Image Analysis Fire Detection Using Focus Data
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Solution Overview
Problem
Existing fire detection methods using infrared cameras face challenges in early fire detection due to heavy smoke interference and require IR filters, which affect color reproducibility and are costly to install.
Innovation Solution
An event detection system and method using image analysis that comprehensively determines edge signals, brightness, and color data to detect smoke and fire by analyzing photographed images, adapting to different fire conditions and generating specific alarm signals based on focus data, brightness, and motion data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If infrared (IR) signals are used for fire detection, then fire detection capability is improved, but color reproducibility deteriorates and installation cost increases due to requiring IR filters
Solution Approach 1:
The patent extracts and removes the IR filter component from the detection system. Instead of using IR signals that require filters, the invention uses visible light signals captured by a standard camera sensor, thereby eliminating the need for expensive IR filters and complex installation while maintaining fire detection capability through analysis of smoke and flame characteristics in the visible spectrum
Solution Approach 2:
The patent creates a copy of fire detection functionality using standard visible light imaging instead of specialized IR imaging. By capturing and analyzing visible light images of smoke and flame, the system replicates fire detection capability without requiring expensive IR camera hardware, thus reducing installation cost and device complexity
2Reliability
If infrared (IR) signals are used for fire detection, then fire detection capability is improved, but the system cannot detect early stage fires due to heavy smoke interference
Solution Approach 1:
The patent segments the fire detection process into multiple analysis dimensions: edge signal analysis to detect smoke boundaries, brightness analysis to identify flame intensity changes, and color analysis to distinguish flame colors. This multi-faceted approach allows the system to detect early stage fires by analyzing subtle changes in smoke edges and brightness that would be imperceptible in traditional IR imaging, thereby improving early detection accuracy
Solution Approach 2:
The patent utilizes color change analysis of smoke and flame in the visible spectrum to detect early stage fires. By monitoring changes in color intensity, hue, and saturation of smoke particles and emerging flames, the system can identify early fire conditions before heavy smoke obscures the view, overcoming the limitation of IR systems that struggle with early detection through smoke
3Measurement precision
If comprehensive image analysis including edge signals, brightness, and color data is performed, then detection accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent divides the image analysis process into three independent modular components: edge signal extraction module, brightness analysis module, and color data analysis module. Each module processes specific features separately and their results are integrated for final detection. This segmentation allows comprehensive analysis while maintaining manageable processing complexity through modular design and independent optimization of each analysis component
Data Source
AI summary
Provided is an event detection system including an image acquisition unit that acquires an image of a predetermined region, an image analysis unit that obtains focus data including a focus distance and a focus gain of the acquired image, an event occurrence determination unit that determines based on the focus data whether an event has occurred, and an alarm generation unit that generates an alarm signal according to an event signal transmitted from the event occurrence determination unit.