Content identification based on digital fingerprint : what can be done if ML decoding fails?

F. Farhadzadeh, S. Voloshynovskiy, O. Koval

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)

Abstract

In this paper, the performance of the content identification based on digital fingerprinting and order statistic list decoding is analyzed by evaluating the probabilities of correct identification, false acceptance and the probability mass function of queried binary fingerprint position on the list of candidates. The particular attention is dedicated to the cases when traditional maximum likelihood decoder fails to produce the reliable content identification. The maximum likelihood decoding is shown to be a particular case of order statistic list decoding for the list size equals 1. We demonstrate the efficiency of the proposed content identification system performance by investigating the probability mass function behavior and imposing the constraint on the cardinality of list size.
Original languageEnglish
Title of host publication2010 IEEE International Workshop on Multimedia Signal Processing (MMSP)
Place of PublicationSaint-Malo, France
PublisherInstitute of Electrical and Electronics Engineers
Pages64-68
ISBN (Print)978-1-4244-8111-8
DOIs
Publication statusPublished - 2010

Fingerprint Dive into the research topics of 'Content identification based on digital fingerprint : what can be done if ML decoding fails?'. Together they form a unique fingerprint.

Cite this