Detecting Re-captured Videos Using Shot-Based Photo Response Non-Uniformity

Jung, Dae-Jin; Hyun, Dai-Kyung; Ryu, Sang Young; Lee, Jiwon; Lee, Hae-Yeoun; Lee, Heung-Kyu

doi:10.1007/978-3-642-32205-1_23

Cited by 3 publications

(6 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The authors in [126] detected video re-capture by exploiting the Photo Response Non-Uniformity (PRNU) of selected video shots. PRNU is a stochastic fingerprint unique to all image or video sensors.…”

Section: Video Re-capture Detection Techniquesmentioning

confidence: 99%

Video content authentication techniques: a comprehensive survey

Singh

Aggarwal

2017

Multimedia Systems

View full text Add to dashboard Cite

Section: Video Re-capture Detection Techniquesmentioning

confidence: 99%

Video content authentication techniques: a comprehensive survey

Singh

Aggarwal

2017

Multimedia Systems

View full text Add to dashboard Cite

“…However, the videos that have undergone inter-frame interpolation (including frame rate change) would exhibit a high FPR. Jung et al proposed a recaptured video detection method using the shot-based SPN [14]. The shot-based SPNs are estimated and examined to identify the recaptured videos.…”

Section: Related Workmentioning

confidence: 99%

“…To resolve the low-quality problem of the estimated shot-based SPN, Warshall's algorithm was used in Jung et al's method [14]. However, Warshall's algorithm only helped the erroneously uncorrelated shot-based SPN pairs to be linked to each other.…”

Section: Correlation-based Spn Merging Using High-frequency Mapmentioning

confidence: 99%

“…Three different k values (0 original criteria, 1, and 2) were used in the tests. Furthermore, in order to demonstrate the performance of the proposed method, it was compared with two recaptured image detection methods (Cao and Kot's method [9], Gao et al's method [10]) and three recaptured video detection methods (Wang and Farid's method [11], Bestagini et al's method [13], and Jung et al's method [14]). In order to apply the recaptured image detection methods to the obtained videos, every I frame was extracted from the N S shots that were used in testing the proposed method.…”

Section: Experiments Settingsmentioning

confidence: 99%

“…8. First, Jung et al's method [14] exhibited steep slopes in the receiver operating characteristic (ROC) curves; these slopes were caused by a few low-quality SPNs. Several low correlations between shot-based SPNs were compensated for using Warshall's algorithm, but the limitation of the low quality of the shot-based SPN was not.…”

Section: Quality Factor Experimentsmentioning

confidence: 99%

See 2 more Smart Citations

Recaptured video detection based on sensor pattern noise

Jung

Hyun

Lee

2015

J Image Video Proc.

Self Cite

View full text Add to dashboard Cite

With the advances in digital camcorders, video recapturing (screen camcording), which is also called camcorder theft, is becoming a significant problem. Nevertheless, little research on recaptured video detection has been undertaken. In this paper, an automated method for the detection of recaptured videos is proposed based on the shot-based sensor pattern noise (SPN). The SPN, which is considered to be the fingerprint of digital imaging sensors, is used due to its identifiable attribute. Furthermore, the differences between the production processes of the original videos and recaptured videos are analyzed, and this results in the shot-based method being proposed. Moreover, the SPN merging and high-frequency map are derived in order to overcome the low quality of the shot-based SPN. Empirical evidence from a large database of test video, including compressed and scaled video, indicates that superior performance of the proposed method.

show abstract

Video recapture detection based on ghosting artifact analysis

Bestagini

Visentini-Scarzanella

Tagliasacchi

et al. 2013

2013 IEEE International Conference on Image Processing

View full text Add to dashboard Cite

Video forensics is becoming a popular field of research and an increasing number of forensic techniques have been proposed in the last few years. However, a simple yet effective method to fool many detectors consists in recapturing a video sequence with a camcorder. For this reason being able to detect video recapture is a topic of interest for a forensic analyst. In this paper, we first characterize the video recapture model, focusing on the common scenario of a sequence recaptured from a LCD monitor using a digital camcorder, then we propose a recapture detector for this case. The detector is based on the analysis of a characteristic ghosting artifact left by the recapture process. The presented algorithm is finally validated by means of tests on original and recaptured sequences. These tests prove that the algorithm achieves high accuracy results.

show abstract

Detecting Re-captured Videos Using Shot-Based Photo Response Non-Uniformity

Cited by 3 publications

References 8 publications

Video content authentication techniques: a comprehensive survey

Video content authentication techniques: a comprehensive survey

Recaptured video detection based on sensor pattern noise

Video recapture detection based on ghosting artifact analysis

Contact Info

Product

Resources

About