An Automated Fish Counting Algorithm in Aquaculture Based on Image Processing

DOI

10.2991/ifmca-16.2017.56How to use a DOI?

Keywords

Fish Counting; Free-swimming; Overlap; Skeleton Extraction

Abstract

A new algorithm based on endpoints of skeleton is presented to efficiently get the number of fish in this paper. Considering the complexity of underwater environment like lack of light, this paper presents an improved adaptive thresholding method to segment the fish image better. In addition, the object of our research is free-swimming fish. The overlapped fish in the image makes the counting result inaccurate often. So after segmentation and morphological processing, this paper adopts image thinning method to extract the skeleton of fish. After that, we get the fish number according to the number of corresponding endpoints in the image. The experimental results show that the method can accurately count the fish population even under high overlapped degree.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jiuyi Le
AU  - Lihong Xu
PY  - 2017/03
DA  - 2017/03
TI  - An Automated Fish Counting Algorithm in Aquaculture Based on Image Processing
BT  - Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
PB  - Atlantis Press
SP  - 358
EP  - 366
SN  - 2352-5401
UR  - https://doi.org/10.2991/ifmca-16.2017.56
DO  - 10.2991/ifmca-16.2017.56
ID  - Le2017/03
ER  -