활어 개체어의 광대역 음향산란신호로부터 어종식별을 위한 시간-주파수 특징 추출
Time-Frequency Feature Extraction of Broadband Echo Signals from Individual Live Fish for Species Identification
0
조회
0
다운로드
9
인용
0
참고문헌
키워드
초록
Joint time-frequency images of the broadband acoustic echoes of six fish species were obtained using the smoothed pseudo-Wigner-Ville distribution (SPWVD). The acoustic features were extracted by changing the sliced window widths and dividing the time window by a 0.02-ms interval and the frequency window by a 20-kHz bandwidth. The 22 spectrum amplitudes obtained in the time and frequency domains of the SPWVD images were fed as input parameters into an artificial neural network (ANN) to verify the effectiveness for species-dependent features related to fish species identification. The results showed that the time-frequency approach improves the extraction of species-specific features for species identification from broadband echoes, compare with time-only or frequency-only features. The ANN classifier based on these acoustic feature components was correct in approximately 74.5% of the test cases. In the future, the identification rate will be improved using time-frequency images with reduced dimensions of the broadband acoustic echoes as input for the ANN classifier.
Abstract
Joint time-frequency images of the broadband acoustic echoes of six fish species were obtained using the smoothed pseudo-Wigner-Ville distribution (SPWVD). The acoustic features were extracted by changing the sliced window widths and dividing the time window by a 0.02-ms interval and the frequency window by a 20-kHz bandwidth. The 22 spectrum amplitudes obtained in the time and frequency domains of the SPWVD images were fed as input parameters into an artificial neural network (ANN) to verify the effectiveness for species-dependent features related to fish species identification. The results showed that the time-frequency approach improves the extraction of species-specific features for species identification from broadband echoes, compare with time-only or frequency-only features. The ANN classifier based on these acoustic feature components was correct in approximately 74.5% of the test cases. In the future, the identification rate will be improved using time-frequency images with reduced dimensions of the broadband acoustic echoes as input for the ANN classifier.
참고문헌 (17)
- Demuth H, "Neural Network Toolbox ™ 6 User’s Guide", pp.84~226 (2009), The MathWorks Inc
- Dong Y, "Analysis of a new joint time-frequency distribution of suppressing cross-term", Res J Appl Sci Eng Technol, 4, pp.1580~1584 (2012)
- S. M. M. Fässler, "Depth-dependent swimbladder compression in herring Clupea haengus observed using magnetic resonance imaging", Journal of Fish Biology, 74(1), pp.296~303 (2009), Wiley-Blackwell[DOI]
- Foote KG, "Importance of the swimbladder in acoustic scattering by fish: A Comparison of gadoid and mackerel target strengths", J Acoust Soc Am, 67, pp.2084~2089 (1980)
- Gavrovska AM, "Determination of morphologically characteristics PCG segments from spectrogram image", Teflor J, 2, pp.74~77 (2010)
- Han SK, "Efficient radar target recognition using a combination of range profile and time-frequency analysis", Progress Electrom Res, 108, pp.131~141 (2010)
- J JAFFE, "Using multi-angle scattered sound to size fish swimbladders", ICES Journal of Marine Science, 63(8), pp.1397~1404 (2006), Oxford University Press (OUP)[DOI]
- Kuruvilla J, "Lung cancer classification using neural networks for CT images", Computer Methods Programs Biomedicine, 113, pp.202~209 (2014)
- 이대재, "펄스압축기법을 이용한 활어 개체어에 대한 광대역 음향산란신호의 분석 및 식별", 한국수산과학회지, 48(2), pp.207~220 (2015), 한국수산과학회
- 이대재, "고등어( Scomber japonicus ), 불볼락( Sebastes thompsoni ) 및 쥐노래미( Hexagrammos otakii )에 의한 광대역 음향산란신호의 시간-주파수 분석", 한국수산과학회지, 48(2), pp.221~232 (2015), 한국수산과학회
- 이대재, "어류 부레의 형태학적 차이에 따른 음향산란강도의 자세 및 주파수 의존성의 변화", 한국수산과학회지, 48(2), pp.233~243 (2015), 한국수산과학회
- Nesse TL, "Measurement of acoustic-scattering spectra from the whole and pars of Atlantic mackerel", ICES J Mar Sci, 66, pp.1169~1175 (2009)[DOI]
- M. S. Safizadeh, "Time-frequency analysis of pulsed eddy current signals", Journal of Nondestructive Evaluation, 20(2), pp.73~86 (2001), Springer Nature[DOI]
- Shilbayeh NF, "An efficient neural network for recognition gestural Hindi digits", American J Appl Sci, 10, pp.938~951 (2013)
- Shui PL, "Instantaneous frequency estimation based on directionally smoothed pseudo- Wegner-Ville distribution bank", IET Radar Sonar Navig, 1, pp.317~325 (2007)[DOI]
- Stanton TK, "New broadband methods for resonance classification and high-resolution imagery of fish with swimbladders using a modified commercial broadband echosounder", ICES J Mar Sci, 67, pp.365~378 (2010)[DOI]
- Traykovski LVM, "Effect of orientation on broadband acoustic scattering of Atlantic krill Euphausia superb: Implications for inverting zooplankton spectral acoustic signatures for angle of orientation", J Acoust Soc Am, 104, pp.2121~2135 (1998)