Multidimensional Meat Imaging for Consistent Automated Grading
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Solution Overview
Problem
The existing meat grading processes rely heavily on manual operations, leading to high labor costs and inconsistent grading results due to variations in worker skill and experience, affecting accuracy and stability.
Innovation Solution
A meat grading method and system that utilizes multi-dimensional imaging and high-precision measurement to train a grading indicator parameter model, enabling automated and accurate grading by calculating grading indicator parameters based on morphological, structural, and composition information of meat pieces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual operations are used for meat grading, then workers can perform grading based on experience and observation, but labor costs increase and grading consistency deteriorates
Solution Approach 1:
The patent replaces the manual mechanical grading system with an automated imaging and measurement system. Multi-dimensional imaging devices capture meat carcass data, and measurement systems automatically calculate grading parameters, eliminating reliance on human workers' subjective judgment and experience while ensuring consistent, objective grading results.
Solution Approach 2:
The patent creates digital copies of the meat carcass through multi-dimensional imaging. These digital models serve as replicas that can be measured and analyzed without physical contact, allowing the grading process to work with copied data rather than requiring direct manual measurement of the actual meat, thereby improving both efficiency and consistency.
2Adaptability or versatility
If manual grading is performed, then flexibility in judgment is maintained, but measurement precision and accuracy deteriorate
Solution Approach 1:
The patent substitutes manual measurement tools and human judgment with automated imaging devices and computational algorithms. These systems provide precise, objective measurements of meat dimensions and characteristics, eliminating the imprecision inherent in manual methods while maintaining adaptability through programmable grading criteria.
Solution Approach 2:
The patent transitions from two-dimensional visual inspection to multi-dimensional imaging and measurement. By capturing depth, volume, and spatial relationships in addition to surface characteristics, the system achieves superior measurement precision while maintaining the flexibility to evaluate multiple grading parameters simultaneously.
3Reliability
If highly skilled workers are employed for grading, then grading quality improves, but labor costs increase
Solution Approach 1:
The patent replaces skilled human workers with automated measurement and imaging systems. These systems perform grading operations without requiring human expertise, thereby eliminating the need to pay premium wages for skilled labor while maintaining or improving grading quality through consistent, objective measurement.
Solution Approach 2:
The patent enables the meat grading system to perform its own measurement and evaluation functions autonomously. The imaging devices and measurement systems self-calibrate and self-evaluate according to programmed criteria, eliminating the need for human operators and associated labor costs while maintaining high grading quality.
Data Source
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AI summary
The present disclosure provides a meat grading method and a meat grading system. The method includes: acquiring a multi-dimensional meat imaging information of a meat piece; performing a high-precision measurement on the meat piece to acquire grading true value data of the meat piece; calculating a grading indicator parameter calculation value based on the multi-dimensional meat imaging information, and training a grading indicator parameter model based on the grading indicator parameter calculation value and the grading true value data to acquire a trained grading indicator parameter model.