Fish recognition method using vector quantization histogram for investigation of fishery resources

Author

Nishida, Yoshiharu ; Ura, Tamaki ; Hamatsu, Tomonori ; Nagahashi, Kenji ; Inaba, Shogo ; Nakatani, Takeshi

Author_Institution

Inst. of Ind. Sci., Univ. of Tokyo, Tokyo, Japan

fYear

2014

fDate

14-19 Sept. 2014

Firstpage

1

Lastpage

5

Abstract

This paper proposed a novel approach to the kichiji rockfish recognition method for investigation of the fish biomass. This method does not depend on the size, position and attitude of the fish, because SIFT feature with rotation invariant is used and is represented by vector quantization histogram. The experiment results showed that our method detected 94 % of object which is the fish from 37 photographs and recognized 57 % of the fish from detected image. And our method was able to recognize kichiji rockfish from SIFT features of the fish head. However, if more than one object is piled up, our method is a possibility of mistaken recognition because features of object other than target are used for recognition.

Keywords

aquaculture; autonomous aerial vehicles; image recognition; object detection; transforms; vector quantisation; SIFT feature; fish attitude; fish biomass; fish head; fish position; fish recognition method; fish size; fishery resources; image detection; kichiji rockfish recognition method; photographs; rotation invariant; vector quantization histogram; Biomass; Feature extraction; Histograms; Image color analysis; Marine animals; Vector quantization; Visualization; AUV; biomass invesitigation; fish recognition method; kithicji rockfish;

fLanguage

English

Publisher

ieee

Conference_Titel

Oceans - St. John's, 2014

Conference_Location

St. John´s, NL

Print_ISBN

978-1-4799-4920-5

Type

conf

DOI

10.1109/OCEANS.2014.7003268

Filename

7003268