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Related Experiment Video

Updated: Jun 8, 2025

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Published on: March 6, 2014

A comprehensive annotated image dataset for real-time fish detection in pond settings.

Vijayalakshmi M¹, Sasithradevi A²

¹School of Electronics Engineering, Vellore Institute of Technology, Kelambakkam-vandalur road, Chennai 600127, India.

|November 4, 2024

Summary

This study introduces a new fish detection dataset for aquaculture, focusing on Orange Chromide fish in Tamil Nadu ponds. The dataset aids in developing non-invasive fish monitoring systems for small-scale industries.

Keywords:

Annotated images Detection Fish Growth level monitor Non-invasive analysis

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Area of Science:

Aquaculture
Computer Vision
Marine Biology

Background:

Fish are crucial for global food security and economies, especially in Tamil Nadu.
Aquaculture practices require efficient, non-invasive monitoring tools for small-scale industries.

Purpose of the Study:

To develop an efficient fish detection system for pond environments.
To facilitate fish classification and growth monitoring in aquaculture.
To create a valuable dataset for automated underwater image analysis.

Main Methods:

Collected underwater video footage of Orange Chromide fish (Etroplus maculatus) in Retteri Pond, Chennai.
Converted video to 2D images and manually annotated them using the Roboflow tool.
Captured data under challenging conditions: occlusion, turbid water, high density, and varying light.

Main Results:

A meticulously annotated dataset of Orange Chromide fish images.
The dataset addresses common computer vision challenges in underwater imagery.
Provides a resource for developing automated fish detection and monitoring tools.

Conclusions:

The annotated dataset is a valuable resource for aquaculture, marine biology, and computer vision research.
Enables the development of non-invasive automated systems for fish management.
Supports advancements in small-scale aquaculture through enhanced monitoring capabilities.