Stereo Vision Fish Biomass Estimation Without Manual Weighing
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Solution Overview
Problem
Manual processes for estimating fish size and weight are time-consuming, inaccurate, and require substantial financial, logistical, and human resources.
Innovation Solution
Utilizing stereo cameras to capture off-axis images of fish, processing them to generate 2-D or 3-D models, and applying regression models or neural networks to determine biomass, shape, size, or health, with image enhancement and object detection to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processes are used to catch and weigh fish samples, then fish size and weight can be estimated, but the process becomes time-consuming and requires substantial human resources
Solution Approach 1:
The patent replaces manual mechanical processes (catching and weighing fish by hand) with an automated image-based measurement system. Cameras capture images of fish, and computer vision algorithms automatically measure fish length and estimate weight, eliminating the need for manual handling and weighing while maintaining measurement accuracy.
Solution Approach 2:
The patent creates digital copies (images) of fish instead of physically handling them. By capturing images and using image analysis to measure fish dimensions and estimate weight, the system avoids the time-consuming manual process while preserving measurement capability.
2Measurement precision
If manual processes are used to catch and weigh fish samples, then fish characteristics can be determined, but substantial financial and logistical resources are required
Solution Approach 1:
The patent replaces complex manual operations (catching, handling, weighing) with a simplified automated system using cameras and image processing software. This reduces the need for human resources and logistical support while maintaining the ability to determine fish characteristics.
Solution Approach 2:
The system performs measurements and estimations automatically without human intervention. The image processing algorithms self-analyze the captured images to extract fish measurements and weight estimates, eliminating the need for manual processing and reducing resource requirements.
3Productivity
If stereo cameras and image processing are used, then accurate fish characteristics can be determined efficiently, but the system complexity increases
Solution Approach 1:
The patent uses a multi-functional system where stereo cameras capture images, and the same image processing pipeline performs multiple tasks including fish detection, key point identification, length measurement, and weight estimation. This consolidates multiple functions into a single integrated system, managing complexity while maintaining high productivity.
Solution Approach 2:
The patent transitions from 2D images to 3D measurements by using stereo vision to estimate fish weight based on measured length and volumetric relationships. This dimensional approach enables accurate weight estimation without physical weighing, improving productivity while the software handles the computational complexity.
Data Source
AI summary
Methods, systems, and apparatuses, including computer programs encoded on a computer-readable storage medium for estimating the shape, size, mass, and health of fish are described. A pair of stereo cameras may be utilized to obtain off-axis images of fish in a defined area. The images may be processed, enhanced, and combined. Object detection may be used to detect and track a fish in images. A pose estimator may be used to determine key points and features of the detected fish. Based on the key points, a model of the fish is generated that provides an estimate of the size and shape of the fish. A regression model or neural network model can be applied to the fish model to determine characteristics of the fish.