Automated Meat Assessment on Carcasses Using Machine Vision
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Solution Overview
Problem
Current methods for determining the amount of meat remaining on animal carcasses are inefficient, leading to waste and reduced production yields, as they rely on manual measurements and are not capable of real-time, accurate assessment.
Innovation Solution
An automated process using machine vision software to generate and process image data from cameras, identifying meat remaining on carcasses by pixel count within specific value ranges, and correlating this data with weight using look-up tables and equations developed from reference images, allowing for precise measurement without interrupting the processing line.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual measurement methods are used to determine meat remaining on carcasses, then the process can be performed with simple equipment, but the measurement precision and productivity are insufficient
Solution Approach 1:
The patent replaces manual mechanical measurement systems with an automated machine vision system using cameras and image processing software. The system captures images of carcasses, processes them through algorithms that identify meat tissue based on color and texture characteristics, and automatically calculates the amount of meat remaining. This substitution of mechanical/manual operations with automated optical detection and computational analysis simultaneously improves both measurement precision and productivity.
2Measurement precision
If manual scraping and weighing of meat is performed, then the measurement can be obtained, but the process requires interruption of the processing line and significant time consumption
Solution Approach 1:
The system performs preliminary actions by capturing images of carcasses as they move through the processing line, before any meat removal operations are completed. The machine vision system processes these images in real-time or near real-time, determining the amount of meat remaining without requiring the line to stop. This eliminates the time loss associated with stopping the line for manual scraping and weighing, while maintaining measurement accuracy through automated image analysis.
3Productivity
If random sampling is used to assess meat remaining, then the measurement process is faster, but the reliability and representativeness of the data are reduced
Solution Approach 1:
The machine vision system provides universal measurement capability that can assess every carcass passing through the processing line, not just random samples. The system is designed to handle continuous streams of carcasses, capturing and analyzing images of each one. This universal application of the measurement system across the entire population of carcasses eliminates sampling errors and provides reliable, representative data for all products, while maintaining high productivity through automated processing.
4Productivity
If automated machinery is used for meat removal, then the productivity increases, but the amount of meat remaining on carcasses is not accurately monitored
Solution Approach 1:
The patent implements a feedback system where the machine vision continuously monitors the amount of meat remaining on carcasses after automated removal operations. The system provides real-time or near real-time data about trimming effectiveness, which can be fed back to operators or control systems. This feedback loop enables continuous optimization of the automated meat removal process, ensuring that productivity gains do not come at the cost of leaving excessive meat on carcasses, thereby preventing loss of valuable product information.
Data Source
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AI summary
An automated process assesses an amount of meat remaining on a trimmed animal carcass by generating image data of the carcass and processing the image data in a computer to calculate the amount of meat remaining on the carcass. The automated process can be carried out using an equation developed by counting pixels in an area of interest in images of a plurality of reference trimmed carcasses from which the remaining meat is thereafter scraped and weighed, to produce data points used to develop the equation which is then used to calculate the amount of meat remaining on a trimmed carcass as it proceeds down a processing line.