Machine Vision Counting for Medication Units
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Solution Overview
Problem
Current counting systems in pharmacies, such as manual counting, weighing scales, and optical beam pour through systems, face challenges like slowness, inaccuracy, and inability to detect damaged units, leading to a need for a more efficient and accurate method that integrates unit detection with control and message management.
Innovation Solution
A machine-vision-based counting system that uses image acquisition and processing to count medication units on a tray, distinguishing them from the background and generating annotated images with sequential numbers, thereby improving accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual counting is used, then flexibility and adaptability are maintained, but productivity is low and time consumption is high
Solution Approach 1:
The patent replaces manual mechanical counting with an automated optical imaging system. A camera captures images of medication units on a tray, and image processing algorithms automatically count and identify the units, eliminating the need for manual visual inspection and counting while significantly improving productivity
Solution Approach 2:
The system creates digital copies (images) of the physical medication units on the tray. These image copies are then processed computationally to count and identify units, allowing the system to analyze multiple units simultaneously without physical contact or manual handling
2Productivity
If weighing scales are used, then productivity increases, but measurement precision deteriorates due to sample-to-sample weight variations
Solution Approach 1:
The patent replaces weight-based measurement with optical imaging and image processing. Instead of measuring the weight of medication units and calculating counts based on average weight, the system directly images and counts individual units, eliminating errors from weight variations, moisture content, and packaging differences
Solution Approach 2:
The system creates visual copies of each medication unit through imaging, allowing direct visual counting rather than indirect weight-based calculation. This enables precise counting of individual units regardless of their weight variations
3Productivity
If optical beam pour through systems are used, then productivity increases, but reliability decreases due to inability to detect damaged units
Solution Approach 1:
The patent segments the counting function into two independent components: quantity counting and quality inspection. The image processing system can count units while simultaneously analyzing their visual characteristics to detect defects, chips, or damage, providing both productivity and reliability
Solution Approach 2:
The imaging system performs multiple functions simultaneously: counting units, identifying individual units, detecting defects, and verifying unit integrity. This multi-functional approach eliminates the trade-off between speed and defect detection capability
4Measurement precision
If pour through optical systems are used, then measurement precision is maintained, but loss of time increases due to manual intervention requirements
Solution Approach 1:
The system performs self-verification through automated image analysis. It automatically counts units, detects potential issues, and provides confidence metrics without requiring manual verification or rerunning of counts, eliminating time loss from manual intervention
Solution Approach 2:
The system provides immediate feedback through annotated images showing counted units, detected defects, and confidence levels. This real-time feedback eliminates the need for manual verification and rerunning of counts by providing transparent, auditable results
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 enhances counting performance by providing accurate, fast, and automated unit detection, reducing human error and improving the overall counting process in pharmacies.
Implementation Method 1
an image acquisition component configured to generate image data responsive to an application of light to the tray. The application of light may distinguish a background field from a plurality of the units disposed on the tray
Data Source
AI summary
A method of processing graphical image data representing optically scanned medication-related units may include receiving image data generated responsive to an application of light to a tray disposed a distance from an image acquisition component. The application of light may distinguish a background field from a plurality of the units disposed on the tray. The method may further include processing the image data to identify objects that correspond to respective ones of the units from the background field, counting the objects identified as corresponding to respective ones of the units, and generating an annotated image including at least a sequential number associated each one of the objects identified as corresponding to respective ones of the units.