# Underwater Weight Estimation of Three Sea Cucumber Species in Culture Tanks Using Image Analysis and ArUco Markers

## TL;DR

Researchers developed a non-invasive method to estimate the weight of sea cucumbers using photos and ArUco markers, avoiding the need to handle them and reducing stress.

## Contribution

A novel, accurate, and non-invasive image-based weight estimation method for sea cucumbers using ArUco markers is introduced.

## Key findings

- The method achieved high accuracy with R2 values of 0.9699 to 0.9882 for three sea cucumber species.
- Image-based weight estimates showed no significant difference from traditional measurements (p > 0.05).
- The technique is cost-effective, simple, and adaptable for other aquatic species.

## Abstract

Sea cucumbers are ecologically important in marine ecosystems, and some species are valuable for trade. Studying their growth is important, but measuring them is difficult because they shrink and lose weight when touched. This study tested a new way to estimate their weight using photos and ArUco markers instead of handling them. The method was tested on three sea cucumber species found in Thailand: black sea cucumber, pink warty sea cucumber, and sand fish. The results showed that this technique is very accurate. This approach can help study their growth without causing stress and may also be useful for other animals. However, challenges include shadows, water clarity, and objects that look similar to sea cucumbers.

Sea cucumbers play a vital role in marine and coastal ecosystems, with some species holding significant economic value. Accurate growth assessment, particularly weight estimation, is crucial for their management and conservation. However, direct measurement poses challenges, as sea cucumbers expel internal fluids when handled, altering their body size and weight. This study evaluates the effectiveness of image analysis combined with ArUco markers to estimate the weight of three economically and ecologically important sea cucumber species found in Thailand: black sea cucumber (Holothuria leucospilota), pink warty sea cucumber (Cercodemas anceps), and sandfish (Holothuria scabra). The proposed method demonstrated high accuracy, with R2 values of 0.9699, 0.9774, and 0.9882, respectively. Furthermore, no significant differences (p > 0.05) were observed between traditional hand measurements and image-based assessments, with relative errors of 7.71 ± 4.30% for black sea cucumber, 5.06 ± 3.37% for pink warty sea cucumber, and 4.50 ± 3.23% for sandfish. Unlike deep learning, which requires large datasets and high computation, this simple, cost-effective, and adaptable method highlights the potential of image analysis combined with ArUco markers as a non-invasive and accurate tool for estimating sea cucumber weight. This approach minimizes stress on the animals and can be extended to other aquatic species. However, challenges such as shadows, water turbidity, and the presence of similarly shaped objects near sea cucumbers should be considered when applying this technique in field conditions.