Weighting optimization with neural network for photo-response-non-uniformity-based source camera identification

Chao Shi, Ngai Fong Law, Hung Fat Frank Leung, Wan Chi Siu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Identifying the source camera of images is becoming increasingly important nowadays. A popular approach is to use a type of pattern noise called photo-response non-uniformity (PRNU). Despite that, the PRNU-based approach is sensitive towards scene content and image intensity. The identification is poor in areas having low or saturated intensity, or in areas with complicated texture. To solve the scene content problem, a weighting scheme that considers the reliability of image regions has been proposed in this paper. The proposed method uses an artificial neural network to determine the optimal weighting of each sub-block in images. Then the weightings are used to help determine the reliability of that region in identifying the source camera. The proposed method is tested against several state-of-art methods. The experiments show an encouraging result in terms of the ROC curve.
Original languageEnglish
Title of host publication2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014
PublisherIEEE
ISBN (Electronic)9786163618238
DOIs
Publication statusPublished - 12 Feb 2014
Event2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014 - Chiang Mai, Thailand
Duration: 9 Dec 201412 Dec 2014

Conference

Conference2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014
Country/TerritoryThailand
CityChiang Mai
Period9/12/1412/12/14

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems

Cite this