• About
  • Policies
  • What is open access
  • Library
  • Contact
Advanced search
      View Item 
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Engineering
      • Department of Computer Engineering
      • View Item
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Engineering
      • Department of Computer Engineering
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Recognition of vessel acoustic signatures using non-linear teager energy based features

      Thumbnail
      View / Download
      547.3 Kb
      Author
      Can, Gökmen
      Akbaş, Cem Emre
      Çetin, A. Enis
      Date
      2016-10
      Source Title
      International Workshop on Computational Intelligence for Multimedia Understanding, IWCIM 2016
      Publisher
      IEEE
      Pages
      1 - 5
      Language
      English
      Type
      Conference Paper
      Item Usage Stats
      164
      views
      451
      downloads
      Abstract
      This paper proposes a vessel recognition and classification system based on vessel acoustic signatures. Teager Energy Operator (TEO) based Mel Frequency Cepstral Coefficients (MFCC) are used for the first time in Underwater Acoustic Signal Recognition (UASR) to identify platforms the acoustic noise they generate. TEO based MFCC (TEO-MFCC), being more robust in noisy conditions than conventional MFCC, provides a better estimation platform energy. Conventionally, acoustic noise is recognized by sonar oper-ators who listen to audio signals received by ship sonars. The aim of this work is to replace this conventional human-based recognition system with a TEO-MFCC features-based classification system. TEO is applied to short-time Fourier transform (STFT) of acoustic signal frames and Mel-scale filter bank is used to obtain Mel Teager-energy spectrum. The feature vector is constructed by discrete cosine transform (DCT) of logarithmic Mel Teager-energy spectrum. Obtained spectrum is transformed into cepstral coefficients that are labeled as TEO-MFCC. This analysis and implementation are carried out with datasets of 24 different noise recordings that belong to 10 separate classes of vessels. These datasets are partially provided by National Park Service (NPS). Artificial Neural Networks (ANN) are used as a classification method. Experimental results demonstrate that TEO-MFCC achieves 99.5% accuracy in classification of vessel noises. © 2016 IEEE.
      Keywords
      MFCC
      Teager energy
      Vessel recognition
      Acoustic noise
      Acoustic variables measurement
      Acoustic waves
      Artificial intelligence
      Audio acoustics
      Discrete cosine transforms
      Neural networks
      Sonar
      Spectroscopy
      Speech recognition
      Discrete Cosine Transform(DCT)
      Mel-frequency cepstral coefficients
      MFCC
      Short time Fourier transforms
      Teager energy
      Teager energy operators
      Underwater acoustic signal
      Vessel Recognition
      Underwater acoustics
      Permalink
      http://hdl.handle.net/11693/37718
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/IWCIM.2016.7801190
      Collections
      • Department of Computer Engineering 1430
      • Department of Electrical and Electronics Engineering 3657
      Show full item record

      Related items

      Showing items related by title, author, creator and subject.

      • Thumbnail

        Wave propagation and acoustic band gaps of two-dimensional liquid crystal/solid phononic crystals 

        Oltulu, O.; Mamedov, A. M.; Özbay, Ekmel (Springer Verlag, 2017)
        The vast majority of acoustic wave propagation in phononic band studies has been usually carried out by scattering inclusions embedded in a viscoelastic medium, such as air or water. In this study, we present calculated ...
      • Thumbnail

        Anisotropy sensitivity of an acoustic lens with slit aperture 

        Atalar, Abdullah; Ishikawa, I.; Ogura, Y.; Tomita, K. (IEEE, 1993)
        A conventional spherical acoustic lens is modified by restricting its aperture in the form of a slit to provide directional sensitivity. The spacing between the two parallel absorbing sheets forming the slit is adjustable ...
      • Thumbnail

        A wideband and a Wide-Beamwidth acoustic transducer design for underwater acoustic communications 

        Elmaslı, I. Ceren; Köymen, Hayrettin (IEEE, 2007-05)
        This paper is concerned with the design of an efficient, wideband and a wide-beamwidth resonant acoustic transducer for high frequency use. The general transducer structure which has two back-to-back quarter wave thick 1-3 ...

      Browse

      All of BUIRCommunities & CollectionsTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartmentsThis CollectionTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartments

      My Account

      Login

      Statistics

      View Usage StatisticsView Google Analytics Statistics

      Bilkent University

      If you have trouble accessing this page and need to request an alternate format, contact the site administrator. Phone: (312) 290 1771
      © Bilkent University - Library IT

      Contact Us | Send Feedback | Off-Campus Access | Admin | Privacy