Flame Detection Using Color and Flicker Analysis
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Solution Overview
Problem
Conventional flame detection methods in large and complex structures suffer from low accuracy and high false alarm rates due to the limitations of the RGB color model and reliance on motion and color recognition alone, leading to delayed fire detection and control.
Innovation Solution
The method employs a flame detecting device that captures images, analyzes color models using 3D RGB and YUV Gaussian mixture models, and analyzes flickering frequencies with Time Wavelet Transform, combined with centroid and area variation analysis to accurately identify flames, reducing false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional RGB color model and motion detection are used for flame recognition, then the detection system is simple to implement, but the recognition accuracy is low and false alarm rate is high
Solution Approach 1:
The patent transforms the color analysis from conventional RGB space to HSV color space, changing the parameter representation. This allows separate analysis of hue, saturation, and value components, improving flame recognition accuracy by focusing on the characteristic yellow-red hue range (30-70 degrees) while filtering out false alarms from other colored objects
Solution Approach 2:
The detection algorithm is segmented into multiple independent modules: motion detection module, color model analysis module, and flickering frequency analysis module. Each module processes specific features independently, then results are combined for final flame determination. This modular approach improves accuracy while maintaining implementation feasibility
2Reliability
If only motion detection and color model recognition are used, then the detection process is fast, but misrecognition occurs frequently causing incorrect identification
Solution Approach 1:
The patent introduces flickering frequency analysis by capturing multiple consecutive images and analyzing the periodic variation of flame characteristics. Flame objects exhibit characteristic flickering patterns (typically 1-10 Hz) that distinguish them from static or uniformly moving objects, significantly improving detection reliability without requiring excessive processing time
Solution Approach 2:
The patent introduces an intermediate analysis step that combines motion detection results with color model analysis before final flame determination. This intermediary verification layer filters out false positives from motion detection alone and reduces misrecognition, improving reliability while maintaining acceptable detection speed
3Measurement precision
If conventional fire fighting facilities are used in large and complex structures, then the facility structure is simple, but the fire detection and control effectiveness is reduced
Solution Approach 1:
The detection system is designed to be universally applicable across different monitored areas by analyzing intrinsic flame characteristics (color hue, flickering frequency, motion patterns) rather than relying on area-specific features. This allows the same algorithm to effectively detect flames in various environments including large halls, complex structures, and different lighting conditions, maintaining high detection accuracy across expanded coverage areas
Data Source
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AI summary
A flame detecting method and device are provided to improve the accuracy of flame detection and reduce the possibilities of the false fire alarm. The flame detecting method and device capture a plurality of images of a monitored area; determines whether a moving area image exists in the plurality of images; analyzes at least one of a color model and a flickering frequency of the moving area image to generate a first analyzed result and compares the first analyzed result with a feature of a reference flame image; analyzes at least one of a variation of a location and an area of the moving area image to generate a second analyzed result and compares the second analyzed result with a predetermined threshold; and determines whether the moving area image is a flame image based on results of the comparing steps.