Infrared Open Flame Detection Using Multi-Frame Gray Scale Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for detecting open flames in non-smoking areas suffer from low accuracy due to the inability to reliably distinguish features such as area, shape, and dynamics, leading to potential health and safety risks from smoking-related fires.
Innovation Solution
A method and apparatus utilizing a terminal equipped with a photographing apparatus, such as an infrared camera, to acquire and process frames of images, segment suspected targets, and analyze gray scale and attribute features to determine if a target is an open flame by comparing against predefined conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image processing methods are used to detect open flames, then the detection process is simple, but the detection accuracy is low due to inability to reliably distinguish features
Solution Approach 1:
The patent segments the image processing into multiple independent modules: gray scale feature extraction module, attribute feature extraction module, and combination judgment module. Each module processes specific features (gray scale, area, shape, dynamics) separately before integrating them for final detection, which improves accuracy while maintaining manageable complexity through modular architecture
Solution Approach 2:
The patent transitions from traditional single-dimension detection to multi-dimensional feature analysis by simultaneously evaluating gray scale characteristics, spatial attributes (area, shape), and temporal dynamics across multiple image frames. This dimensional expansion enables reliable distinction between open flames and other targets, significantly improving detection accuracy
2Reliability
If multiple features (area, shape, dynamics) are analyzed to improve detection accuracy, then detection reliability improves, but the processing time increases
Solution Approach 1:
The patent performs preliminary feature extraction and pre-judgment on each image frame before integrating with historical frames. By pre-processing gray scale and attribute features independently, the system reduces the computational burden during the combination judgment phase, thereby improving reliability without excessive time penalty
Solution Approach 2:
The patent continuously accumulates and processes image frames in real-time, maintaining an ongoing analysis of feature changes over time. This continuous processing approach ensures that detection reliability improves through accumulated evidence while the system adapts processing intensity based on current detection needs, optimizing the time-reliability trade-off
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
Accurately detects open flames by combining gray scale and attribute feature analysis, improving detection accuracy and enabling timely warning to prevent health and safety hazards.
Implementation Method 1
utilizing a terminal equipped with a photographing apparatus, such as an infrared camera
Data Source
Figure 1~2
Figure 3~4
Figure 5~7
AI summary
A method and apparatus for detecting an open flame, and a storage medium belong to the field of safety protection. The method includes: acquiring a plurality of frames of first images (21) of a suspected target in a monitoring region; acquiring, based on the plurality of frames of first images, gray scale change features of the plurality of frames of first images and attribute features of the suspected target, the gray scale change features being configured to indicate temperature changes (22) of the suspected target; and determining that the suspected target in the monitoring region is an open flame (23) if the gray scale change features of the plurality of frames of first images and the attribute features of the suspected target both satisfy an open flame condition. The method can be used to accurately detect whether there is an open flame in the monitoring region.