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Energy-based linear PCM audio recovery method of impaired MP4 file stored in dashboard camera memory

Authors :
Oc-Yeub Jeon
Jung Hwan Lee
Lim Seong Ho
Park Nam In
Byun Jun Seok
JiWoo Lee
Gi-Hyun Na
Source :
Forensic Science International: Digital Investigation. 39:301274
Publication Year :
2021
Publisher :
Elsevier BV, 2021.

Abstract

Sounds recorded by a dashboard camera presents essential evidence on a vehicle's driving condition for analyzing car accidents. In reality, when a direct impact of a vehicle equipped with a dashboard camera occurs, the power supply to the dashboard camera is abruptly terminated, and the digital video being recorded at that time may be incompletely stored; thus, there is no information such as the location or size to be read for the image and audio decoding. In this paper, we propose a method for recovering the linear pulse code modulation (PCM) audio from the impaired MP4 file partially stored in a video event data recorder (VEDR), known as a dashboard camera, during road vehicle accidents. This method is based on the principle of extracting an actual audio signal using the energy of each frame in the pseudo audio, which is generated from all data in the “mdat” area of the impaired MP4 file. For performance evaluation, the various video files with linear PCM audio format in the MP4 container were obtained through the different dashboard cameras. As the objective evaluation, we measured the audio recovery ratio, distance based on dynamic time warping (DTW) and comparison of the waveform and spectrogram. Moreover, the performance of the proposed method was evaluated using the multiple stimuli with a hidden reference and anchor (MUSHRA) test as the subjective assessment. As a result, it is shown from the evaluation that the proposed method can recover significantly better the linear PCM audio signal than the conventional methods from an impaired MP4 file.

Details

ISSN :
26662817
Volume :
39
Database :
OpenAIRE
Journal :
Forensic Science International: Digital Investigation
Accession number :
edsair.doi...........fd0117df1989d6beec732f20efc18807