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Automated Non-Contact Measurement System for Fish Surface Area and Volume in Industrial Processing Lines
Subject area: Science,Engineering and Technology · Area of research: Industrial Automation & Smart Manufacturing
DOI: https://doi.org/10.64388/IREV10I1-1719575
Abstract
This study presents the development of an automated, non-contact measurement system designed to estimate the surface area and volume of fish within dynamic industrial processing lines. Traditional manual measurement methods are often invasive, time-consuming, and incompatible with high-speed production environments. To overcome these limitations, a computer vision-based system utilizing 3D-coordinate mapping was developed. A significant technical advancement in this research is the integration of a predictive Kalman filter algorithm to stabilize coordinate extraction against mechanical vibrations and motion blur inherent in moving conveyor systems. The methodology involves real-time point cloud reconstruction of the fish geometry, followed by mathematical integration to calculate morphometric parameters. Experimental validation shows that the automated system achieves high precision, with an average error of less than 0.6% compared to the manual partition method. The results demonstrate that the proposed system provides a robust, high-throughput solution for real-time quality control and dosage calculation in the fish processing industry. This work bridges the gap between static laboratory-scale measurements and fully automated industrial applications.
Keywords
Automated Measurement, 3D-Coordinate Mapping, Industrial Conveyor, Kalman Filter, Non-Contact Sensing
How to cite this paper
@article{1719575,
author = {Jotje Rantung, Gideon David Rantung},
title = {Automated Non-Contact Measurement System for Fish Surface Area and Volume in Industrial Processing Lines},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {1},
pages = {698-706},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1719575.pdf},
abstract = {This study presents the development of an automated, non-contact measurement system designed to estimate the surface area and volume of fish within dynamic industrial processing lines. Traditional manual measurement methods are often invasive, time-consuming, and incompatible with high-speed production environments. To overcome these limitations, a computer vision-based system utilizing 3D-coordinate mapping was developed. A significant technical advancement in this research is the integration of a predictive Kalman filter algorithm to stabilize coordinate extraction against mechanical vibrations and motion blur inherent in moving conveyor systems. The methodology involves real-time point cloud reconstruction of the fish geometry, followed by mathematical integration to calculate morphometric parameters. Experimental validation shows that the automated system achieves high precision, with an average error of less than 0.6% compared to the manual partition method. The results demonstrate that the proposed system provides a robust, high-throughput solution for real-time quality control and dosage calculation in the fish processing industry. This work bridges the gap between static laboratory-scale measurements and fully automated industrial applications.},
keywords = {Automated Measurement, 3D-Coordinate Mapping, Industrial Conveyor, Kalman Filter, Non-Contact Sensing},
month = {July},
doi = {https://doi.org/10.64388/IREV10I1-1719575}
}