JP2001201577A - Weather detector, weather detection system, and weather detecting method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a weather detector, weather detection system and weather detecting method capable of quickly detecting meteorological states in a number of positions. SOLUTION: An image data obtained by photographing a snowing monitoring area is inputted (S10), and a two-dimensional discrete Fourier transform is performed for the image data (S12). The total sum of power spectra obtained by the two-dimensional discrete Fourier transform is calculated (S14), and the snowing state of the snowing monitoring area is judged on the basis of the value of the total sum of power spectra (S16).

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a weather detection device, a weather detection system, and a weather detection method for detecting weather conditions such as snowfall using image processing technology.

[0002]

2. Description of the Related Art On a highway or the like, it is necessary to remove snow from the road in winter due to weather conditions. This snow removal operation is performed by dispatching a snowplow according to weather conditions such as the amount of snowfall per unit time, and removing snow on the road with the snowplow. At that time, it is necessary to know the weather condition accurately in order to perform the snow removal work quickly and accurately.

In the past, weather situation, workers by measuring whether the snow of what g to 1m ² per hour by using a snowfall meter directly, has been measured.

[0004]

However, such a weather detection method cannot quickly grasp the weather conditions. In addition, when there are many measurement points for weather conditions, it is necessary to deploy workers accordingly, which requires a large number of personnel. Under such circumstances, there is a strong demand for technical development of devices capable of quickly detecting weather conditions at many locations.

The present invention has been made in order to solve the above problems, and provides a weather detection device, a weather detection system, and a weather detection method capable of quickly detecting weather conditions at many locations. The purpose is to:

[0006]

That is, a weather detection device according to the present invention is a Fourier transform means for inputting image data obtained by photographing a snowfall monitoring area and performing a two-dimensional discrete Fourier transform on the image data. And a calculating means for calculating the sum of the power spectra obtained by the two-dimensional discrete Fourier transform, and a snowfall judging means for judging the snowfall state of the snowfall monitoring area based on the value of the sum of the power spectra.

[0007] A weather detection system according to the present invention further comprises a photographing means for photographing a monitoring area in which a snowfall condition is to be monitored, a video signal output from the photographing means, and monitoring based on image data of the video signal. The above-mentioned weather detection device for detecting a snowfall state of the area is provided.

[0008] The weather detection method according to the present invention includes a Fourier transform step of inputting image data obtained by photographing a snowfall monitoring area and performing a two-dimensional discrete Fourier transform on the image data. And a snowfall judging step of judging the snowfall state of the snowfall monitoring area based on the value of the sum of the power spectra.

According to these inventions, the snowfall state can be detected through the periodicity in the image data by performing the two-dimensional discrete Fourier transform on the image data. In addition, the detection result is hardly affected by the surrounding brightness at the time of photographing, and accurate snowfall detection can be performed.

Further, in the weather detecting device according to the present invention, it is preferable that the snowfall judging means judges the snowfall state using a relational expression showing a relation between the sum of the power spectra and the snowfall state. When such a configuration is adopted, the snowfall state can be quantitatively indicated by numerical values by substituting the sum of the power spectra into the relational expression.

Further, the weather detection device according to the present invention is provided with a Fourier transform means for inputting image data obtained by photographing a monitoring area and performing a two-dimensional discrete Fourier transform on the image data, and a two-dimensional discrete Fourier transform. Wind power determining means for determining the wind power in the monitoring area based on the obtained power spectrum distribution state.

Further, the weather detection system according to the present invention receives photographing means for photographing a monitoring area, and a video signal output from the photographing means, and detects wind power in the monitoring area based on image data of the video signal. The weather detection device is provided.

[0013] The weather detection method according to the present invention further comprises a Fourier transform step of inputting image data obtained by photographing the monitored area and performing a two-dimensional discrete Fourier transform on the image data, and a two-dimensional discrete Fourier transform. And a wind power judging step of judging the wind power in the monitoring area based on the obtained distribution state of the power spectrum.

According to these inventions, by performing two-dimensional discrete Fourier transform on the image data, it is possible to detect the wind power in the monitoring area through the periodicity of the image data. In addition, the detection result is hardly affected by ambient brightness at the time of photographing, and accurate wind force detection can be performed.

[0015]

Embodiments of the present invention will be described below with reference to the accompanying drawings. In each of the drawings, the same elements are denoted by the same reference numerals, and description thereof is omitted. Also, the dimensional ratios in the drawings do not always match those described.

(First Embodiment) FIG. 1 is a configuration diagram of a weather detection system and a weather detection device according to this embodiment.

As shown in FIG. 1, a weather detection system 1
Is a system for detecting a snowfall condition on a highway on which a vehicle or the like travels, and includes a monitoring camera 2 and a weather detection device 3.

The surveillance camera 2 is a photographing means for photographing on a highway or a general national road, for example, a CCD camera or the like is used. The surveillance camera 2 is not limited to one that captures a moving image, and may be one that captures a still image. Further, the surveillance camera 2 may be a movable camera capable of changing a shooting position. In this case, a detection plate 21 to be described later may be periodically photographed at regular time intervals.

When a monitoring camera used for a road traffic monitoring system is installed, the traffic monitoring camera may be used as the monitoring camera 2 of the weather detection system 1. In this case, a video signal obtained by an existing monitoring camera is used, and weather detection can be performed based on the video signal. Therefore, there is no need to separately install the monitoring camera 2 for the weather detection system 1, and the installation cost of the weather detection system 1 can be greatly reduced.

In front of the monitoring camera 2, a detection plate 21 is provided. The detection plate 21 functions as a background for detecting falling snow, and is formed of a black plate. By making the detection plate 21 black, the presence of white snow becomes clear and the snow can be easily imaged. It is desirable that the surface of the detection plate 21 is waterproof-coated. In this case, snow is prevented from adhering to the surface of the detection plate 21, and the function as a background at the time of shooting snow is not impaired. Further, it is desirable to provide illumination for illuminating the detection plate 21 so that the snowfall state can be detected even at night.

Although only one surveillance camera 2 is shown in FIG. 1, the weather detection system 1 includes a plurality of surveillance cameras 2, and the surveillance cameras 2 are installed at each location on the road. .

Each monitoring camera 2 is electrically connected to the weather detection device 3 and outputs a video signal to the weather detection device 3. The weather detection device 3 receives a video signal of the monitoring camera 2, performs image processing based on the video signal, and detects a weather condition in a monitoring area, and functions as a weather detection unit in the weather detection system 1. .

The weather detection device 3 includes a video input unit 31,
Image processing unit 32, measurement processing unit 33, external device output unit 34
And a human interface 35.

The video input unit 31 receives a video signal output from the surveillance camera 2, converts an analog video signal into a digital signal, and performs A / D conversion at regular intervals. The video signal is input to the image memory as image data. The input of the image data is performed at a constant period, for example, 3 sec. It is performed every time. The input image data is, for example, a set of pixels having a gray scale value for each of the x-axis and y-axis coordinate points, and the gray scale of the pixel is, for example, 8-bit 256 gradation.

The image processing section 32 carries out processing such as Fourier transform processing of image data, calculation processing of a power spectrum, and determination of a snowfall mode, and is constituted by, for example, an image processing processor. The measurement processing unit 33 performs control processing such as data accumulation processing and communication processing with an external device, and is configured by, for example, a general-purpose microprocessor.

The external output section 34 outputs the weather condition in the monitoring area as a detection signal.
Is connected to The external device 4 displays weather information and the like, and is, for example, a weather database or a warning display board installed in a control center, a display panel installed near an expressway, and the like.

The human interface 35 is for setting system parameters and outputting processing results, and is installed between the monitor / maintenance console 5 and the image processing unit 32, the measurement processing unit 33 and the external output unit 34. ing. The monitor / maintenance console 5 is installed in a control center (not shown), and performs settings of the weather detection device 3 and the like. In the control center, a video signal transmitted from the surveillance camera 2 is input to the monitor via the weather detection device 3 so that a monitoring person can visually monitor the monitoring area.

Next, a weather detection method in the weather detection system and the weather detection device according to the present embodiment will be described.

In FIG. 1, a surveillance camera 2 photographs a surveillance area on a highway. The video signal of the surveillance camera 2 is input to the video input unit 31 of the weather detection device 3, A / D converted, and stored as image data. Then, a weather condition is detected by the weather detection device 3 based on the image data.

FIG. 2 shows a flowchart of the weather detection process in the weather detection device 3.

Step S10 of FIG. 2 (hereinafter simply referred to as "S1
0 ". The same applies to other steps. In), the image data is read. Image data is
For example, it is read at a constant period of 3 sec. Then
The process proceeds to S12, where Fourier transform processing for performing two-dimensional discrete Fourier transform on the read image data is performed.

This Fourier transform processing is performed in a partial area in the image data, that is, in a measurement area. In the measurement area, an area where the number of pixels is a factorial of 2 is set.
An area of 4 × 64 is set.

Then, the power spectrum F (u, v) in the measurement area is calculated by the following equation (1).

(Equation 1) Here, f (x, y) is the luminance value of the pixel in the measurement area, M is the number of pixels in the horizontal direction of the measurement area, and N is the number of pixels in the vertical direction of the measurement area. u and v are −M / 2 ≦ u ≦ M
/ 2, −N / 2 ≦ v ≦ N / 2.

Then, the flow shifts to S14, based on the power spectrum F (u, v) of the equation (1), as shown in the following equation (2), the intensity (amplitude spectrum) P (u) of the power spectrum. , V) are calculated. P (u, v) = (R2 + I2) 1/2 (2) where R is the real part of F (u, v), and I is F (u,
The imaginary part of v).

The power spectrum intensity P (u,
Based on v), the total sum PM of the power spectrum in the measurement region is calculated as shown in the following equation (3).

(Equation 2) Here, PM is a value excluding P (0, 0).

Then, the flow shifts to S16, where a snowfall state is determined. The determination of the snowfall state is performed based on the total sum PM of the calculated power spectra.

For example, the snowfall mode is set as "strong", "medium", "weak", and "none" in the order of the snowfall intensity, the thresholds of "strong" and "medium" of the snowfall mode are set to A1, Are set as A2, and the thresholds of "weak" and "none" in the snowfall mode are set as A3. In this case, the thresholds A1, A2 and A3 are: A1>A2> A3
Is set.

If the sum PM of the calculated power spectrum is equal to or greater than the threshold value A1, the snowfall mode is determined to be "strong", and the sum PM of the calculated power spectrum is determined by the threshold value A1. If the value is smaller than A1 and equal to or more than the threshold value A2, the snowfall mode is determined to be “medium”. Sum PM of power spectrum determined and determined as "weak"
Is smaller than the threshold value A3, it is determined that the snowfall mode is "none".

Then, the flow shifts to S18, where the information on the determined snowfall mode is output from the external output unit 34 to the external device 4, and the control processing ends.

Next, the results of actual weather detection performed using the weather detection device, the weather detection system, and the weather detection method according to this embodiment will be described.

FIGS. 3 to 6 show image data obtained on the basis of the video image captured by the monitoring camera 2. FIG. FIG. 3 shows image data when the snowfall state is strong. FIG. 4 shows image data when the snowfall state is medium. FIG. 5 shows image data when the snowfall state is weak. FIG. 6 shows image data when snow does not fall. Note that the image data of FIGS.
The vertical n is a bmp image of 320 × 240 (76800 points). In FIGS. 3 to 6, a black portion is a black detection plate 21.

The above-described image processing in S12 to S14 in FIG.
That is, Fourier transform processing was performed. As a result, FIGS.
4 was obtained.

FIG. 7 shows a three-dimensional image obtained by Fourier transforming image data when the snowfall condition is strong. In FIG. 7, the horizontal direction of u and v indicates frequency components, and the vertical direction of PM indicates intensity at each frequency component. FIG. 8 is a plan view of FIG. 7 and shows a frequency distribution in the Fourier transform when the snowfall state is strong.

FIG. 9 shows a three-dimensional image obtained by performing a Fourier transform on image data when the snowfall state is moderate. FIG. 10 is a plan view of FIG. 9, and shows a frequency distribution in the Fourier transform when the snowfall state is moderate.

FIG. 11 is obtained by performing a Fourier transform on the image data when the snowfall condition is weak, and shows it three-dimensionally. FIG. 12 is a plan view of FIG. 11, and shows a frequency distribution in the Fourier transform when the snowfall state is weak.

FIG. 13 is obtained by performing a Fourier transform on the image data without snowfall, and shows it three-dimensionally. FIG. 14 is a plan view of FIG. 13 and shows a frequency distribution in the Fourier transform when there is no snowfall.

FIGS. 7 to 14 are obtained by shuffling the u and v frequency components by distributing the low frequency component at the center and the high frequency component at the four corners.

Looking at the Fourier transform in the case of a strong snowfall state shown in FIGS. 7 and 8, the power spectrum (PM) is large centering on the low frequency component, and the periodicity in the vertical direction (v) is strongly shown. ing.

Looking at the Fourier transforms in FIGS. 9 and 10 when the snowfall state is medium, the power spectrum (PM) is large centering on the low frequency component, but the periodicity in the vertical direction (v) is low. Somewhat strongly indicated.

Looking at the Fourier transform in the case where the snowfall state is weak in FIGS. 11 and 12, the power spectrum (PM) is small as a whole.

Looking at the Fourier transform without snowfall shown in FIGS. 13 and 14, the power spectrum (P
M) is very small.

When the sum of the power spectra in each snowfall state is calculated, as shown in FIG. 15, it is 1181291.1 when the snowfall state is strong, and 1015720.0 when the snowfall state is moderate, as shown in FIG. It was 885125.7 when the snowfall condition was weak, and was 39936.7 when there was no snowfall condition.

As described above, each snowfall state can be determined based on the magnitude of the sum of the power spectra. In this case, as the threshold for determining the snowfall state, for example, the threshold A1 of “strong” and “medium” in the snowfall state is set to 105000
0, the threshold A2 of "medium" and "weak" in the snowfall state is 950
If the threshold value A3 for “weak” and “none” in the snowfall state is set to 450,000, the snowfall state can be determined based on the sum of the power spectra.

As described above, according to the weather detection system, the weather detection device, and the weather detection method according to the present embodiment, the image data of the location where the weather condition is to be detected is image-processed, so that the snowfall condition can be reduced. Can be detected.
For this reason, it is possible to quickly detect a snowfall situation at many places.

Further, by performing Fourier transform as image processing, it is possible to detect the periodicity of the image due to snowfall in the image data, and determine the snowfall state based on the degree of the periodicity. Therefore, it is possible to reliably determine the snowfall state without being affected by the brightness of the image due to the brightness around the monitoring area.

Further, by determining the snowfall state based on the sum of the power spectra, not the maximum value of the power spectrum obtained by the Fourier transform, it is possible to reliably determine whether the snowfall state is "strong" or "medium". can do.

Further, according to the weather detection system, the weather detection apparatus and the weather detection method according to the present embodiment, if the video of the existing surveillance camera is used, no new installation work of the surveillance camera is required, and the weather detection is not required. Easy installation of the system.

In this embodiment, the weather detection system, the weather detection device and the weather detection method for detecting the snowfall on the highway have been described. However, the weather detection system, the weather detection device and the weather detection method according to the present invention are not limited to this. The present invention is not limited to this, and may detect a snowfall situation in another place.

(Second Embodiment) Next, a weather detection device, a weather detection system, and a weather detection method according to a second embodiment will be described.

Although the weather detection device, the weather detection system, and the weather detection method according to the first embodiment detect the snowfall state of the monitoring area, the weather detection device, the weather detection system, and the weather detection according to the present embodiment. The method is to detect the wind force during snowfall in the monitoring area.

The weather detection device and the weather detection system according to the present embodiment have the same hardware configuration as the weather detection device and the weather detection system of the first embodiment shown in FIG.

FIG. 16 is a flowchart of a weather detection process according to the weather detection device and the like.

At step S20 in FIG. 16, image data is read. The image data is, for example, 3
It is read at a constant period of c. Next, the flow shifts to S22, where Fourier transform processing of the read image data is performed. This Fourier transform processing is performed in S12 of FIG.
Is performed in the same manner as the Fourier transform processing.

Next, the flow shifts to S24, where the distribution of the power spectrum is detected. For example, the distribution of the power spectrum is detected by detecting the distribution of the power spectrum of the frequency component in the Fourier transform of the image data.

Then, the flow shifts to S26, where the wind power in the monitoring area is determined based on the distribution of the power spectrum.
For example, as shown in FIG.
When the power spectrum is distributed, it means that the image data has strong periodicity in the horizontal direction.
It can be determined that the snow is falling in the horizontal direction and the wind is strong. On the other hand, when the power spectrum is distributed in the horizontal direction (u) of the frequency distribution, it means that the vertical direction in the image data is strong, so it is determined that snow is falling in the vertical direction and the wind power is weak. be able to.

The Fourier transform of the image data is also performed by shuffling in this case.

Then, the flow shifts to S28, where information on the determined wind power is output from the external output unit 34 to the external device 4, and the control processing ends.

As described above, according to the weather detection system, the weather detection device, and the weather detection method according to the present embodiment, the image data of the location where the weather condition is to be detected is image-processed, so that the monitoring area can be monitored. Wind power can be detected. For this reason, the wind conditions at many locations can be quickly detected.

Further, by performing Fourier transform as image processing, it is possible to detect the periodicity of the image due to snowfall or the like in the image data, and determine the wind power in the monitoring area based on the degree of the periodicity. Therefore, without being affected by the brightness of the image due to the brightness around the monitoring area,
The determination of wind power can be performed reliably.

(Third Embodiment) Next, a weather detection system and a weather detection device according to a third embodiment will be described. This embodiment is different from the first embodiment in the internal configuration of the measurement processing unit 33 and the method in which the measurement processing unit 33 determines the snowfall state based on the sum of power spectra.

FIG. 17 is a diagram showing the measurement processing unit 33 provided in the weather detection device 3 of the present embodiment. As shown in the figure, the measurement processing unit 33 has a built-in relational expression storage unit 33a that stores a relational expression indicating the relation between the total sum PM of the power spectrum and the snowfall state. Hereinafter, this relational expression is referred to as a “snowfall intensity calculation expression”.

Referring to FIG. 18, the formula for calculating the snowfall intensity will be described. FIG. 18 is a graph used to generate the snowfall intensity calculation formula. First, using the weather detection system of the first embodiment, the sum PM of the power spectrum is calculated and the horizontal axis is used, and the actual snowfall intensity (cm / h) when the sum of each power spectrum is calculated is the vertical axis. Plotted. This graph shows the results obtained by daytime measurements. Then, when an optimal curve indicating the distribution of each plotted point was obtained, the following two-dimensional binary data showing the correlation between the image output result x (sum of power spectra) and the snowfall intensity y (cm / h) was obtained. The following equation for calculating snowfall intensity was obtained. y = ax ² + bx + c (where a = 3.0 × 10 ⁻¹⁷ , b = −4.0 × 1
0 ^-9 , c = 0.113) Note that the Pearson product moment correlation coefficient R of the snowfall intensity relational expression is 0.8462, and it is found that there is a strong correlation between the sum x of the power spectrum and the snowfall intensity y. Was.

Then, the weather detection system 1 of this embodiment
First, the operations of S10 to S20 in FIG. 2 are performed as in the first embodiment to actually detect the snowfall state.
Then, after obtaining the total sum PM of the power spectrum in S14, the measurement processing unit 33 substitutes the total sum PM of the power spectrum into the above-described snowfall intensity calculation formula stored in the relational expression storage unit 33a, thereby obtaining the snowfall intensity ( cm / h) (S16). The snowfall intensity obtained in this way quantitatively indicates the snowfall state as a numerical value, and has higher reliability than the result detected in the first embodiment.

FIGS. 19 and 20 are graphs showing the relationship between the time and the snowfall intensity. The snowfall intensity detected by the weather detection system 1 of the present embodiment is represented by a solid line, and the manually measured snowfall intensity ( Hereinafter, the true value is represented by a broken line. FIG. 19 shows the measurement results from 9:40 to 10:25, and FIG. 20 shows the measurement results from 12:10 to 14:05. As shown in each graph,
The tendency of the snowfall intensity detected by the weather detection system 1 is close to the true value, and it can be seen that the weather detection accuracy of the gas phase detection device and the weather detection system of the present embodiment is extremely excellent. For this reason, weather conditions at many places can be detected quickly and accurately.

FIG. 21 is a graph used to derive a nighttime snowfall intensity calculation formula. First, as in the case of obtaining the daytime snowfall intensity calculation formula, the total PM of the power spectra was obtained using the weather detection system of the first embodiment, and this was set as the horizontal axis, and the total PM of each power spectrum was obtained. The actual snowfall intensity (cm / h) at that time was plotted on the vertical axis. Then, when an optimal curve indicating the distribution of each plotted point was obtained, the total power spectrum x
The following binary / secondary snowfall intensity calculation formula showing the correlation between the snowfall intensity and the snowfall intensity y (cm / h) was obtained. y = ax ² + bx + c (where a = 2.39 × 10 ⁻¹⁶ , b = −7.32 × 1
0 ⁻⁸ , c = 5.601) Note that the Pearson product-moment correlation coefficient R of this snowfall intensity relational expression is 0.8590, which indicates that there is a strong correlation between the sum x of the power spectrum and the snowfall intensity y. Was.

FIG. 22 is a graph showing the relationship between the time and the snowfall intensity. The snowfall intensity detected by the weather detection system 1 of this embodiment is represented by a solid line, and the true value is represented by a broken line. The measurement time was from 18:05 to 20: 2 at night.
Up to 0 minutes. As shown in this graph, the tendency of the snowfall intensity detected by the weather detection system 1 is close to a true value, and even at night, the weather detection accuracy of the gas phase detection device and the weather detection system according to the present embodiment is It turns out that it is excellent.

[0077]

As described above, according to the present invention, the weather condition can be detected by processing the image data of the place where the weather condition is to be detected. For this reason, the weather conditions of many places can be detected quickly.

By performing a two-dimensional discrete Fourier transform on the image data, it is possible to detect a weather condition through the periodicity of the image data. In addition, the detection result is hardly affected by the surrounding brightness at the time of photographing, and accurate weather conditions can be detected.

[Brief description of the drawings]

FIG. 1 is an explanatory diagram of a weather detection system according to a first embodiment.

FIG. 2 is a flowchart showing the operation of the weather detection device.

FIG. 3 is an explanatory diagram of image data.

FIG. 4 is an explanatory diagram of image data.

FIG. 5 is an explanatory diagram of image data.

FIG. 6 is an explanatory diagram of image data.

FIG. 7 is an explanatory diagram of image data after Fourier transform.

FIG. 8 is an explanatory diagram of image data after Fourier transform.

FIG. 9 is an explanatory diagram of image data after Fourier transform.

FIG. 10 is an explanatory diagram of image data after Fourier transform.

FIG. 11 is an explanatory diagram of image data after Fourier transform.

FIG. 12 is an explanatory diagram of image data after Fourier transform.

FIG. 13 is an explanatory diagram of image data after Fourier transform.

FIG. 14 is an explanatory diagram of image data after Fourier transform.

FIG. 15 is an explanatory diagram of a power spectrum sum in image data.

FIG. 16 is an explanatory diagram of a weather detection device and the like according to a second embodiment.

FIG. 17 is a diagram illustrating a measurement processing unit of the weather detection system according to the third embodiment.

FIG. 18 is a graph for obtaining a daytime snowfall intensity calculation formula.

FIG. 19 is a graph showing a relationship between a result obtained by the weather detection system of the third embodiment and a true value.

FIG. 20 is a graph showing a relationship between a result obtained by the weather detection system of the third embodiment and a true value.

FIG. 21 is a graph for obtaining a snowfall intensity calculation formula for night use.

FIG. 22 is a graph showing a relationship between a result obtained by the weather detection system of the third embodiment and a true value.

[Explanation of symbols]

1. Weather detection system 2. Surveillance camera (photographing means)
3 weather detector, 21 detection plate, 33 measurement processor,
33a ... Relational expression storage unit.

Claims (7)

[Claims] An image data obtained by photographing a snowfall monitoring area is input, and a Fourier transform means for performing a two-dimensional discrete Fourier transform on the image data, a power spectrum obtained by the two-dimensional discrete Fourier transform is provided. A weather detection device comprising: a calculating unit that calculates a total sum; and a snowfall determining unit that determines a snowfall state of the snowfall monitoring area based on a value of the sum of the power spectra. 2. The snowfall judging means uses a relational expression indicating a relation between the sum of the power spectra and a snowfall state,
The weather detection device according to claim 1, wherein the snowfall state is determined. 3. A photographing means for photographing a monitoring area for monitoring a snowfall condition, a video signal output from the photographing means being input, and detecting a snowfall state of the monitoring area based on image data of the video signal. A weather detection system comprising: the weather detection device according to claim 1. 4. A Fourier transforming step of inputting image data obtained by photographing a snowfall monitoring area and performing a two-dimensional discrete Fourier transform on the image data, and a power spectrum obtained by the two-dimensional discrete Fourier transform. A weather detection method, comprising: a calculating step of calculating a sum; and a snowfall determining step of determining a snowfall state of the snowfall monitoring area based on a value of the sum of the power spectra. 5. Fourier transform means for inputting image data obtained by photographing a monitoring area and performing a two-dimensional discrete Fourier transform on the image data, and a distribution of a power spectrum obtained by the two-dimensional discrete Fourier transform A wind power determining means for determining a wind power in the monitoring area based on a state. 6. A photographing means for photographing a monitoring area, and a video signal output from the photographing means is input, and a wind force in the monitoring area is detected based on image data of the video signal. A weather detection system comprising: a weather detection device; 7. A Fourier transform step of inputting image data obtained by photographing a monitoring area and performing a two-dimensional discrete Fourier transform on the image data, and a distribution of a power spectrum obtained by the two-dimensional discrete Fourier transform. A wind power determining step of determining a wind power in the monitoring area based on a state.