Machine-Readable Code Decoding Under Blood Occlusion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional image processing techniques for machine-readable codes, such as QR codes, fail to accurately interpret obscured codes due to substances like blood, leading to inaccurate counting of surgical textiles during medical procedures.
Innovation Solution
A method and system that adjusts the color space of an image to isolate the predominant color of the obscuring substance, locates the machine-readable code region, and binarizes it to enhance decoding, using techniques like corner detection and neural networks to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing techniques are used to read machine-readable codes, then the process is simple and fast, but the accuracy deteriorates when the code is obscured by substances like blood
Solution Approach 1:
The image processing is divided into distinct segments: initial image acquisition, color space adjustment to isolate the predominant color of the obscuring substance, binarization of the machine-readable code region, and decoding. This segmentation allows each step to be optimized independently, improving decoding accuracy while managing complexity through modular processing
Solution Approach 2:
Before attempting to decode the obscured machine-readable code, the system performs preliminary color space adjustment to isolate the predominant color of the obscuring substance and applies binarization to the code region. These preliminary actions enhance the contrast and clarity of the code elements before decoding, thereby improving accuracy without requiring complex real-time processing during decoding
2Measurement precision
If color space adjustment and binarization are applied to isolate obscuring substances, then decoding accuracy improves, but processing time increases
Solution Approach 1:
Instead of processing the entire image uniformly, the system applies color space adjustment and binarization specifically to the machine-readable code region after locating it. This localized processing approach maintains high decoding accuracy while minimizing the amount of data that requires intensive processing, thereby reducing overall processing time
Solution Approach 2:
The system dynamically adjusts image processing parameters based on the detected predominant color of the obscuring substance. By changing the color space parameters to isolate the specific color of the obscuring material, the system enhances code visibility efficiently without requiring exhaustive processing of all possible color variations, thus balancing accuracy and processing speed
Data Source
AI summary
Systems and methods for processing an image of a machine-readable code. The method includes accessing an image of a machine-readable code comprising coded information, wherein the machine-readable code is at least partially obscured, occluded, false, or blurry. The image is refined by a trained neural network to render the machine-readable code locatable. An adjusted image may be generated in which the orientation of the machine-readable code is refined. The coded information is decoded, and fluid-related information may be displayed based on the decoded information. The decoded information may be unique to the item to which the machine-readable code is affixed. Other apparatus and methods are also described.