Hashmi, Muhammad Abdur Rehman;
Raza, Rana Hammad;
(2017)
Landmark Based Audio Fingerprinting for Naval Vessels.
In:
2016 International Conference on Frontiers of Information Technology (FIT).
(pp. pp. 297-302).
IEEE: Islamabad, Pakistan.
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Abstract
This paper presents a novel landmark based audio fingerprinting algorithm for matching naval vessels' acoustic signatures. The algorithm incorporates joint time - frequency based approach with parameters optimized for application to acoustic signatures of naval vessels. The technique exploits the relative time difference between neighboring frequency onsets, which is found to remain consistent in different samples originating over time from the same vessel. The algorithm has been implemented in MATLAB and trialed with real acoustic signatures of submarines. The training and test samples of submarines have been acquired from resources provided by San Francisco National Park Association [14]. Storage requirements to populate the database with 500 tracks allowing a maximum of 0.5 Million feature hashes per track remained below 1GB. On an average PC, the database hash table can be populated with feature hashes of database tracks @ 1250 hashes/second achieving conversion of 120 seconds of audio data into hashes in less than a second. Under varying attributes such as time skew, noise and sample length, the results prove algorithm robustness in identifying a correct match. Experimental results show classification rate of 94% using proposed approach which is a considerable improvement as compared to 88% achieved by [17] employing existing state of the art techniques such as Detection Envelope Modulation On Noise (DEMON) [15] and Low Frequency Analysis and Recording (LOFAR) [16].
| Type: | Proceedings paper |
|---|---|
| Title: | Landmark Based Audio Fingerprinting for Naval Vessels |
| Event: | 14th International Conference on Frontiers of Information Technology |
| Dates: | 19 Dec 2016 - 21 Dec 2016 |
| ISBN-13: | 978-1-5090-5300-1 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/fit.2016.061 |
| Publisher version: | https://doi.org/10.1109/fit.2016.061 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Time-frequency analysis; Databases; Acoustics; Sonar; Propellers; Fingerprint recognition |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Engineering Science Faculty Office |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10162595 |
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