Stereo Wound Imaging for Marker-Free Depth Measurement
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Solution Overview
Problem
Existing wound imaging and measurement systems face challenges in accurately determining distance and depth without using fiducial markers or complex light patterns, which can lead to contamination and measurement errors, especially in clinical settings.
Innovation Solution
A portable handheld system with two camera sensors captures primary and secondary images, calculates parallax values to determine pixel shift, and computes depth data without requiring fiducial markers or direct contact, using stereoscopic imaging for accurate wound measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fiducial markers are used for reference scale, then measurement reference is provided, but contamination risk and measurement accuracy deteriorate
Solution Approach 1:
The patent removes fiducial markers from the measurement system entirely, extracting the harmful element that caused contamination. Instead of using external reference markers placed on or near the wound, the system uses the wound edges themselves as the reference scale through edge detection algorithms, eliminating the source of contamination while maintaining measurement accuracy.
Solution Approach 2:
The measurement system uses the wound itself as the reference scale rather than requiring external fiducial markers. The wound edges automatically provide the reference information needed for accurate measurement through image processing algorithms that detect and measure the wound boundaries directly from the captured image.
2Measurement precision
If fiducial markers are placed close to wound, then measurement accuracy improves, but contamination risk and detection errors increase
Solution Approach 1:
The system extracts and eliminates the need for fiducial markers that caused detection reliability issues. By removing these external markers and using the wound edges themselves as the reference, the system avoids shadows, lighting variations, and visual confusion that compromised detection reliability.
Solution Approach 2:
The system creates a homogeneous measurement approach where the same image processing algorithms are used to detect both the wound edges and the reference scale. This uniformity in detection methodology eliminates the reliability issues that arose from having separate detection systems for markers and wound boundaries.
3Measurement precision
If structured light pattern is projected, then depth measurement is enabled, but system complexity and cost increase
Solution Approach 1:
The patent replaces complex mechanical/optical structured light projection systems with a simpler computational approach. Instead of projecting physical light patterns and using complex optical setups to measure depth, the system uses standard imaging combined with edge detection and geometric calculations to achieve depth and dimension measurements.
Solution Approach 2:
The system introduces image processing algorithms as an intermediary between the captured image and the measurement result. These computational mediators extract depth and dimensional information from standard 2D images through edge detection and geometric relationships, eliminating the need for complex optical intermediaries like structured light projectors.
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 precise measurement of wound size, area, and depth without contamination risks, enhancing clinical efficiency and reducing errors by employing stereoscopic imaging and parallax calculations.
Implementation Method 1
calculates parallax values to determine pixel shift
Data Source
AI summary
A portable, handheld system for target measurement is provided. The system comprises an imaging assembly comprising two cameras, separated by a fixed distance, and a processor coupled to the imaging assembly. The processor activates the imaging assembly to capture two images of the target by using the two cameras. The processor further partitions the two acquired images of the target into image elements and analyzes image elements to determine a pixel shift value between corresponding image elements in the two images. Next, the processor calculates a parallax value between the corresponding image elements by using the determined pixel shift value and computes measurement data, such as depth, based on the calculated parallax value to output the measurement data to a display of the imaging system.