Return to search

Determining the recording time of digital media by using the electric network frequency

Authentication of recordings is an important task in forensic sciences. When processing audio or video material, some tasks might be related to determining whether or not the material has been edited or falsified in any way, or in other cases, to determine at what point in time a recording was made. The transition from analog to digital media has provided a solid foundation for the process of determining recording times by using the frequency variations in the electrical network, when interferences from the network are present in the investigated recording. This thesis describes a method of how to record the frequency of the electrical network in order to establish a reference database, evaluates several methods to isolate and extract the disturbances from recordings as well as suggests methods of how to search the database in order to locate the time of a recording. It is concluded, that each of the methods suggested has both advantages and disadvantages, depending on the state of the examined recording. Tests are also conducted in order to determine, whether or not, battery powered recording equipment is susceptible to recording the disturbances, or harmonics thereof, from electromagnetic fields near conducting wire or other electrical equipment. It is found that the fundamental frequency disturbance is usually difficult to detect, but also, that it is not uncommon that harmonics can be present in the recordings from the battery powered devices tested. Included in this thesis are also the results of the development of a graphical user interface for Matlab, where some of the features include the possibility to filter sound files, estimate frequency patterns and perform database searches, as well as the evaluation of a frequency analysis software. Both intended to serve as an aid for locating and extracting the disturbances of interest, as well as for finding the corresponding frequency patterns in the established database.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-160370
Date January 2011
CreatorsKantardjiev, Alex
PublisherUppsala universitet, Signaler och System
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess
RelationUPTEC E, 1654-7616 ; 11005

Page generated in 0.0025 seconds