1. Field of the Invention
The present invention relates to a method and system for detecting early fires in a predetermined area, and more particularly, to a method and system that can detect if images contain flames and if a flame increases to be a fire.
2. Description of the Prior Art
Generally, a HSI (hue/saturation/intensity) domain is usually utilized for analyzing images, since hue, saturation and intensity can represent all combinations of light to describe color. One prior art method detects if images have flames in the HSI domain. The method includes capturing images in a predetermined area, transforming RGB of each pixel of the images into HSI, and determining if the HSI of each pixel complies with rules in the HSI domain.
In the prior art, the RGB of each pixel is transformed into the HSI by the following equations:
In the prior art, HSI is utilized for analyzing flame. The HSI domain is divided into six regions, as shown in
0°≦H≦60° (i)
Brighter environment: 30≦S≦100, Darker environment: 20≦S≦100 (ii)
127≦I≦255 (iii)
The method mentioned above for detecting fire includes a series of complicated equations to transform RGB into HSI, which requires intensive computations. Besides, the low bound of the saturation condition (ii) may be too small to work correctly and hence it will yield a false fire-detection due to the appearance of reflected flames.
Furthermore, in a fire detecting system, another important function is to generate a fire alarm to prevent a fire accident. The method for generating a fire alarm according to the prior art compares the number of fire pixels to a threshold. If the number of fire pixels in an image is larger than the threshold, a fire alarm is output. However, the method is confined by the distance between the fire and an image capturing device (such as a camera). This enormously increases the false fire alarm rate and thus cannot adequately achieve the purpose of detecting early fires.
For example, suppose that the size of a flame is constant, such as a flame of a candle or a lighter. This kind of flame does not constitute a fire accident; therefore, a fire alarm is not required. Please refer to
In another situation, supposing that the flame spreads out and forms a fire, a fire alarm should be generated. Please refer to
It is therefore a primary objective of the claimed invention to provide a method for detecting early fires in a predetermined area to solve the above-mentioned problem.
The claimed invention includes capturing a plurality of images in a predetermined area for generating a plurality of difference frames during an interval, detecting a number of pixels that have fire characteristics in each difference frame, and if the detection result indicates that the flame of the predetermined area substantially increases during the interval, outputting an early fire alarm.
These and other objectives of the present invention will no doubt become obvious to those of ordinary skill in the art after reading the following detailed description of the preferred embodiment that is illustrated in the various figures and drawings.
In order to shed light on the present invention, the first discussion relates how to detect fire pixels of frames, and the second discussion relates how to detect a flame increasing to become a fire. Finally, the best embodiment of detecting early fires, which combines the first method with the second method, is disclosed.
To provide less-computational fire-detecting rules and overcome the problem of small low-bound in condition (ii) described previously, we develop a more cost-effective and reliable fire-detection strategy. Two basic ideas behind the proposed technique are based on direct processing with RGB model and solving the problem of the reflected flames. As mentioned above, the color range of a common fire is from red to yellow. From the table in
Because fire is a light source, the image capturing device needs sufficient brightness to capture useful image sequences. From the color of fire, R is the maximum of R, G, and B and is thus the major component. There should be a stronger R in a fire image. Hence, the value of the R component should be over a threshold, Rt, which is obtained from the results of experiments. However, background illumination can affect the saturation of flames or generate a false appearance of flame so that false fire detection occurs. To prevent such a mistake caused by the background illumination, the saturation of flames must satisfy a determined equation to eliminate the false appearance of flame. The determined equation is also obtained from the result of experiments. Based on the explanation above, the rules are described as follows:
0≦S≦1
In rule 3, when the value of the red component of a pixel is Rt, the saturation of the pixel is St. St and Rt are obtained from a great number of experiment values. Both St and Rt are affected by the background illumination, such as that during the day or the night. Therefore, St and Rt change with the environment. In rule 3, when R increases up to the value 255, the result should be zero. That is, S of fire pixels increases with R increasing while the result of rule 3 decreases.
Please refer to
Detecting flames by the three rules only requires calculating S according to RGB instead of transforming RGB into HSI. Also, the present invention reduces a lot of calculation by directly utilizing RGB for detecting if pixels captured are fire pixels.
In addition, the color range of flames is from red to yellow and R is the maximum of components R, G, and B of a fire pixel, as shown in
The next discussion relates how to detect if a flame is increasing to be a fire. After detecting flames by the three rules, the number of fire pixels of each image can be calculated. Repeats of capturing images and recording the number of fire pixels of each image are required for the detection. Capturing K images and determining if the number of fire pixels increases over P %*K times indicates whether a flame is spreading out to become a fire, and if a fire alarm should be generated.
For instance, suppose that K is 100 and P is 70. After capturing 100 images and calculating the numbers of fire pixels of each image, the number of fire pixels is compared between sequential images. If the number of fire pixels in a latter image is larger than that in a former image, the number of fire pixels has increased. In other words, the number of fire pixels of the i-th image is compared to that of the i+1-th image, and the number of fire pixels of the i+1-th image is compared to that of the i+2-th image, and so on. If the number of fire pixels increases over 70 (K*P %=100*70%=70) times, the flame is detected as spreading out to become a fire and a fire alarm should be generated.
The methods mentioned above are carried out in a fire detection system. Please refer to
Step 100: start the fire detection system.
Step 102: the image capturing device 12 captures a plurality of images and a background image.
Step 104: detect if there is a difference between the background image and the current image; that is, perform a difference frame process. The differences between the images captured by the image capturing device 12 and the background image are retained and noise of the differences is removed for generating a plurality of difference frames. The difference between the current image and the background image is detected by the difference frame process.
Step 106: detect if each pixel is a fire pixel by the three rules and record the numbers in each difference frame. If at least one of pixels is a fire pixel, go to step 108. Otherwise, if no pixel has fire characteristics, re-detect the difference between the background image and the images captured by the image capturing device 12 and go to step 104.
Step 108: detect if the flame increases to be a fire according to the numbers of fire pixels of difference frames. If yes, go to step 110. If no, stay in step 108. Because pixels of difference frames are detected to be fire pixels, the flame is still small at this time. Therefore, continuously detect if the flame increases to be a fire.
Step 110: if the number of fire pixels increases over K*P % times, it indioates that the flame spreads out to be a fire and a fire alarm should be generated.
The present invention can reduce the calculations required and efficiently reduce the false fire alarm rate while preventing fire accidents.
As mentioned above, the prior art is confined by the distance of the flame and the image capturing device so that the false fire alarm rate increases. The present invention can efficiently reduce the false fire alarm rate.
For instance, suppose that the size of flame is constant, such as a flame of a candle or a lighter. This kind of flame will not bring about a fire accident; therefore, a fire alarm is not provided. Please refer to
In another situation, supposing that the flame spreads out and forms a fire, the fire alarm should be generated. Please refer to
From the examples mentioned above, the present invention efficiently reduces the false fire alarm rate.
Generally, fires are formed by inflammable substances in a combustion-supporting atmosphere at suitable temperature. Equally important, it takes a period of time to form a fire. The present invention uses the period before a fire is fully formed to repeatedly record the number of fire pixels of difference frames for detecting if a flame increases, outputting a fire alarm when significant flame increase is determined. Thus, the flame can be extinguished before forming a full-scale fire. The present invention also can efficiently reduce the false fire alarm rate to achieve efficient fire detection.
Those skilled in the art will readily observe that numerous modifications and alterations of the device may be made while retaining the teachings of the invention. Accordingly, the above disclosure should be construed as limited only by the metes and bounds of the appended claims.
Number | Name | Date | Kind |
---|---|---|---|
5243418 | Kuno et al. | Sep 1993 | A |
5510772 | Lasenby | Apr 1996 | A |
5726632 | Barnes et al. | Mar 1998 | A |
5937077 | Chan et al. | Aug 1999 | A |
6184792 | Privalov et al. | Feb 2001 | B1 |
6956485 | Aird et al. | Oct 2005 | B1 |
20030044042 | King et al. | Mar 2003 | A1 |
20040061777 | Sadok | Apr 2004 | A1 |
Number | Date | Country | |
---|---|---|---|
20050253728 A1 | Nov 2005 | US |