Spectral Image Analysis for Foreign Matter Detection in Liquid Products
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Solution Overview
Problem
Current methods for detecting foreign matter in liquid products are resource-intensive and time-consuming, requiring extensive inspection and scanning from multiple angles, which increases costs and inefficiencies.
Innovation Solution
A foreign matter management system utilizing a spectral camera, processor, and memory to acquire spectral images, calculate relationship matrices, and determine the presence of foreign matter through data cubes and machine learning models, enabling efficient detection by analyzing pixel values and similarities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple scanning methods and inspectors are used to detect foreign matter, then detection accuracy is improved, but time consumption and cost increase
Solution Approach 1:
The patent segments the inspection process by dividing the liquid product container into multiple regions of interest (ROIs) and assigning different scanning methods to different regions. Critical regions receive more thorough inspection while less critical regions use faster methods, thereby maintaining detection accuracy while reducing overall inspection time.
Solution Approach 2:
The patent applies partial inspection strategies where not all regions undergo the same level of scanning. Instead, the system performs excessive inspection (multiple scanning angles and methods) only on regions with higher foreign matter risk, while using minimal inspection on other regions, thus optimizing the balance between accuracy and time efficiency.
2Measurement precision
If multiple scanning methods and inspectors are used to detect foreign matter, then detection accuracy is improved, but cost increases
Solution Approach 1:
The patent segments the inspection resources and assigns them strategically to different regions of the liquid product. By dividing the container into multiple ROIs and applying appropriate scanning methods to each, the system avoids deploying all inspection resources to every region, thereby reducing overall resource consumption while maintaining detection accuracy.
Solution Approach 2:
The patent changes the inspection parameters (scanning method, number of inspectors, scanning angles) based on the specific characteristics of different regions. This adaptive approach ensures that resources are used efficiently - applying high-resource methods only where necessary and low-resource methods where sufficient - thus reducing total resource consumption while maintaining detection accuracy.
3Reliability
If extensive inspection from various angles is performed, then foreign matter detection capability is improved, but device complexity and resource requirements increase
Solution Approach 1:
The patent segments the inspection task into multiple regions of interest, each with specific scanning requirements. This segmentation allows the system to apply complex multi-angle scanning only to regions where it is most beneficial, while using simpler scanning methods in other regions, thereby reducing overall system complexity while maintaining detection capability.
Solution Approach 2:
The patent implements a dynamic inspection strategy where the scanning method and number of angles are adjusted based on the specific region being inspected and the detected risk level. This dynamic approach allows the system to use simple scanning for low-risk regions and complex scanning only when necessary, reducing the average device complexity while maintaining high reliability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides accurate and efficient detection of foreign matter in liquid products, reducing the need for extensive manual inspection and lowering costs by automating the process with advanced image analysis and machine learning techniques.
Implementation Method 1
a spectral camera acquiring a spectral image of a liquid product including a liquid substance injected therein
Data Source
AI summary
Embodiments relate to acquiring a spectral image of a liquid product including a liquid substance injected therein. A data cube corresponding to the spectral image captured for the liquid substance of the liquid product is acquired. The data cube may be divided into windows of a predetermined size. A current relationship matrix indicating a relationship between pixel values included in the divided windows is obtained. Whether the liquid product contains a foreign matter is determined, based on the current relationship matrix.