Applying Depth Estimation in Standardizing Meat Grading

Based on Patent Research | US-10726537-B2 (2020)

Inconsistent meat grading, caused by variable cut surface presentation, creates challenges in food manufacturing. This variability hinders automation and leads to subjective, less accurate quality assessments. Depth Estimation, a computer vision technique, addresses this by precisely determining the 3D position of the cut surface. It ensures consistent alignment for subsequent image capture, providing objective data for improved grading accuracy and operational efficiency.

SOLUTION OVERVIEW

Manual Grading to AI Grading Shift

In food manufacturing, inconsistent meat grading stemming from variable cut surface presentation poses significant challenges to automation and objective quality assessment. Depth Estimation technology directly addresses this by precisely determining the three-dimensional position of each cut surface. This computer vision technique gathers spatial data, then uses it to guide subsequent processes, ensuring consistent alignment of the product for accurate image capture. This crucial step provides the stable input needed for reliable quality evaluation.

This capability streamlines production lines, enabling automation of quality checks that were previously hindered by product variability. Depth Estimation systems can integrate seamlessly, providing real-time positional data to robotic handlers or imaging stations. Consider it like an automated baker's assistant that perfectly positions every loaf of bread for slicing, ensuring uniform cuts regardless of how it arrived. This technology fosters significant operational improvements, optimizes resource utilization, and enhances overall decision-making in meat processing.

HOW IT WORKS

Decoding Meat Depth from Scans

Capturing 3D Spatial Data

The system begins by scanning the meat product using 3D imaging technology. This process gathers detailed spatial data, creating a precise three-dimensional map of the cut surface and its surrounding contours. This initial step provides the raw depth information required for analysis.

Determining Cut Surface Position

Next, the collected 3D spatial data is processed by the Depth Estimation system. It precisely identifies and calculates the exact three-dimensional coordinates and orientation of the cut surface. This crucial analysis pinpoints the surface's position for subsequent actions.

Ensuring Consistent Product Alignment

With the cut surface's precise position known, the system guides automated handlers or imaging stations. This ensures the meat product is consistently aligned and presented in a uniform manner for the next process. This step eliminates variability in product presentation, a key challenge in food manufacturing.

Capturing Standardized Quality Images

Once the product is perfectly aligned, a high-resolution 2D image of the cut surface is captured. This standardized image provides consistent, objective input for quality assessment and grading algorithms. The reliable image capture enables accurate and automated evaluations.

Potential Benefits

Improved Grading Accuracy

Depth Estimation ensures consistent product alignment for imaging, eliminating variability and providing objective data. This leads to more precise and reliable meat quality assessments.

Enhanced Automation Potential

By precisely positioning products, this technology removes a major barrier to automating quality checks. It enables seamless integration of robotic handlers and imaging systems.

Streamlined Production Workflows

Consistent input from Depth Estimation reduces manual intervention and rework, accelerating processing lines. This optimizes resource utilization and increases throughput.

Objective Quality Insights

The system provides stable, objective data for quality evaluation, moving beyond subjective assessments. This empowers better decision-making for process improvements in food manufacturing.

Implementation

1 Install Imaging Hardware. Mount 3D sensors and 2D cameras on the production line. Ensure stable power and network connectivity for data capture.

2 Calibrate Depth System. Perform initial calibration of 3D sensors to accurately capture meat product dimensions and surface contours.

3 Configure Processing Logic. Set up the depth estimation algorithms to precisely identify and calculate the cut surface's 3D position.

4 Integrate Alignment Control. Connect the depth system's positional data to automated handlers or imaging stations for consistent product alignment.

5 Validate System Performance. Test the end-to-end system to confirm accurate alignment and standardized 2D image capture for quality assessment.

Source: Analysis based on Patent US-10726537-B2 "Image acquisition for meat grading" (Filed: July 2020).