore our results provide important insight for practical application of image filters and future research.

Original languageEnglish
Title of host publication2015 22nd International Conference on Systems, Signals and Image Processing - Proceedings of IWSSIP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Print)9781467383530
Publication statusPublished - 30 Oct 2015
Event22nd International Conference on Systems, Signals and Image Processing, IWSSIP 2015 - London, United Kingdom
Duration: 10 Sept 201512 Sept 2015


Conference22nd International Conference on Systems, Signals and Image Processing, IWSSIP 2015
Country/TerritoryUnited Kingdom


  • Filter
  • Image Processing
  • Quotient
  • Recognition


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