KR102595467B1 - Information analysis system using image and method thereof - Google Patents

Abstract

The information analysis system using images according to an embodiment disclosed in this document acquires identification information of a vehicle entering a reference area, adjusts the irradiation angle of light by controlling the lighting unit based on the identification information of the vehicle, and adjusts the irradiation angle of the light to the vehicle. It may include a data processing unit configured to determine whether the vehicle violates traffic laws by analyzing an image captured together with the light of the lighting unit when passing the reference area.

Description

Information analysis system using images and methods related thereto{INFORMATION ANALYSIS SYSTEM USING IMAGE AND METHOD THEREOF}

Embodiments disclosed in this document relate to an information analysis system and method using images.

To analyze traffic information, technology is being used to analyze images taken of roads through cameras. For example, this video analysis technology can capture images of vehicles that violate various traffic laws, such as vehicles that violate traffic signals, speeding vehicles, and vehicles that violate parking, and conduct crackdowns based on the captured images.

Meanwhile, in the event of a traffic accident or sudden stop on the road, the risk of an accident can vary significantly depending on whether a seat belt is worn, so it is important to encourage drivers or passengers to wear seat belts. However, today, due to coatings on vehicle windows, etc., it is difficult to determine whether a seat belt is worn by simply capturing images of the vehicle with a camera.

Therefore, there is a need for technology to more reliably and easily determine whether drivers and passengers are wearing seat belts based on image analysis technology.

Embodiments disclosed in this document determine whether the driver and passengers of the vehicle are wearing seat belts by controlling the light irradiation angle of the lighting for vehicle image taking in consideration of the angle or height of the windshield depending on the type or specifications of the vehicle. The purpose is to provide an information analysis system and method for obtaining vehicle images that can be judged more accurately and easily.

In addition, the embodiments disclosed in this document determine whether the cause of the seat belt not being detected in the image is not wearing a seat belt, a system error, or environmental factors (e.g., the position of the sun, type of coating film on the windshield of the vehicle). The purpose is to provide an information analysis system and method using video that can secure reliability when analyzing video to determine whether or not a seat belt should be worn by determining whether the problem is with the video itself.

The technical problems of the embodiments disclosed in this document are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the description below.

The information analysis system using images according to an embodiment disclosed in this document acquires identification information of a vehicle entering a reference area, adjusts the irradiation angle of light by controlling the lighting unit based on the identification information of the vehicle, and adjusts the irradiation angle of the light to the vehicle. It may include a data processing unit configured to determine whether the vehicle violates traffic laws by analyzing an image captured together with the light of the lighting unit when passing the reference area.

According to one embodiment, the data processing unit may be set to select one of a plurality of light sources having different light irradiation angles included in the lighting unit based on identification information of the vehicle.

According to one embodiment, the data processing unit obtains specification information of the vehicle that matches the identification information of the vehicle, and based on the identification information of the vehicle, a plurality of light sources with different light irradiation angles included in the lighting unit You can select one of the options and adjust the angle of the selected light source to correspond to the specification information of the vehicle.

According to one embodiment, the identification information of the vehicle may include at least one of the vehicle model and vehicle number of the vehicle.

According to one embodiment, the specification information of the vehicle may include information about the angle of the windshield provided in the vehicle.

According to one embodiment, the specification information of the vehicle may include at least one of information about the height of a windshield provided in the vehicle or information about the size of the vehicle.

According to one embodiment, the data processing unit causes errors that occur when determining whether the vehicle violates traffic laws based on the position of the sun while the vehicle passes the reference area and the shadow created by the vehicle. can be judged.

According to one embodiment, the information analysis system using images may further include a sensor unit that detects a change in the position of the sun over time.

According to one embodiment, the data processing unit may determine the type of film provided in the vehicle using the image of the vehicle and determine the cause of the error based on the type of film.

A method of operating an information analysis system using an image according to an embodiment disclosed in this document includes the steps of obtaining vehicle identification information of a vehicle entering a reference area, and controlling the lighting unit based on the vehicle identification information to determine the light irradiation angle. It may include the step of adjusting and determining whether the vehicle violates traffic laws by analyzing an image taken together with the light of the lighting unit when the vehicle passes the reference area.

The information analysis system and related method using images according to an embodiment disclosed in this document controls the light irradiation angle of the lighting for vehicle image shooting by considering the angle or height of the windshield that is different depending on the type or specification of the vehicle. By doing so, it is possible to more accurately and easily determine whether the driver and passengers of the vehicle are wearing seat belts.

In addition, the information analysis system and related method using images according to an embodiment disclosed in this document determine whether the cause of seat belt failure in the image is not wearing a seat belt, a system error, or the vehicle image itself due to environmental factors. By determining whether it is a problem, reliability can be secured when analyzing images to determine whether a seat belt is worn.

In addition, the information analysis system and method using video according to an embodiment disclosed in this document can provide various traffic-related services by collecting vehicle and pedestrian traffic information, traffic law violation information, and crime prevention information. .

1 is a diagram for explaining the operation of an information analysis system using images according to an embodiment disclosed in this document.
Figure 2 is a block diagram showing the configuration of an information analysis system using images according to an embodiment disclosed in this document.
Figure 3 is a flowchart showing the overall operation of the information analysis system using images according to an embodiment disclosed in this document.
Figure 4 is a flowchart showing an error determination operation of an information analysis system using images according to an embodiment disclosed in this document.
FIG. 5 is a diagram illustrating front glass images for each sun position of an object obtained in an information analysis system using images according to an embodiment disclosed in this document.
Figure 6 is a diagram showing front glass images for each film type of an object acquired in an information analysis system using images according to an embodiment disclosed in this document.
Figure 7 is a flowchart showing an information analysis method using images according to an embodiment disclosed in this document.

Hereinafter, various embodiments disclosed in this document will be described in detail with reference to the attached drawings. In this document, the same reference numerals are used for the same components in the drawings, and duplicate descriptions for the same components are omitted.

With respect to the various embodiments disclosed in this document, specific structural and functional descriptions are merely illustrative for the purpose of explaining the embodiments, and the various embodiments disclosed in this document may be implemented in various forms. It should not be construed as limited to the described embodiments.

Expressions such as “first,” “second,” “first,” or “second” used in various embodiments may modify various elements regardless of order and/or importance, and refer to the elements as It is not limited. For example, a first component may be renamed a second component without departing from the scope of the embodiments disclosed in this document, and similarly, the second component may also be renamed to the first component.

Terms used in this document are merely used to describe specific embodiments and may not be intended to limit the scope of other embodiments. Singular expressions may include plural expressions, unless the context clearly indicates otherwise.

All terms used herein, including technical or scientific terms, may have the same meaning as generally understood by a person of ordinary skill in the technical field of the embodiments disclosed in this document. Terms defined in commonly used dictionaries can be interpreted as having the same or similar meaning as the meaning they have in the context of related technology, and unless clearly defined in this document, they are not interpreted in an ideal or excessively formal sense. . In some cases, even terms defined in this document cannot be interpreted to exclude embodiments disclosed in this document.

1 is a diagram for explaining the operation of an information analysis system using images according to an embodiment disclosed in this document.

Referring to FIG. 1, the information analysis system 100 using images according to an embodiment disclosed in this document includes a lighting unit 110, a data processing unit 140, an object detection unit 160, and a photographing unit 170. can do. The lighting unit 110, data processing unit 140, object detection unit 160, and imaging unit 170 are installed in specific areas (e.g., intersections, alleys, tunnels, or highways) to capture and analyze images. It may also be referred to as the ‘information acquisition department’.

The photographing unit 170 may include a camera capable of capturing images. The object detection unit 160 is a sensor (e.g., radar (radio detection)) that detects an object, such as a vehicle (e.g., 0b1) or a person, and measures the position or movement distance of the object by tracking the movement of the object. and ranging (RADAR), light detection and ranging (LIDAR), and laser detection and ranging (LADAR). Depending on embodiments, the information analysis system 100 may use the photographing unit 170 and the object detection unit 160 cooperatively. For example, the information analysis system 100 may preferentially use the object detection unit 160 to more accurately detect the moving position, distance, direction, or speed of an object, and when it is necessary to identify the shape of the object. The imaging unit 170 can be used. According to an embodiment, the photographing unit 170 and the object detection unit 160 may be implemented as one integrated module.

The data processing unit 140 may obtain traffic information through at least one of the photographing unit 170 or the object detection unit 160. ‘Traffic information’ may include, for example, road images. In addition, traffic information includes vehicle images, number of vehicles, vehicle's driving speed, vehicle's driving direction, vehicle's driving lane, vehicle's travel distance, vehicle's traffic volume, vehicle's waiting length, vehicle's occupancy rate, pedestrian image, pedestrian's It may further include at least one of number, walking speed, or walking direction. Additionally, the passage information may include identification information including at least one of the vehicle model, type, color, size, driving lane, license plate number, or appearance of a pedestrian.

In addition to traffic information, the data processing unit 140 may obtain at least one of behavior information or crime prevention information through the photographing unit 170. 'Behavior information' includes speeding violations, red light violations, driving on the wrong side of the road, lane violations, cutting in, lane violations, stop line violations, violation of old diesel vehicle operation restrictions, weight restrictions, failure to wear seat belts, illegal parking, pedestrian violation of traffic signals, or unauthorized use. This may mean an act that violates traffic laws, such as crossing, or an act that requires guidance from the driver, such as improper loading or violation of truck rest periods. ‘Crime prevention information’ may include at least one of life crime prevention information or traffic crime prevention information. In addition, the data processing unit 140 can use traffic information to detect events such as vehicle stopping, vehicle accidents, appearance of pedestrians/wild animals, falling objects, road kill, landslides, fog, or potholes.

Although not shown in FIG. 1, the data processing unit 140 may detect an event through data acquired from at least one sensor in addition to the photographing unit 170 and the object detection unit 160. For example, the data processing unit 140 includes an acceleration sensor for detecting impacts on the road, a positioning sensor for detecting landslides on slopes adjacent to the road, a temperature/humidity sensor for detecting weather changes such as temperature/humidity, and a load sensor. An event may be detected based on data received from at least one of a motion detection sensor for detecting a kill or an acoustic sensor.

The data processing unit 140 applies an artificial intelligence (AI)-based image analysis/processing algorithm such as deep learning or machine learning to generate traffic information, behavior information, crime prevention information, or event information. You can obtain at least one of the following. In one embodiment, the data processing unit 140 analyzes the image acquired by the photographing unit 170 or enters the reference area (AR) of the object (Ob1) moving in the specified direction (F) through the object detection unit (160). /Can detect whether it passes or not. When the data processing unit 140 detects that the object Ob1 enters the reference area AR (i.e., the point at which it passes L1 in FIG. 1) through the object detection unit 160, the data processing unit 140 detects the object through the photographing unit 170. Traffic information of (Ob1) can be obtained. For example, the data processing unit 140 may use an image of the object Ob1, identification information, or driving information (e.g., driving speed, driving direction of the vehicle, driving lane of the vehicle, distance traveled by the vehicle, traffic volume of the vehicle, At least one of waiting length and vehicle occupancy rate can be obtained. Additionally, the data processing unit 140 according to an embodiment disclosed in this document may obtain specification information of the object Ob1 that matches the identification information of the object Ob1. For example, the specification information of the object Ob1 may include size information of the object Ob1 (e.g., length, height, width, etc. of the object Ob1) and angle information of the front glass of the object Ob1. You can. Additionally, the specification information of the object 0b1 may further include height information of the front glass of the object Ob1. At this time, the specification information of the object Ob1 may be stored in the database of the information analysis system 100 using images or may be received from an external server (eg, operating device 50).

The lighting unit 110 may irradiate light to the object Ob1. The lighting unit 110 may be implemented as part of the photographing unit 170 or may be implemented as a separate device from the photographing unit 170. The photographing unit 170 can control the lighting unit 110 to emit light when capturing an image. Due to the light emitted during image capture, the photographing unit 170 can capture images of an object (e.g., a vehicle) even at night, and when capturing images, the vehicle's windshield (or vehicle coating film attached to the windshield) can be filmed. Transmittance may increase. When the transmittance increases, the photographing unit 170 can capture images inside the vehicle. In FIG. 1, the lighting unit 110 is shown as having a single light source, but the lighting unit 110 may include a plurality of light sources installed at different angles in different positions. The lighting unit 110 may include a lighting driver (or lighting control unit) that can adjust the irradiation angle of light of the lighting unit 110 based on a signal received from the data processing unit 140.

When the object 0b1 passes the reference area AR (or passes L2), the data processing unit 140 displays the image of the object 0b1 illuminated by light through the lighting unit 110, such as not wearing a seat belt. Traffic law violation behavior of the object (0b1) can be detected. At this time, the data processing unit 140 can adjust the light irradiation angle by controlling the lighting unit 110 based on the identification information of the object 0b1 (e.g., vehicle type such as large (bus)/small car (passenger car)). , Additionally, the light irradiation angle can be more finely adjusted by controlling the lighting unit 110 based on the specification information of the object Ob1. For example, the data processing unit 140 may select a light source (lighting unit) that matches the identification information of the object Ob1 and adjust the angle of the selected light source according to specification information. At this time, the lighting control unit of the lighting unit 110 may adjust the angle of the lighting unit 110 to correspond to the height of the object 0b1 and the angle of the front glass based on the signal received from the data processing unit 140. Through this, the data processing unit 140 causes the lighting unit 110 to illuminate the front glass of the object 0b1 at the point when the object 0b1 passes through the reference area AR (i.e., when it passes L2 in FIG. 1), i.e. The angle can be controlled so that light is irradiated to the driver and passengers. When light is irradiated to the object 0b1 by the lighting unit 110, the photographing unit 170 can capture an image of the object 0b1. Accordingly, a user (eg, an operator of the operating device 50) can determine whether the driver and passenger of the object 0b1 are wearing seat belts based on the captured image of the object 0b1. In addition, the information analysis system 100 using an image according to an embodiment disclosed in this document determines whether the object 0b1 is speeding or violates a signal based on the image of the object 0b1 captured by the photographing unit 170. You can control them together.

Additionally, the data processing unit 140 according to an embodiment disclosed in this document can detect the cause of errors that may occur when determining traffic law violations through images. In this case, the data processing unit 140 may measure the exact position of the sun based on the sensor unit (eg, solar tracker) and the length and direction of the shadow, and then determine an error according to the sun's position. Additionally, the data processing unit 140 may determine the type of film provided in the object 0b1 through the image and determine an error according to the type of film based on this.

In one embodiment, the information analysis system 100 using images may further include an operating device 50. The operating device 50 (e.g., control center) may be operated by a public institution such as a local government, road construction company, facility corporation, or police agency. The operating device 50 stores and manages the information acquired through the data processing unit 140 in a database, and the user (e.g., traffic control agent) of the operating device 50 controls the road situation in real time using the stored information. You can output the interface that can be used. Additionally, the operating device 50 can compensate for the insufficient hardware performance of the data processing unit 140. For example, the data processing unit of the operating device 50 may include hardware (eg, GPU) that can implement image processing at a higher performance than the data processing unit 140. The data processing unit of the operating device 50 may perform the same functions as the data processing unit 140, including analysis of road conditions (e.g., traffic information, crime prevention information, or event information). In this case, the data processing unit 140 included in the traffic information acquisition unit can be removed or deactivated. The operating device 50 may transmit a command to the data processing unit 140 to control signals or lighting units or provide a different route to the vehicle based on the analyzed road situation.

Figure 2 is a block diagram showing the configuration of an information analysis system using images according to an embodiment disclosed in this document. The configurations described below may be implemented as hardware devices, or may be implemented as software such as instructions and programs. Referring to FIG. 2, the information analysis system 100 using images according to an embodiment disclosed in this document includes a lighting unit 110, a data processing unit 140, an object detection unit 160, a photographing unit 170, and a sensor unit. It may include (180). Hereinafter, components having the same names and reference numbers as those in FIG. 1 may have the same or similar functions as the components described in FIG. 1.

The lighting unit 110 may irradiate light to an object passing through the reference area. At this time, the lighting unit 110 may be configured in a tilt structure and may include a single light source or a plurality of light sources installed at different locations and irradiating light to the object at different angles.

The data processing unit 140 may obtain passage information of an object entering the reference area. In this case, the data processing unit 140 may obtain at least one of object identification information and object specification information matching the identification information. At this time, the data processing unit 140 obtains specification information stored in a database (not shown) provided in the information analysis system 100 using images, or obtains object identification information and object identification information from an external server (e.g., operating device 50). You can receive matching specification information. For example, the object specification information may include information about the size of the object (eg, length, height, width, etc.) of the object and information about the angle of the front glass provided on the object.

The data processing unit 140 may acquire an image of an object passing through a reference area and determine whether the object violates traffic laws based on the acquired image. In this case, the data processing unit 140 may determine whether the object violates a signal, speeds, or violates the wearing of a seat belt based on the image of the object. When the lighting unit 110 irradiates light, the data processing unit 140 may control the light irradiation angle of the lighting unit 110 so that the light irradiation angle is appropriate for the vehicle model or specification information.

Meanwhile, when the lighting unit 110 includes a plurality of light sources. The data processing unit 140 may select one of a plurality of light sources based on object identification information. For example, the plurality of light sources may include a light source for a large vehicle and a light source for a small vehicle, and since the vertical light incident angle on the windshield is different for a large vehicle and a small vehicle, the data processing unit 140 You can select a light source that matches your vehicle model. Even for the same vehicle type, the angle or height of the windshield may be different depending on the vehicle specifications, so in the embodiment, the data processing unit 140 uses the specification information to adjust the angle of the light source selected based on the object identification information in a more detailed manner by tilting it. can be adjusted accordingly.

The data processing unit 140 may determine the cause of an error that occurs when determining whether a traffic law is violated based on the position of the sun while the object passes through the reference area and the shadow created by the object. In this case, the data processing unit 140 calculates the exact position of the sun by considering the position of the sun measured by the sensor unit 180 and the length and direction of the shadow of the object or the driver or passenger riding the object in the image. can do. For example, the data processing unit 140 may determine whether an error has occurred in the acquired image of the object due to the influence of backlight or direct light. Additionally, the data processing unit 140 may determine the type of film provided on the object using the image of the object. At this time, the data processing unit 140 may determine the cause of the error based on the type of film. For example, the data processing unit 140 may determine whether the film provided on the object is a reflective film or an absorptive film based on the image of the object. In this way, the data processing unit 140 can determine the cause of an image analysis error by considering factors such as factors depending on the position of the sun or the type of film provided on the object. Therefore, the accuracy and reliability of the information analysis system 100 using images can be secured.

The object detection unit 160 can detect an object entering the reference area. For example, the object detection unit 160 may be radar or lidar. Additionally, there may be one or more object detection units 160.

The photographing unit 170 may photograph an object entering or passing through the reference area. At this time, the photographing unit 170 may capture images of the object at the time when the object enters and when it passes through the reference area. Additionally, the photographing unit 170 may be equipped with a light source (eg, lighting unit 110) for photographing. For example, the photographing unit 170 may be a camera. When a light source installed at a light irradiation angle corresponding to the vehicle type is selected by the data processing unit 140, the photographing unit 170 may control the lighting unit 110 to emit light through the selected light source. Additionally, the photographing unit 170 may control the lighting unit 110 to emit light through a light source selected and finely adjusted by the data processing unit 140.

The sensor unit 180 can detect changes in the sun's position over time. For example, the sensor unit 180 may be a solar tracker that tracks the position of the sun. In this case, the sensor unit 180 can predict the position of the sun by storing the sensing value of CdS (cadmium sulfide) every hour.

In this way, the information analysis system 100 using images according to an embodiment disclosed in this document controls the angle of lighting according to the specifications of the vehicle, thereby more accurately and easily determining whether the driver and passengers of the vehicle are wearing seat belts. You can judge.

In addition, the information analysis system 100 using images according to an embodiment disclosed in this document determines image analysis errors based on the position of the sun and the type of vehicle coating film, thereby providing reliability when analyzing images regarding violation of seat belt wearing. can be secured.

Figure 3 is a flowchart showing the overall operation of the information analysis system using images according to an embodiment disclosed in this document.

Referring to FIG. 3, the data processing unit 140 may first detect the entry of an object into the reference area through the object detection unit 160 (S101). For example, the object may be a vehicle. Additionally, the data processing unit 140 may detect identification information of the object through the photographing unit 170 when the object enters (S102).

Then, the data processing unit 140 may match the identification information of the detected object with the specification information of the object stored in advance (S103). For example, the data processing unit 140 may obtain vehicle specification information (e.g., length, height, width of the vehicle, angle of the windshield) corresponding to the vehicle model or vehicle number of the object detected through the image. there is.

Next, the data processing unit 140 may adjust the angle of the lighting unit 110 to correspond to the vehicle identification information or specification information (S104). For example, when the lighting unit 110 is composed of a plurality of light sources, the data processing unit 140 selects one light source among the plurality of light sources based on identification information (e.g., vehicle model) and then selects the light source based on the specification information. You can control the angle of the light source. In another implementation, the data processing unit 140 may adjust the angle of the lighting unit 110 after the object passes the reference area.

The data processing unit 140 may detect that an object passes the reference area through the object detection unit 160 (S105). At this time, the data processing unit 140 may detect the object's identification information again based on the image of the object captured at the time of passage of the object. When a light source installed at a light irradiation angle corresponding to the vehicle type is selected by the data processing unit 140, the photographing unit 170 may control the lighting unit 110 to emit light through the selected light source. Additionally, the photographing unit 170 may control the lighting unit 110 to emit light through a light source selected and finely adjusted by the data processing unit 140.

The data processing unit 140 may analyze the image of the object (S106). In this case, the data processing unit 140 can determine whether the object violates traffic laws by analyzing whether the object is speeding, violating a traffic signal, or wearing a seat belt through the image (S107).

Meanwhile, if it is not determined whether traffic regulations are violated, the data processing unit 140 may perform an error determination (S108). For example, when a seat belt is not detected through an image, the data processing unit 140 needs to check whether the driver is not actually wearing a seat belt or whether the seat belt is not detected due to a specific factor. In this case, the data processing unit 140 may check whether the occupant is detected if the seat belt is not detected, and may determine that an environmental factor exists if the occupant is not detected. Environmental factors may include, for example, factors depending on the position of the sun or factors depending on the type of film of the object.

The data processing unit 140 may generate data according to the result of determining whether traffic laws are violated (S109). For example, when non-wearing of a seat belt is detected through video analysis including the windshield ('Yes' in operation S107), the data processing unit 140 identifies the relevant violation information (seat belt not being worn) and the vehicle corresponding to the violation information. Enforcement data containing information (e.g., at least one of vehicle model or vehicle number) may be generated. For another example, if it is not detected whether the seat belt is worn ('No' in operation S107), the data processing unit 140 may generate data regarding the determined error through operation S108.

The data processing unit 140 may transmit the generated data to the operating device 50. The user (or operator) of the operating device 50 can know whether a vehicle is controlled based on the data received from the data processing unit 140 or check the details of errors that appear during the video analysis process.

Figure 4 is a flowchart showing an error determination operation of an information analysis system using images according to an embodiment disclosed in this document.

Referring to FIG. 4, the data processing unit 140 according to an embodiment disclosed in this document may track the position of the sun using the sensor unit 180 when determining an error (S201). At this time, the sensor unit 180 may store the sun's position measurements for each time zone.

Additionally, the data processing unit 140 may detect the position of the sun based on the length and direction of the shadow appearing in the image (S202). In this case, the data processing unit 140 can predict the position of the sun based on the length and direction of the shadow of an object (eg, a vehicle) in the image or the shadow of the object's driver or passenger. In this way, the data processing unit 140 can accurately detect factors due to the sun's position (eg, backlight, direct light) based on the sun's position measurement by the sensor unit 180 and shadow analysis through the image.

Additionally, the data processing unit 140 may determine the type of film provided on the object based on the front glass image of the object (S203). For example, the data processing unit 140 may determine that in an image of an object, if the front glass reflects all the light, it is a reflective film, and if it absorbs all the light, it can be determined that it is an absorptive film.

Next, the data processing unit 140 may determine errors that occurred during image analysis by considering factors due to the position of the sun and factors due to the type of film of the object (S204). Therefore, the information analysis system 100 using images according to an embodiment disclosed in this document can determine environmental factors related to seat belt detection and perform error determination to secure accuracy and reliability of the system.

FIG. 5 is a diagram illustrating front glass images for each sun position of an object obtained in an information analysis system using images according to an embodiment disclosed in this document. In addition, Figure 6 is a diagram showing front glass images for each film type of an object acquired in an information analysis system using images according to an embodiment disclosed in this document.

5 (a) and (b) respectively show backlight (for example, when sunlight enters from the opposite side of the photographing unit 170) and direct light (for example, when sunlight enters the rear of the photographing unit 170). (if coming from). Additionally, Figures 6 (a) and (b) show images of a reflective film and an absorptive film, respectively.

Referring to Figures 5 (a) and (b), the sensor unit 180 (eg, solar tracker) may store the CdS sensing value every hour. In this way, the data processing unit 140 predicts the position of the sun based on the sensing value stored by the sensor unit 180 for the time when the object passes the reference area, and identifies the object and the driver or passenger in the image of the object at that time. The exact position of the sun can be obtained by additionally detecting the length and direction of the shadow. Through this, it is possible to determine errors according to the position of the sun and identify the cause (for example, backlight or direct light) that makes image analysis impossible.

That is, the data processing unit 140 may determine an error due to backlight or direct light in the case of an image in which the outline or interior is transparent but the interior is not clearly visible, such as the images in (a) and (b) of Figures 5. Additionally, the data processing unit 140 may perform learning for error determination by post-processing the determined image after determining an error according to the position of the sun. The data processing unit 140 may perform error determination according to the sun position based on the learned image.

Referring to (a) and (b) of FIGS. 6, the data processing unit 140 may determine the type of film provided on the object (eg, vehicle) from the acquired image. For example, in the case of vehicle films, there are usually two types: reflective films and absorbent films, and these films each have different effects. In other words, as shown in (a) of Figure 6, in the case of a reflective film, all light is reflected and the background affects the image of the windshield of the vehicle, and as shown in (b) of Figure 6, the absorptive film In this case, light can be absorbed, causing the image on the vehicle's windshield to appear black.

In this way, the information analysis system 100 using an image according to an embodiment disclosed in this document determines the position of the sun based on the sensor unit 180 and the shadow analysis of the image, and detects the type of film provided in the vehicle. When analyzing images of whether the driver and passengers are wearing seat belts, the cause of the error can be accurately analyzed and reliability can be secured.

Figure 7 is a flowchart showing an information analysis method using images according to an embodiment disclosed in this document.

Referring to FIG. 7, the information analysis system 100 may obtain identification information of a vehicle entering the reference area (S310). Additionally, the information analysis system 100 may further obtain specification information matching the identification information.

Additionally, the information analysis system 100 can adjust the irradiation angle of light by controlling the lighting unit 110 based on the vehicle identification information (S320). Additionally, the information analysis system 100 can adjust the irradiation angle of light by controlling the lighting unit 110 to correspond to the specification information of the object. Through this, the lighting unit 110 can accurately irradiate light to the windshield of a vehicle passing through the reference area.

Meanwhile, in step S320, when the lighting unit 110 includes a plurality of light sources. The information analysis system (e.g., data processing unit 140) may select one of a plurality of light sources based on the vehicle identification information and adjust the angle of the selected light source to correspond to the vehicle specification information. For example, the plurality of light sources may be installed so that the light incident angles on the windshields of the large vehicle and the small vehicle are vertical, respectively. That is, in step S320, the information analysis system 100 selects a light source according to the obtained identification information and then finely adjusts the angle of the selected light source to correspond to the specification information.

Next, the information analysis system 100 can determine whether the vehicle violates traffic laws by analyzing the image captured along with the light from the lighting unit 110 when the vehicle passes the reference area.

Meanwhile, although not shown in FIG. 7, the information analysis system 100 according to an embodiment disclosed in this document can determine the cause of errors that occur in the process of determining traffic law violations. In this case, the information analysis system 100 determines the cause of the error based on the type of film provided on the vehicle using the position of the sun while the vehicle passes through the reference area, the shadow created by the vehicle, and the image of the vehicle. can do. Since this is described in FIGS. 5 and 6, detailed description will be omitted.

As such, the information analysis method using images according to an embodiment disclosed in this document can more accurately and easily determine whether the driver and passengers of the vehicle are wearing seat belts by controlling the angle of lighting according to the vehicle type. there is.

In addition, the information analysis method using images according to an embodiment disclosed in this document determines errors based on the position of the sun and the type of vehicle coating film, thereby securing reliability when analyzing images related to seat belt violations. .

In the above, just because all the components constituting the embodiments disclosed in this document are described as being combined or operated in combination, the embodiments disclosed in this document are not necessarily limited to these embodiments. That is, as long as it is within the scope of the purpose of the embodiments disclosed in this document, all of the components may be operated by selectively combining one or more of them.

In addition, terms such as “include,” “comprise,” or “have” described above mean that the corresponding component may be present, unless specifically stated to the contrary, and thus do not exclude other components. Rather, it should be interpreted as being able to include other components. All terms, including technical or scientific terms, have the same meaning as generally understood by a person of ordinary skill in the technical field to which the embodiments disclosed in this document belong, unless otherwise defined. Commonly used terms, such as terms defined in dictionaries, should be interpreted as consistent with the contextual meaning of the relevant technology, and should not be interpreted in an idealized or overly formal sense unless explicitly defined in this document.

The above description is merely an illustrative explanation of the technical idea disclosed in this document, and those skilled in the art in the technical field to which the embodiments disclosed in this document belong will understand without departing from the essential characteristics of the embodiments disclosed in this document. Various modifications and variations will be possible. Accordingly, the embodiments disclosed in this document are not intended to limit the technical idea of the embodiments disclosed in this document, but rather to explain them, and the scope of the technical idea disclosed in this document is not limited by these embodiments. The scope of protection of the technical ideas disclosed in this document shall be interpreted in accordance with the claims below, and all technical ideas within the equivalent scope shall be interpreted as being included in the scope of rights of this document.

Claims (15)

Obtain identification information of the vehicle entering the reference area,
Obtaining specification information of the vehicle that matches identification information of the vehicle,
By controlling the lighting unit based on the identification information of the vehicle, the irradiation angle of light is adjusted to correspond to the specification information of the vehicle, and by analyzing the image captured with the light of the lighting unit when the vehicle passes the reference area, It includes a data processing unit set to determine whether the vehicle violates traffic laws,
An information analysis system using images, wherein the vehicle specification information includes information about the angle of the windshield provided in the vehicle. The method of claim 1, wherein the data processing unit,
An information analysis system using images, configured to select one of a plurality of light sources with different light irradiation angles included in the lighting unit based on the identification information of the vehicle. The method of claim 1, wherein the data processing unit,
Selecting one of a plurality of light sources with different light irradiation angles included in the lighting unit based on the identification information of the vehicle,
An information analysis system using images that adjusts the angle of the selected light source to correspond to the specification information of the vehicle. In claim 2 or 3,
An information analysis system using an image in which the identification information of the vehicle includes at least one of the vehicle model and vehicle number. delete In claim 4,
An information analysis system using images wherein the specification information of the vehicle includes at least one of information about the height of the windshield provided in the vehicle or information about the size of the vehicle. The method of claim 1, wherein the data processing unit,
An information analysis system using images that determines the cause of errors that occur when determining whether the vehicle violates traffic laws based on the position of the sun while the vehicle passes the reference area and the shadow created by the vehicle. In claim 7,
An information analysis system using images further comprising a sensor unit that detects changes in the position of the sun over time. The method of claim 1, wherein the data processing unit,
An information analysis system using images that determines the type of film provided in the vehicle using the image of the vehicle and determines the cause of the error based on the type of film. In claim 1,
An information analysis system using an image further comprising an object detection unit that detects a vehicle entering the reference area. In claim 1,
An information analysis system using video, further comprising a photographing unit for photographing the video. The method of claim 11, wherein the imaging unit,
An information analysis system using images that controls the lighting unit so that the lighting unit, the angle of which is adjusted by the data processing unit, irradiates light. The method of claim 11, wherein the data processing unit,
An information analysis system using video set to obtain at least one of traffic information, behavior information, and crime prevention information through the photographing unit. In claim 13,
An information analysis system using images further comprising an operating device set to control road conditions through information acquired through the photographing unit and the data processing unit. In the method of operating an information analysis system using images,
Obtaining vehicle identification information of a vehicle entering the reference area;
Obtaining specification information of the vehicle matching identification information of the vehicle;
adjusting the irradiation angle of light to correspond to the specification information of the vehicle by controlling the lighting unit based on the identification information of the vehicle; and
A step of determining whether the vehicle violates traffic laws by analyzing an image captured together with the light of the lighting unit when the vehicle passes the reference area,
A method of operating an information analysis system, wherein the vehicle specification information includes information about the angle of a windshield provided in the vehicle.

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