Real-Time Blood Detection via Color Probability Analysis
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Solution Overview
Problem
Current endoscopic and laparoscopic imaging systems face challenges with low-quality images due to exposure issues, insufficient light, and bodily fluids, which can lead to missed problems during surgery, necessitating a real-time blood detection solution.
Innovation Solution
A blood detection system that uses a camera and processing unit to extract image blocks and calculate blood probability through red color dominance, deviation, and colorfulness probabilities, enabling real-time detection without processor-intensive operations like segmentation or edge detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image processing methods (segmentation, edge detection) are used for blood detection, then detection accuracy may be improved, but processing time increases and real-time detection becomes difficult
Solution Approach 1:
The patent extracts only the essential color information (red color dominance, deviation, and colorfulness) from the image data, ignoring other complex features. This extraction approach enables real-time processing by focusing only on the most relevant characteristics for blood detection, achieving near-instant detection without processor-intensive operations.
Solution Approach 2:
The patent changes the detection parameters from complex image processing metrics to simple color-based parameters (red color dominance, red color deviation, red color colorfulness). This parameter transformation allows the system to achieve both high detection accuracy and real-time performance by using computationally efficient color space calculations instead of traditional segmentation and edge detection algorithms.
2Measurement precision
If complex image processing algorithms are applied, then detection precision may improve, but device complexity and computational requirements increase
Solution Approach 1:
The patent uses simple, computationally inexpensive color probability calculations instead of complex algorithms. These lightweight computational operations can be performed rapidly with minimal processing power, making the system suitable for real-time implementation in resource-constrained environments while maintaining effective blood detection capability.
3Productivity
If real-time detection is implemented using simple color analysis, then processing speed improves, but detection reliability may be affected by image quality issues
Solution Approach 1:
The patent applies different color probability calculations to different regions of the image (image blocks), allowing the system to adapt to local variations in lighting and image quality. By analyzing red color dominance, deviation, and colorfulness in each local region independently, the system maintains detection reliability even when overall image quality is compromised by exposure issues or insufficient light.
Data Source
AI summary
A blood detection system, and a method of operation thereof, including: a camera for obtaining an input image frame; and a processing unit connected to the camera, the processing unit including: an image block module for extracting image blocks from the input image frame, and an automatic blood detection module, coupled to the image block module, for calculating an overall blood probability of the image blocks including: determining a red color dominance probability, determining a red color deviation probability, and determining a red color colorfulness probability.