KR100715140B1 - Visibility measuring apparatus and method - Google Patents

Abstract

The present invention is provided at a predetermined distance from a specific target, the camera for shooting a predetermined period of the image of the target; An illuminance sensor installed at a specific position in a specific region in which the target is fixed and detecting illuminance of a specific position at a predetermined cycle; The image taken by the camera and the light quantity data detected by the illuminance sensor are input, the image is processed and color analyzed by the input image, and reference correction data and correction error data are set in advance. A data logger comparing and analyzing the correction data to calculate a first correction, and comparing and correcting the correction error data and the amount of input light; And a network for allowing the main server connected to the data logger through a communication interface to remotely monitor the visibility of a specific area, thereby enabling more accurate and accurate visibility measurement.

In addition, remote monitoring is possible by sending the secondary and tertiary visibility information of a certain period calculated in a specific area on the web, so that the visibility information for a specific area can be collected quickly, and monthly, time range, and weather conditions. The standard correcting data and correcting error data are set according to the environment such as star, day / night, etc., so it is possible to measure more accurate correctiveness in various environments, and it is highly reliable. You can calibrate manually.

Description

Visibility measuring apparatus and method

1 is an illustration of a visibility measurement method according to the prior art,

2a to 2c are detailed block diagrams of the visibility measurement device according to the present invention,

3a to 3c is a flow chart of the visibility measurement method according to the invention,

4A to 4C are exemplary views of an overlay image in the visibility measurement method according to the present invention.

5 is an exemplary diagram of a table converted from visibility corresponding to color analysis according to the present invention.

* Description of the symbols for the main parts of the drawings *

10: CCD camera 20: Ambient light sensor

30: noise filter 40: main server

50: network 60: client

The present invention relates to a visibility measuring apparatus and method, and more particularly, to a primary camera by calculating a primary visibility by image processing of image data photographing a target with a resolution-enhanced CCD camera and overlaying with a reference image to analyze colors. The corrected error is corrected by applying the amount of light detected by the illuminance sensor to calculate the more accurate secondary correction, and the third order of averaging a plurality of secondary corrections calculated at regular intervals for each image pixel. The present invention relates to a visibility measurement apparatus and method for remotely monitoring from outside and collecting information on a specific area quickly and accurately by storing the visibility and transmitting the web based on a web through a network.

Visibility represents the turbidity of the atmosphere and is determined by the way of looking at objects at different distances. However, it is difficult to measure accurately because the method of viewing varies according to the size, shape, brightness, color of the target, and the situation of the background or individual differences of the naked eye.

Therefore, in order to measure visibility, conventionally, a target is set at a point where the distance is known in each direction, and the visibility is measured by visual observation based on the reference, or the brightness difference between the object and the background at a specific distance is measured. Corrective measurements were also taken, or a measuring instrument was used to determine the corresponding visibility from the concentration when looking at the target through the milky glass with varying concentrations and indistinguishable from the background.

In particular, the visibility system is used to measure visibility in aviation, etc.For visibility measurements on airfield runways and automobile roads, the intensity of horizontal light emitted from the floodlight is measured by a receiver at an arbitrary distance, and it is calculated from light attenuation. The method is used. This is called a transmissometer, and it is possible to obtain a viewing distance such as visibility during the day, but there may be a problem that other values may appear at night. In addition, the installation was difficult and there was a lot of error in the correction data depending on the environmental conditions between the light source and the receiver.

In addition, the transmitter of the transmittance meter is similar to the headlight bulb of an automobile, and the light receiving unit uses a phototube.

FIG. 1A illustrates a visibility measurement method using a transmissometer, which measures the amount of light transmitted directly into the atmosphere, and is based on a single (50m) and double (15 / 75m) base. It operates in two ways: the base line.

1b shows a visibility measurement method using a forward-scatter meter method, which measures the amount of reflected light (scattered and scattered), and has the smallest deviation at 35 ° and 135 ° angles. The phenomenon (particle form) can be observed.

The present invention has been made to solve the problems of the prior art as described above, and an object of the present invention is to shoot a target in a specific area with a CCD camera having an improved resolution, and then to perform primary correction by analyzing image processing and colors. The present invention provides a visibility measuring device and method capable of more accurate and accurate visibility measurement by calculating and comparing the amount of light sensed by the illuminance sensor and calculating the secondary visibility corrected for the error of the primary visibility.

Another object of the present invention is to calculate a third order correction by averaging a plurality of successive second visions for each image pixel, which is stored at regular intervals, so that a more accurate and accurate visibility measurement is possible. To provide.

Still another object of the present invention is to enable remote monitoring by transmitting a web of secondary and tertiary visibility information of a certain period calculated in a specific area, and to correct visibility of a specific area quickly. The present invention provides a measuring system and method thereof.

Technical means according to the present invention for achieving the above object is provided at a predetermined distance from a specific target, the camera for taking a picture of the target image at a predetermined cycle; An illuminance sensor installed at a specific position in a specific region in which the target is fixed and detecting illuminance of a specific position at a predetermined cycle; The image taken by the camera and the light quantity data detected by the illuminance sensor are input, the image is processed and color analyzed by the input image, and reference correction data and correction error data are set in advance. A main server configured to compare and analyze visibility data to calculate primary visibility, and to correct the primary visibility by comparing and analyzing the correction error data and the input light amount; And a network connecting the main server connected to the main server through a communication interface to remotely monitor visibility of a specific area.

In order to achieve the above object, the technical method according to the present invention comprises the steps of: setting reference correction data and correction error data; Photographing an image of a specific target at a predetermined cycle, and detecting illuminance of a specific area in which the target is fixed at a predetermined cycle; Analyzing color by removing noise of the captured image, image processing, and overlaying a reference image; Calculating primary visibility by comparing and analyzing color analysis data and reference visibility data of the image; And comparing the detected amount of light with the correction error data, and correcting the primary correction to calculate the secondary correction.

According to the present invention, more accurate and accurate visibility measurement is possible and the reliability is high.

In addition, it is possible to remotely monitor and collect visibility information for a specific area quickly, and reference correction data and correction error data are set corresponding to the environment such as monthly, time range, weather condition, day / night, etc. More accurate visibility can be measured in a variety of environments, providing high reliability and remotely correcting errors caused by changes in the environment or weather.

In addition, it is possible to communicate with the external main server through the network network, so that it can transmit the actual image through web or internet as well as the correction of a specific area, so it can be usefully used by traffic stations providing traffic status information and Korea Expressway Corporation. In addition, it can be used for various weather services in connection with meteorological equipment based on image processing, and can be used as observation data such as visibility change phenomenon of a specific area or change of visibility change due to weather change.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

2A is a visibility measuring device according to an embodiment, and includes a CCD camera 10, an illumination sensor 20, a noise filter 30, a main server 40, a network 50, and a client 60. do.

The CCD camera 10 is installed in a specific area to measure visibility, photographs a target fixed to a specific area at regular intervals, converts the photographed image into a digital signal, and then changes the main server through the noise filter 20. To send). In addition, it is possible to adjust the pan / tilt / zoom through an input unit (not shown) provided in the CCD camera itself, and also to adjust the pan / tilt / zoom in accordance with the control signal of the main server (40).

The CCD (Charge Coupled Device) converts a wave of light into an electrical signal and converts it into a digital format.The camera is a high-performance camera that has a zoom function and can be freely adjusted up to 1mm in measurement resolution. It is possible to capture images in real time even in a controlled, snowy situation.

In addition, as a countermeasure for the problem of video noise caused by nighttime measurement, this camera is equipped with a high-performance DSP (Digital Signal Process) function to enable automatic focusing, image quality remote control and automatic adjustment, and infrared light recognition (0.001lux). Visibility can be measured without noise at night, and the best image quality (eg focus, color, brightness, sharpness) can be adjusted by day and night classification using image analysis.

Therefore, the measurement error inaccuracy due to scattering due to snow particles, fog, and foreign substances, which are disadvantages of the ultrasonic method, is compensated for, and the measurement error is very small even in the deep snow and dense fog conditions, resulting in high reliability in product structure and performance.

The illuminance sensor 20 is installed in a specific area in which a camera photographing a target is installed, and detects the illuminance of a specific area at regular intervals and transmits the detected data to the main server 40.

The noise filter 30 removes noise of an image photographed by the CCD camera 10 and transmits the noise to the main server 40.

Noise is a phenomenon in which noise is included in an image photographed by a CCD camera, thereby degrading an image quality. In other words, noise is more likely when shooting with a long exposure or high sensitivity without using the flash in a dark place than in a bright place. In particular, the noise phenomenon is particularly affected by the CCD size. The smaller the area occupied by a pixel in a CCD, the more likely the noise is to occur.

The reason for this is that when the CCD size is small, the CCD area occupied by one pixel becomes smaller, and thus the amount of light received is also reduced. Then, the sensor amplifies the signal received by the CCD in order to maintain a constant brightness, and not all pixels receive the same amount of light, so a difference occurs for each pixel in the amplification process. This is what causes noise in the image.

That is, the noise filter (ie, noise reduction) is connected to the CCD camera 10 and removes the noise of the image generated by the above-described software by the internal software method.

The main server 40 inputs the image from which the noise is removed through the noise filter 20 at regular intervals, the amount of light detected by the illuminance sensor 20 at regular intervals, and zoom / pan / tilt of the CCD camera. The controller analyzes the color by image processing the input image and overlaying the processed image and the reference image.

In addition, the main server 40 stores reference correction data and correction error data. When the color of the input image is analyzed at a predetermined period, the primary server 40 compares and analyzes the color analysis data and the reference correction data to calculate the primary correction, and at regular intervals. Comparing and analyzing the input light quantity and the correction error data to correct the primary visibility to calculate and store the secondary visibility, and is stored at regular intervals, but the average calculation of a plurality of successive secondary visibility to calculate and store the third correction.

In addition, the main server 40 sets and stores the captured image as a reference image on a clear day, that is, when the visibility is close to infinity, and the plurality of turbidity emulation images that emulate the turbidity and reference image set arbitrarily by the operator are provided. 4A through 4C, color turbulence analysis is performed by overlaying an arbitrary turbidity emulation image and a reference image, as shown in FIGS. 4A to 4C, and correcting a color corresponding to color analysis data (ie, hue, saturation, luminance, color difference, etc.). The entered reference correction data is stored. In addition, an example of reference visibility data is shown in FIG.

In addition, the main server 40 stores a plurality of light quantity emulation images emulating a plurality of light quantity and a reference image set arbitrarily by the operator, and performs color analysis by overlaying the light quantity emulation image and the reference image, and corrects the color corresponding to the color analysis. Comparing and analyzing the visibility of the reference image and the correction visibility error data for calculating the error corresponding to the amount of light is stored.

In addition, the main server 40 is connected and connected to the network 50, the web server running the web browser by entering the domain name or address of the main server 40 in the address bar to access the image and visibility for a particular region Information may be provided.

2c, the main server 40 includes an A / D converter 41, an image processor 42, a key input unit 43, a controller 44, a memory unit 45, and a communication unit. And a display portion 47.

When the analog signal of the amount of light detected by the illuminance sensor 20 is input, the A / D converter 41 converts the digital signal into a digital signal and transmits it to the controller 44.

The image processor 42 processes the image photographed by the CCD camera 10 and transmits the image to the controller 44.

The key input unit 43 controls the key signal input by the operator when an arbitrary command key signal is input by the operator when the operator arbitrarily instructs a specific operation when setting the reference image, reference visibility data, and visibility error data. Transfer to 44.

For example, when the key input unit 43 sets an image of the image captured by the CCD camera 10 close to infinity (ie, an image taken when the weather is clear) as the reference image, the zoom / It consists of execution keys for specific operations such as tilt / pan, correction of reference images, arbitrary turbidity, and numeric keys for inputting any amount of light.

The control unit 44 is interconnected with the memory unit 45 and stores a corrective analysis program, thereby receiving data necessary for executing the corrective analysis program from the memory unit 45.

That is, when an image processed by the image processor 42 is input, the controller 44 analyzes colors by overlaying the image processed image and the reference image, and compares the analyzed color analysis data and the reference visibility data to the first order. Calculate the visibility, and calculate the secondary visibility by correcting the primary visibility by comparing and analyzing the amount of light inputted from the A / D conversion unit 41 and the correction error data, and averaging a plurality of consecutive secondary visibility 3 The difference visibility is calculated, and the calculated first to third order visibility are transmitted to the memory unit 45.

In addition, if a specific image is selected from the image photographed by the CCD camera 10 through the key input unit 43 and is set as the reference image, the controller 44 of the reference image and the reference image input through the key input unit 43 are selected. When the visibility is transmitted to the memory unit 45, and if any turbidity is input through the key input unit 43, the turbidity and the reference image are emulated to store a plurality of emulation images, and the stored emulation image and the reference image are overlaid. When the color is analyzed and a correction corresponding to color analysis data (ie, hue, saturation, luminance, color difference, etc.) according to a plurality of emulation images is input through the key input unit 43, the reference correction data is set. The visibility data is transmitted to the memory section 45.

Here, the reference visibility data may be formed in plural in correspondence with monthly, hourly, weather conditions, etc., and the visibility is measured by comparing and analyzing the reference visibility data corresponding to the current conditions.

In addition, when a predetermined amount of light is input through the key input unit 43, the input light amount and the reference image are emulated to store a plurality of emulation images, the stored emulation image and the reference image are overlaid, and the color is analyzed. When the visibility correction data corresponding to the amount of light is set by comparing and analyzing the visibility of the reference image, the set correction error data is transmitted to the memory unit 45.

The memory unit 45 may include various types of data transmitted from the control unit 44, that is, reference visibility data, visibility error data, year / month / date / time corresponding to reference image, reference image correction, monthly, hourly, weather condition, and the like. And stored with the visibility, and transmits the stored data corresponding to the control signal of the controller 44 to the controller 44.

The communication unit 46 is connected to the wired / wireless network 50, and when an image and a correction information data request signal of a specific area are input from the external client 60, the communication unit 46 transmits an input signal to the control unit 44, and the control unit. When the corresponding information data is input at (44), the input information data is transmitted to the client 60 through the interconnected network 50.

The display unit 47 displays data corresponding to the instruction control signal of the controller 44, displays an operation screen corresponding to a specific key signal input by the operator, displays an image photographed by a CCD camera, and displays reference correction data. And a data input screen when setting the correction error data.
Although the main server 40 measured the visibility of a zone, the main server 40 may remotely control a plurality of CCD cameras, but may construct a database 220 for storing data and images of the plurality of zones. Through the network 50, the visibility of each region can be comprehensively stored and analyzed, and the visibility and image information for a specific region can be provided through the Internet.

The network 50 is a wired / wireless communication interface that connects and connects the main server 40 and the external client 60. The network 50 transmits the image and visibility information of a specific area stored in the main server 40 to the external client 60. It also provides remote monitoring from outside.

The client 60 is a specific person / specific group server that can remotely monitor the visibility and video of a specific area by accessing the main server 40 through the network 50, that is, the change of visibility or the change of weather in a specific area. It may be a researcher using a correction trend according to the observation data, or a meteorological office providing a meteorological service in connection with meteorological equipment based on image processing, or a traffic broadcasting station (TBS) informing traffic conditions.

In addition, the client 60 may receive a service if a computer is provided without a separate program and a web browser (Internet Explorer, Netscape, etc.) is installed.

delete

Hereinafter, a method of measuring visibility will be described with reference to FIGS. 3A to 3C.

First, reference visibility data and visibility error data for measuring visibility are set.

In more detail, among the images captured by the CCD camera 10, an image of which visibility is close to infinity is set as a reference image (S1-11 and S1-21), and the correction and reference image of the image set as a reference are stored. do.

Next, after a plurality of turbidity is arbitrarily set (S1-12), a plurality of turbidity emulation images are generated and stored by emulating the reference image and the plurality of turbidity (Emulation S1-13).

Here, the reference image can be set as a reference region for image processing by clearly distinguishing an area from the surrounding environment on the screen or by specifying a particularly strong area compared to the surroundings. However, special areas such as objects that emit light or reflect light and moving objects should be excluded.

Next, the plurality of turbidity emulation images and the reference image are overlayed (Overlay S1-14), respectively, and the color is analyzed according to the turbidity (S1-15), and the sampling corresponding to the corrected color data corresponding to the analyzed color data (S1). 16), the reference visibility data is set (S1-17) and stored (S1-18).

Here, the visibility changes depending on the turbidity. The change in visibility means that the chromaticity and saturation of the intrinsic color of the object are changed in color. The visibility analysis using color calculates the spatial difference of colors. It explains in a way.

That is, as the visibility deteriorates, white light is increased due to scattering of aerosol. Therefore, the amount of the red component of each color component is rapidly increased and the blue component tends to be decreased.

In addition, as the visibility worsens, the color difference tends to increase, and the increase in color and saturation difference is caused by aerosol white scattering. When the visibility deteriorates sharply, the color change is largely caused by the decrease in solar radiation. It can be seen that the width rises.

In conclusion, the phenomenon of visibility attenuation is dominated by light scattering phenomenon compared to light absorption phenomenon, and it is used for converting the actual distance of visibility by analyzing statistics on the change propensity between R, G, and B channels.

Therefore, as shown in FIG. 5, the color analysis is a calculation of a change ratio of hue, saturation, and luminance of the emulation image and the reference image, and samples the visibility corresponding to the color difference between the emulation image and the reference image.

Here, the standard visibility data can be set for each month, time zone, and weather condition, and the visibility of a specific zone is measured by applying the standard visibility data corresponding to the current conditions. In addition, the reference correction data corresponding to the monthly and time zones are automatically applied by the main server, and the reference correction data corresponding to the weather conditions are automatically applied according to the control signal of the main server in connection with the meteorological office server (not shown). In addition, the operator may directly input weather conditions to apply reference correction data corresponding to the input conditions.

Next, a plurality of light amounts are arbitrarily set (S1-22), and then a reference image and a plurality of light amounts are emulated (S1-23) to generate and store a plurality of light quantity emulated images.

After that, a plurality of light quantity emulation images and a reference image are overlaid (S1-24), and the color is analyzed (S1-25). The visibility corresponding to the analyzed color data is compared with the visibility of the reference image to calculate the error of the visibility. After (S1-26), the correction error data corresponding to the amount of light is set (S1-27) and stored (S1-28).

As described above, when the reference correction data and the correction error data are set (S1), the CCD camera 10 captures the image of the target fixed to a specific area at a predetermined period (S2) and then removes the noise of the captured image to maintain the main. It transmits to the server 40, and also detects the illuminance of the specific area in which the target is fixed (S2) at a predetermined period (S2) and transmits the detected light amount to the main server.

Next, when the image from which the noise is removed is input to the main server 40, the input image is processed (S3) and then overlayed with the reference image to analyze the color of the image (S4), and the color analysis of the color-analyzed image. The primary visibility is calculated by comparing the data with the reference visibility data (S5).

Next, after comparing and analyzing the amount of light input to the main server 40 and the correction error data, the primary correction is corrected to calculate the secondary correction (S6).

Next, the primary and secondary visibility are stored at regular intervals (S8), but the average of a plurality of successive secondary corrections is calculated to calculate the third correction (S7) and then stored (S8).

In this case, in order to reduce the error caused by the temporary visibility failure due to the floating dust or air flow change, the third operation is averaged, but the average operation is calculated except for the above-described correction. The third correction is calculated.

The main server 40 is connected to the network 50 so as to be able to communicate. When an external main server is connected to the main server 40 through the network 50, the primary to tertiary visibility of a specific zone is established. And the image can be monitored remotely by searching by date / time.

That is, the client 60 may be provided with an image and visibility for a specific region by accessing the domain name or address of the main server 40 in the address bar while driving the web browser.

The present invention is not limited to the above-described embodiments, and various changes can be made by those skilled in the art without departing from the gist of the present invention as claimed in the following claims.

As described in detail above, the present invention calculates the first correction by capturing a target in a specific area with a CCD camera having an improved resolution and then analyzing image processing and colors, and comparing and analyzing the amount of light detected by the illumination sensor. By calculating the secondary visibility which correct | amended the error of primary visibility, it can measure more accurately and precisely.

In addition, by calculating a third order correction, which is stored at a constant period but averaging a plurality of consecutive second sights, more accurate and accurate visibility measurement is possible, and thus the reliability is high.

In addition, remote monitoring is possible by sending the secondary and tertiary visibility information of a certain period calculated in a specific area on the web, so that the visibility information for a specific area can be collected quickly, and monthly, time range, and weather conditions. The standard correcting data and correcting error data are set according to the environment such as star, day / night, etc., so it is possible to measure more accurate correctiveness in various environments, and it is highly reliable. You can calibrate manually.

In addition, it is possible to communicate with the external main server through the network network, so that it can transmit the actual image through web or internet as well as the correction of a specific area, so it can be usefully used by traffic stations providing traffic status information and Korea Expressway Corporation. In addition, it can be used for various weather services in connection with meteorological equipment based on image processing, and can be used as observation data such as visibility change phenomenon of a specific area or change of visibility change due to weather change.

Claims (10)

A camera installed at a predetermined distance from a specific target to photograph the target image at a predetermined cycle; An illuminance sensor installed at a specific position in a specific region in which the target is fixed and detecting illuminance of a specific position at a predetermined cycle; The image taken by the camera and the light quantity data detected by the illuminance sensor are input, the image is processed and color analyzed by the input image, and reference correction data and correction error data are set in advance. A main server configured to compare and analyze the visibility data to calculate a primary visibility, and to correct the primary visibility by comparing and analyzing the correction error data and light quantity data input by the illumination sensor; A network for allowing a client connected to the main server through a communication interface to remotely monitor visibility of a specific area; The main server Overlapping a plurality of emulation images emulating a reference image with a plurality of turbidity and light quantity with the reference image and analyzing the color and storing the corresponding correction as reference correction data, and comparing the reference correction data and the light quantity data A visibility measurement device, characterized in that one correction error data is stored. delete delete delete In the method of measuring visibility, Setting reference visibility data and visibility error data; Photographing an image of a specific target at a predetermined cycle, and detecting illuminance of a specific area in which the target is fixed at a predetermined cycle; Analyzing color by removing noise of the captured image, image processing, and overlaying a reference image; Calculating primary visibility by comparing and analyzing color analysis data and reference visibility data of the image; Calculating a second correction by comparing the detected amount of light data with the correction error data and correcting the first correction; Setting the reference visibility data; A user arbitrarily setting and storing a reference image; Generating a plurality of images by emulating the reference image and the plurality of turbidities after arbitrarily setting the plurality of turbidities; Analyzing a color by overlaying the plurality of turbidity emulation images and a reference image; And And setting reference visibility data corresponding to the visibility corresponding to the analyzed plurality of color data. delete delete delete delete delete

Images