Robust underwater target recognition using auditory cepstral coefficients

Yaozhen Wu, Yixin Yang, Can Tao, Feng Tian, Long Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Feature vector extraction is measured as major step in development of underwater target recognition. To improve robustness of the performance of feature vector extraction, we proposed a novel approach for robust underwater target recognition applying the auditory cepstral coefficients (ACC) based on auditory filter and cubic-log compression instead of Mel filter and logarithmic compression in Mel-frequency cepstral coefficients (MFCC). Our experimental results show that the ACC feature represents considerably better than conventional acoustic features, and the ACC feature is used for underwater target recognition system to yield promising recognition performance.

Original languageEnglish
Title of host publicationOCEANS 2014 - TAIPEI
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479936465
DOIs
StatePublished - 20 Nov 2014
EventOCEANS 2014 MTS/IEEE Taipei Conference: Oceans Regeneration - Taipei, Taiwan, Province of China
Duration: 7 Apr 201410 Apr 2014

Publication series

NameOCEANS 2014 - TAIPEI

Conference

ConferenceOCEANS 2014 MTS/IEEE Taipei Conference: Oceans Regeneration
Country/TerritoryTaiwan, Province of China
CityTaipei
Period7/04/1410/04/14

Keywords

  • auditory cepstral coefficients
  • auditory filter
  • cubic-log compression
  • feature extraction
  • underwater target recognition

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