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Detection of video frame insertion based on constraint of human visual perception

Abstract

dc:description.abstract

Recently, due to availability of inexpensive and easily-operable multimedia tools, digital multimedia technology has experienced drastic advancements. At the same time, video forgery becomes much easier and makes more difficult to validate the video content. Consequently, the origin and integrity of video can no longer be taken for granted. A methodology is developed that is capable of detecting the video frame insertion based on the constraint of human visual perception. The main idea is based on the so-called differential sensitivity. That is, that the variation of brightness of neighboring video frames has some constraint. First, the video sequence is partitioned into short and overlapping sub-sequences. Second, the ratio of the temporal variation of brightness calculated at the beginning and the ending frames of each sub-sequence is computed and compared with a threshold to determine the approximate location of the video frame insertion. Third, a procedure is conducted to determine the exact location of the insertion. The success of simulation works on more than 200 video sequences. The precision rate of detection is about 94.09%, and the precision rate of detecting location of frame insertion is 84.88% on testing database

Degree

thesis:*
Name thesis:degree_name
Master of Science in Electrical Engineering - (M.S.)
Discipline thesis:degree_discipline
Electrical and Computer Engineering
Year
2013

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Zheng, Lu
Contributors dc:contributor
  • Yun Q. Shi
  • Edwin Hou
  • Tan-Feng Sun

Subjects

dc:subject × 3

Identifiers

dc:identifier.*
Repository record dc:identifier
https://digitalcommons.njit.edu/theses/222
OAI identifier oai:identifier
oai:digitalcommons.njit.edu:theses-1221

Chain of custody

source
Harvested from
NJIT
Base URL
digitalcommons.njit.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Zheng, Lu. Detection of video frame insertion based on constraint of human visual perception. 2013. https://digitalcommons.njit.edu/theses/222