Flame Detection Using Flickering Frequency 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 use of the RGB color model and reliance on motion and color recognition alone, leading to inefficient fire detection and control.
Innovation Solution
The proposed method employs a flame detecting system that captures images, analyzes color models using three-dimensional RGB and YUV Gaussian mixture models, and analyzes flickering frequencies and location variations to accurately identify flames, reducing false alarms by comparing analyzed results with reference flame features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional RGB color model and motion detection are used for flame detection, then the detection system is simple to implement, but the detection accuracy is low and false alarm rate is high
Solution Approach 1:
The patent transforms the flame detection problem from spatial color analysis to temporal frequency analysis. By converting video frames into frequency domain representations through FFT and analyzing flickering frequencies, the system captures the dynamic temporal characteristics of flames rather than static color properties, thereby improving detection accuracy while maintaining system simplicity
Solution Approach 2:
The patent replaces conventional color-based optical analysis with frequency-based spectral analysis. Instead of comparing RGB color values against flame color models, the system applies Fast Fourier Transform to extract frequency signatures from temporal pixel intensity variations, substituting a more sophisticated mathematical approach for simpler color matching
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 performs preliminary frequency domain transformation and flickering frequency extraction before final flame determination. By pre-processing the video data to extract temporal frequency characteristics and storing reference frequency signatures, the system prepares discrimination criteria in advance, enabling faster and more reliable flame identification without requiring complex real-time color model comparisons
Solution Approach 2:
The patent introduces frequency domain analysis as an intermediary step between raw video capture and flame detection decision. The Fast Fourier Transform acts as a mediator that converts spatial-temporal pixel data into frequency signatures, which then serve as the basis for reliable flame identification, bridging the gap between simple motion detection and accurate flame recognition
Data Source
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.