Paper Abstract and Keywords |
Presentation |
2014-09-01 15:50
Fish species classification by the support vector machine Atsushi Kinjo, Masanori Ito, Ikuo Matsuo (Tohoku Gakuin Univ.), Tomohito Imaizumi, Tomonari Akamatsu (FRA-NRI) PRMU2014-45 IBISML2014-26 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Fish species classification using echo-sounder is important for fisheries. With school of mixed species, it is necessary to extract individual fish echoes and to classify individual fish species from echoes. A broadband signal, which offered the advantage of high range resolution, was applied to detect individual fish for this purpose. The positions of fish were estimated from the time difference of arrivals by using the split-beam system. The target strength (TS) spectrum of individual fish echo was computed from the isolated echo and the estimated position. In this paper, the Support Vector Machine was introduced to classify fish species by using these TS spectra. In addition, it is well known that the TS spectra are dependent on not only fish species but also fish size. Therefore, it is necessary to classify both fish species and size by using these features. We tried to classify two species and two sizes of schools. Subject species were chub mackerel (Scomber japonicas) and Japanese jack mackerel (Trachurus japonicus). We calculated the classification rates. The fish species and size classification rate was about 67%. And, the fish species classification rate was about 80%. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Fish species and size classification / Support Vector Machine / Target strength spectra / Broad-band split beam / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 114, no. 198, IBISML2014-26, pp. 57-62, Sept. 2014. |
Paper # |
IBISML2014-26 |
Date of Issue |
2014-08-25 (PRMU, IBISML) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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PRMU2014-45 IBISML2014-26 |
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