Traffic control using video information, monitoring and enforcement methods and systems for moving objects

Abstract

The present invention relates to a method and system for traffic control, monitoring of moving objects, and enforcement using image information. A method for traffic control, monitoring of moving objects, and enforcement using image information according to one embodiment of the present invention comprises: a traffic management step in which a traffic management module evaluates the presence or absence of a moving object or a stationary object that has encroached upon a predetermined first boundary area and a second boundary area based on information collected from a first camera; an image collection step in which, if a boundary area encroachment signal occurs in the traffic management step, the traffic management module specifies the location of the encroached boundary area and collects and combines image information capturing the boundary area where the encroachment occurred from one or more cameras linked to the first camera; a first evaluation step in which a traffic law violation reporting module processes the image information collected in the image collection step to generate analysis information and evaluates whether a traffic law violation has occurred by analyzing the analysis information according to a predetermined standard; and a warning step in which, if evaluated as a traffic law violation in the first evaluation step, a warning signal is output to the collected image information and the moving object or stationary object on a display. If evaluated as a traffic law violation in the first evaluation step, the collected video information, the analysis information, and the evaluation information of the traffic law violation reporting module are transmitted to an administrator terminal, and the second evaluation step in which the traffic law violation status is evaluated at the administrator terminal is included. The present invention controls abnormal driving of vehicles, motorcycles, electric scooters, etc., and deviant behavior of pedestrians, and integrates and analyzes collected information to enable effective monitoring and enforcement of traffic law violations, thereby establishing road safety and traffic order.

Description

Technology Field

[0001] The present invention relates to a method and system for traffic control, monitoring of moving objects, and enforcement using image information. More specifically, it enables traffic control to prevent traffic accidents, identification and monitoring of moving objects, and effective enforcement by utilizing image information acquired at an intersection where a crosswalk exists. Through this, the invention provides a method and system capable of preventing traffic accidents and enhancing pedestrian safety. Background Technology

[0002] Recently, as the penetration rate of mobile vehicles increases and urban areas expand, traffic congestion has become commonplace, causing massive economic losses. Consequently, various efforts are being made to resolve this, such as constructing new roads or expanding existing ones; however, these methods not only require substantial financial resources but also have limitations that make it difficult to resolve the issue in the short term.

[0003] Furthermore, the types of means of transportation, or mobility devices, have recently been diversifying explosively. Consequently, the movement paths of these devices have become complex and difficult to predict, leading to frequent occurrences of accidents and traffic law violations that differ from simple traffic accidents between vehicles and pedestrians.

[0004] Meanwhile, intersections are the most frequent sites for traffic violations compared to other roads, as the connection of lanes with different driving directions leads to a high concentration of conflicts between moving objects and pedestrians. These violations include speeding, violations of bus lanes and shoulder lanes, signal violations, lane violations, intersection traffic rules, lane violations, U-turn violations, and tailgating, resulting in the most common occurrence of collision accidents.

[0005] Accordingly, various studies are being conducted to manage intersection traffic flow by establishing unmanned enforcement systems and traffic information collection systems at intersections.

[0006] In particular, with the recent expansion of wireless communication infrastructure and the refinement of detection sensor technology, Information & Communication Technology (ICT) has been introduced to integrate traffic information management, enabling real-time monitoring of traffic conditions at intersections.

[0007] In managing such intersections, the most important functions are classified into the function of collecting traffic information and the function of cracking down on violating moving objects.

[0008] However, conventionally, traffic information collection systems and enforcement systems for cracking down on violating moving objects were operated separately. Consequently, information detected by each system was transmitted to different information processing systems to produce data tailored to specific purposes, which not only prevented the integrated management of valid information but also resulted in the haphazard installation of system components at intersections, degrading urban aesthetics and increasing installation and operating costs. Furthermore, there are certain limitations in monitoring, managing, and enforcing regulations while reflecting the characteristics of the rapidly increasing variety of mobility devices.

[0009] Furthermore, the independent operation method of each system, as in conventional technology, presents a problem in that single-purpose camera systems will continue to be added to roads in the future, making integrated management of information more difficult, increasing costs associated with the continuous installation of single-purpose systems, and causing greater difficulties in maintaining and managing the additionally installed hardware.

[0010] Therefore, there is an urgent need for a traffic monitoring system capable of managing integrated information by comprehensively performing functions such as traffic signal violation enforcement, traffic information collection, and crime prevention. Prior art literature

[0011] (Patent Document 0001) KR 10-1372843 B1(Patent Document 0002) KR 10-1216641 B1 The problem to be solved

[0012] The present invention aims to provide a method and system for traffic control, monitoring, and enforcement of moving objects using image information, in order to prevent pedestrian accidents within crosswalks at intersections.

[0013] The present invention is intended to enable the detection of various moving objects, including two-wheeled vehicles, and to enable monitoring and enforcement thereof, thereby allowing for the control and prevention of problems related to traffic law violations and traffic accidents caused by the rapidly increasing variety of mobility devices.

[0014] The present invention is intended to control abnormal driving of vehicles, motorcycles, electric scooters, etc., and deviant behavior of pedestrians, and to enable effective monitoring and enforcement of traffic law violations by integrating and analyzing collected information, thereby establishing road safety and traffic order.

[0015] The present invention is intended to perform monitoring to prevent violations and accidents by monitoring the movement and stopping areas of various mobility devices and pedestrians, and to extend the maintenance cycle by applying a contamination-resistant lens to the camera for this purpose, thereby ensuring that the excellent image quality of acquired footage is consistently maintained regardless of external environmental conditions such as weather or seasons. means of solving the problem

[0016] To achieve the objective of the present invention, a method for traffic control, monitoring of moving objects, and enforcement using image information according to an embodiment of the present invention comprises: a traffic management step in which a traffic management module evaluates the presence or absence of a moving object or a stationary object that has encroached upon a predetermined first boundary area and a second boundary area based on information collected from a first camera; an image collection step in which, when a boundary area encroachment signal occurs in the traffic management step, the traffic management module specifies the location of the encroached boundary area and collects and combines image information capturing the boundary area where the encroachment occurred from one or more cameras linked to the first camera; a traffic law violation reporting module processes the image information collected in the image collection step to generate analysis information and evaluates whether a traffic law violation has occurred by analyzing the analysis information according to a predetermined standard; and a warning step in which, if evaluated as a traffic law violation in the first evaluation step, a warning signal is output to the collected image information and the moving object or stationary object on a display. If evaluated as a traffic law violation in the first evaluation step, the collected video information, the analysis information, and the evaluation information of the traffic law violation reporting module are transmitted to an administrator terminal, and the second evaluation step in which the traffic law violation status is evaluated at the administrator terminal is included.

[0017] The first camera is installed at a location where the movement path of moving objects on the road, including vehicles and pedestrians, can be collected, and one or more cameras linked to the first camera may be cameras already installed around the first camera.

[0018] The first boundary area above may be an arbitrary boundary area set to control moving bodies including vehicles centered on a crosswalk, and the second boundary area may be an arbitrary boundary area set to control moving bodies including pedestrians centered on a crosswalk.

[0019] The above analysis information may include specific information regarding the classification of moving or stationary objects based on predetermined criteria derived from video information in the traffic violation reporting module.

[0020] In the first evaluation step, if an intrusion by a moving object or a stationary object onto the first boundary area is evaluated, and if a stationary object for pedestrian crossing is evaluated to exist on the second boundary area, the caution warning step may be to output a caution signal toward the stationary object.

[0021] One or more of the first camera or one or more cameras linked to the first camera may have an anti-contamination coating layer formed on the camera lens.

[0022] A traffic control, monitoring of moving objects, and enforcement system using image information according to another embodiment of the present invention may include: a server; a communication unit capable of transmitting and receiving data; a traffic management module that evaluates the presence or absence of a moving object or a stationary object that has encroached upon a predetermined first boundary area and a second boundary area based on information collected from a first camera, specifies the location of the encroached boundary area when a boundary area encroachment signal occurs, and collects and combines image information captured from one or more cameras linked to the first camera that captures the boundary area where the encroachment occurred; a traffic violation reporting module that processes the image information collected from the camera to generate analysis information, and evaluates whether a traffic law has been violated by analyzing the analysis information according to a predetermined standard; a display that receives a signal from the traffic violation reporting module and outputs a warning signal to the collected image information and the moving object or stationary object; and an administrator terminal that receives the collected image information, the analysis information, and the evaluation information from the traffic violation reporting module, and transmits an evaluation signal regarding whether a traffic law has been violated.

[0023] A non-transient computer-readable medium according to another embodiment of the present invention is a non-transient computer-readable medium that stores instructions, and the instructions may cause the processor to perform the method when executed by the processor. Effects of the invention

[0024] To prevent pedestrian accidents within a crosswalk at an intersection, the present invention provides a method and system for traffic control, monitoring and enforcement of moving objects using image information.

[0025] The present invention enables the detection of various moving objects, including two-wheeled vehicles, and allows for monitoring and enforcement thereof, thereby enabling the control and prevention of problems related to the rapidly increasing variety of mobility devices and the resulting traffic law violations and traffic accidents.

[0026] The present invention controls abnormal driving of vehicles, motorcycles, electric scooters, etc., and deviant behavior of pedestrians, and integrates and analyzes collected information to enable effective monitoring and enforcement of traffic law violations, thereby establishing road safety and traffic order.

[0027] The present invention performs monitoring to prevent violations and accidents by monitoring the movement and stopping areas of various mobility devices and pedestrians, and applies a contamination-resistant lens to the camera for this purpose to extend the maintenance cycle and ensure that the excellent image quality of the acquired footage is consistently maintained regardless of external environmental conditions such as weather or season. Brief explanation of the drawing

[0028] FIG. 1 illustrates a flowchart of a method for traffic control, monitoring of moving objects, and enforcement using image information according to an embodiment of the present invention. FIG. 2 illustrates a control unit according to one embodiment of the present invention. FIG. 3 illustrates the concept of a method for traffic control, monitoring of moving objects, and enforcement using image information according to an embodiment of the present invention. FIG. 4 illustrates the setting of a boundary area according to one embodiment of the present invention. Specific details for implementing the invention

[0029] The present invention will be described in detail below with reference to the drawings. The embodiments described below are provided as examples to ensure that the concept of the present invention is sufficiently conveyed to a person skilled in the art. Accordingly, the present invention is not limited to the embodiments described below and may be embodied in other forms. Furthermore, in the drawings, the size and thickness of the device, etc., may be exaggerated for convenience. Throughout the specification, the same reference numerals indicate the same components.

[0030] The advantages and features of the present invention and the methods for achieving them will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below but may be implemented in various different forms. These embodiments are provided merely to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention, and the present invention is defined only by the scope of the claims. Throughout the specification, the same reference numerals refer to the same components. In the drawings, the sizes and relative sizes of layers and regions may be exaggerated for clarity of description.

[0031] The module referred to in this invention includes all forms that can be operated by a person skilled in the art, such as those that perform a specific function in hardware or perform a function in software on a processor.

[0032] A method for traffic control, monitoring of moving objects, and enforcement using image information according to an embodiment of the present invention comprises: a traffic management step (S1) in which a traffic management module (301) evaluates the presence or absence of a moving object or a stationary object that has encroached upon a predetermined first boundary area and a second boundary area based on information collected from a first camera (111); an image collection step (S2) in which, when a boundary area encroachment signal occurs in the traffic management step (S1), the traffic management module (301) specifies the location of the encroached boundary area and collects and combines image information captured from one or more cameras (112) linked to the first camera (111) that capture the boundary area where the encroachment occurred; and a traffic law violation reporting module (302) processes the image information collected in the image collection step (S2) to generate analysis information, and evaluates whether a traffic law violation has occurred by analyzing the analysis information according to a predetermined standard. If evaluated as a traffic law violation in the first evaluation step, a warning step (S4) for outputting a warning signal to the video information collected on the display (400) and to the moving object or stationary object; and if evaluated as a traffic law violation in the first evaluation step (S3), a second evaluation step (S5) for transmitting the collected video information, the analysis information, and the evaluation information of the traffic law violation reporting module (302) to the administrator terminal (500) and receiving an evaluation of whether there is a traffic law violation at the administrator terminal (500).

[0033] The term "vehicle" as used in this invention is not limited to conventional automobiles and includes two-wheeled vehicles, electric scooters, bicycles, and all other mobility devices that a person can ride and move on.

[0034] The above traffic management step (S1) is capable of managing and controlling traffic on general roads or pedestrian walkways, and primarily involves monitoring traffic control and traffic law violations centered on points where pedestrians and mobility intersect.

[0035] In the above traffic management step (S1), the type and location of the camera installed in the first camera (111) may be arbitrarily set according to the area being managed. Additionally, the boundary area refers to an arbitrary area set based on image information collected by the first camera (111), and includes all ranges that a person of ordinary skill can set for traffic monitoring or for analyzing or collecting evidence of traffic law violations, and is not specifically limited.

[0036] The first boundary area above may be an arbitrary boundary area set to control moving bodies including vehicles centered on a crosswalk, and the second boundary area may be an arbitrary boundary area set to control moving bodies including pedestrians centered on a crosswalk.

[0037] Through the first boundary area mentioned above, an analysis of whether a vehicle encroaches upon pedestrian protection centered on the crosswalk and the resulting possibility of accidents or violations of traffic laws can be conducted. Additionally, the second boundary area mentioned above can monitor matters that compromise traffic safety, such as pedestrian jaywalking or vehicle encroachment on pedestrian paths, or analyze violations of traffic laws.

[0038] Referring to Fig. 4, furthermore, if necessary, the distance between the crosswalk and the vehicle stop line—that is, an area on the road extended by about 1m from the crosswalk—can be set as the first preliminary boundary area. By setting the above preliminary boundary area, the movement and abnormal behavior of moving objects can be effectively identified and warnings can be given in advance, thereby increasing the preventive effect against traffic accidents.

[0039] In addition, a second preliminary boundary area may be established between the second boundary area and the first preliminary boundary area as needed. Through this, violations such as jaywalking by deviating partially or entirely from the crosswalk, encroachment of moving objects on the pedestrian path, or illegal parking can be effectively detected, and accidents resulting therefrom can be prevented.

[0040] In the above image collection step (S2), the intrusion of a moving object, including a pedestrian or mobility object, into a boundary area is determined based on information collected from the camera (110) and the occurrence of intrusion is analyzed. The analysis involves identifying the moving object through image analysis and classifying the intrusion or pre-intrusion stage within the boundary area to generate analysis information. The specific analysis tool or method is not specifically limited and includes all means that a person skilled in the art can select and apply for image analysis.

[0041] The camera (112) linked to the first camera is configured to be linked within a certain area range among the existing cameras installed with the first camera (111) as the center, and there may be multiple cameras (112) linked to the first camera. Through this, video information captured from various angles can be collected based on specific location information where an intrusion occurred, and the accuracy of the analysis can be increased.

[0042] In the present invention, a traffic law violation is first analyzed according to a pre-set range through the first evaluation stage (S3), and a final evaluation is received through the administrator terminal (500) in the second evaluation stage (S5) to make a final judgment on whether there is a traffic law violation. Administrative processing regarding traffic law violations must be carried out by a person analyzing the relevant laws and based on the final result. However, since administrative work may become excessive if all collected data is analyzed by a person through the administrator terminal (500), it is important to provide effective filtering. Therefore, the present invention proceeds with the first evaluation stage (S3) before the second evaluation stage (S5), and achieves the effect of preventing administrative work from becoming excessive by increasing the accuracy of the first evaluation stage (S3).

[0043] In the first evaluation step (S3) above, information collected from the first camera (111) and the camera (112) linked to the first camera is processed. Specifically, a certain area within the range specified as where an intrusion has occurred, centered on the boundary area, is image-analyzed from various angles. Through this, analysis information is generated, and for example, the analysis information may include the type of moving object, movement speed, intrusion area, intrusion range, intrusion range time, index information based on a predetermined risk index, and information on relevant laws and regulations where violations are expected. The specific analysis method and the classification of items in the analysis information are not particularly limited and include all matters that a person skilled in the art can select and apply.

[0044] Preferably, the present invention includes an image module (303), wherein the image module (303) may apply an image filter to image information collected from the first camera (111) or a camera (112) linked to the first camera to extract moving object information and license plate information. Image processing through the application of an image filter is not particularly limited, but details regarding image processing, which is an effect of the present invention, will be described later.

[0045] The above warning step (S4) refers to a step of outputting warning information to prevent secondary accidents to pedestrians or occupants of mobility, and outputting information including some or all of the collected video information and analysis information to a display (400) according to a predetermined standard to prevent additional accidents of moving objects or stationary objects.

[0046] The above second evaluation step (S5) allows for verification by the manager to proceed as a preliminary step to the final administrative disposition through the manager terminal (500), and the specific method is not particularly limited.

[0047] The first camera (111) is installed at a location where the movement path of moving objects on the road, including vehicles and pedestrians, can be collected, and one or more cameras (112) linked to the first camera may be cameras already installed around the first camera (111). Through this, some of the linked cameras (112) are selected around a specific location, and the accuracy of the analysis can be increased by collecting image information from various angles through the selected linked cameras (112).

[0048] The above analysis information may include specific information regarding the classification of moving or stationary objects based on predetermined criteria in the traffic law violation reporting module (302) based on video information.

[0049] In the first evaluation step (S3), if an intrusion by a moving object or a stationary object onto the first boundary area is evaluated and a stationary object for pedestrian crossing is evaluated to exist on the second boundary area, the warning step may be such that a warning signal is output toward the stationary object.

[0050] One or more cameras (110) among the first camera (111) or one or more cameras (112) linked to the first camera may have an anti-contamination coating layer formed on the camera lens.

[0051] Since the above camera (110) must be installed and operated mainly outdoors, it is inevitably exposed to sources of pollution for a long time due to environmental factors such as seasonal factors on the road, weather, and road factors such as exhaust fumes and dust, and low-grade collisions and vibrations caused by moving objects on the road and pedestrian walkway occur irregularly.

[0052] Accordingly, in order to stably collect high-quality images from a camera (110) including a first camera (111) or one or more cameras (112) linked to the first camera, it is important to apply a coating layer to the camera lens to improve water resistance, stain resistance, and durability. That is, since the present invention analyzes monitoring and traffic law violations based on image information, stably collecting high-quality images is very important in terms of the accuracy of analysis. Therefore, when the above coating layer is applied, the maintenance cycle of the camera (110) can be extended, and high-quality images can be stably collected.

[0053] Specifically, the lens included in the camera (110, 111, 112) may have a coating layer formed on its surface by coating it with a coating composition comprising a compound represented by the following chemical formula 1, phenyltrimethoxysilane, a colloidal silica organic solvent, and a dispersant.

[0054] [Chemical Formula 1]

[0055]

[0056] Since the lens coated with the above coating composition and having the coating layer formed thereon has excellent durability, stain resistance, and water resistance, it is possible to stably collect high-quality information according to the performance of the camera (110) set, even if it is exposed for a long period of time to an external environment or an environment with high contamination and frequent vibrations, such as the space where the camera (110) is installed in the present invention.

[0057] When the above-mentioned colloidal silica is used, a fine inorganic coating layer is formed on the lens surface, thereby improving physical strength and stain resistance. Additionally, when the above-mentioned phenyltrimethoxysilane is used, a stable coating layer is formed with the above-mentioned colloidal silica, thereby achieving the effect of improving overall physical properties such as durability, stain resistance, and water resistance.

[0058] The above organic solvent is selected from the group consisting of methyl ethyl ketone (MEK), toluene, benzene, alcohol, and mixtures thereof, and preferably, alcohol may be used, but is not limited thereto.

[0059] As the above-mentioned dispersant, a polyester-based dispersant may be used, and specifically, TEGO-Disperse 670 (Manufacturer: EVONIK), a polyester-based dispersion stabilizer composed of a copolymer of 2-methoxypropyl acetate and 1-methoxy-2-propyl acetate, may be used, but is not limited to the above examples and any dispersant obvious to a person skilled in the art may be used without limitation.

[0060] The above coating composition may additionally include a stabilizer as an additional additive, and the stabilizer may include a UV absorber, an antioxidant, etc., but is not limited to the above examples and can be used without limitation.

[0061] Preferably, the coating composition may comprise 2 to 7 parts by weight of a compound represented by Formula 1, 0.1 to 2 parts by weight of colloidal silica, 0.1 to 1 part by weight of phenyltrimethoxysilane, and 0.1 to 1 part by weight of a dispersant, based on 100 parts by weight of an organic solvent. According to the above range, not only can a stable coating layer be formed on the lens surface of the camera (110), but a coating layer exhibiting excellent durability, stain resistance, and water resistance can also be formed compared to cases outside the above range.

[0062] 1. Preparation Example: Preparation of a coating layer

[0063] In order to confirm the physical properties of the coating layer formed according to the coating composition of the present invention, a coating composition was prepared according to the composition shown in Table 1 below. In Table 1 below, A is a compound represented by the above chemical formula 1, B is 4-Dimethylamino-4'-nitrostilbene, C is colloidal silica, and D is phenyltrimethoxysilane. In the above composition, the solvent (U) was entirely ethanol, and in each example, the dispersant was 2-methoxypropyl acetate mixed at 1 part by weight per 100 parts by weight of U.

[0064] Te1 Te2 Te3 Te4 Te5 Te6 U 100 100 100 100 100 100 A 1 2 5 7 10 - B - - - - - 5 C 0.1 0.5 1 2 3 1 D 0.01 0.1 0.5 1 2 0.5

[0065] (Unit: parts by weight)

[0066] Te1 to Te6 were each applied to the lens surface and then sufficiently cured to form a coating layer on the lens surface.

[0067] 2. Experimental Example: Evaluation of Physical Properties

[0068] 2-1. Appearance Evaluation of the Coating Layer

[0069] The coating layers formed using the above Te1 to Te6 were evaluated for appearance to confirm whether a homogeneous coating layer was formed on the surface. For the evaluation, coating layers were formed on three lenses for each coating composition, and an examiner evaluated each lens. The evaluation was conducted by assigning 3 points if a uniform coating layer was formed on all three lenses, 2 points if a uniform coating layer was formed on two of the three lenses, 1 point if a uniform coating layer was formed on one of the three lenses, and 0 points if a non-uniform coating layer was formed on all lenses. The results are shown in Table 2 below.

[0070] Te1 Te2 Te3 Te4 Te5 Te6 Appearance evaluation 0 3 3 3 1 2

[0071] (Unit: exponent)

[0072] Referring to Table 2 above, it can be seen that a uniform coating layer is formed when using Te2 to Te4. On the other hand, Te1 and Te5 were evaluated as being uneven with a single point, which is disadvantageous in terms of overall yield. This is in terms of process and production yield, and the most homogeneous coating layer can be formed when using Te2 to Te4.

[0073] 2-2. Durability Evaluation

[0074] The durability of the formed coating layer was confirmed through scratch resistance evaluation (TF) and temperature resistance evaluation (TH). This evaluates whether the coating layer can be stably maintained in an environment exposed to the outside. Specifically, for the scratch resistance evaluation, a tester applied friction with a plastic bar with the same force to each coating layer to observe whether scratches formed. For the temperature resistance evaluation, the physical changes occurring in the coating layer formed on the lens were evaluated after performing temperature changes three times: cooling to 0°C, rapidly heating to 60°C, and then cooling again. Each result was evaluated using an index from 1 to 10 by comparing them with the Te6 result fixed at index 5. The results are shown in Table 3 below. In Table 3 below, for each index, a higher number indicates superior durability.

[0075] Te1 Te2 Te3 Te4 Te5 Te6 TF 1 6 9 8 3 5 TH 5 6 9 9 2 5

[0076] (Unit: exponent)

[0077] Referring to Table 3 above, it can be seen that the coating layer of Te1 has poor physical durability. Additionally, it can be seen that Te5 is vulnerable to physical and temperature fluctuations. On the other hand, it can be seen that Te2 to Te4 exhibit excellent physical and temperature fluctuations, and in particular, the stability of the formed coating layer is very superior compared to Te6.

[0078] 2-3. Stain Resistance Evaluation

[0079] A lens having a coating layer formed according to Te1 to Te6 above was attached to a model camera, and the model camera was attached to a moving object for 3 days and then exposed to a general road driving environment. As a comparative example (Con), the same lens without a coating layer was used. Subsequently, an evaluator assessed the degree of contamination of the lens before and after the test. For objective comparative evaluation, the result of con was fixed at index 1, and compared with this, it was expressed as an index from 1 to 10. Meanwhile, the higher the number of the index, the better the contamination resistance.

[0080] before Te1 Te2 Te3 Te4 Te5 Te6 Contamination resistance evaluation 1 3 7 9 9 1 3

[0081] (Unit: exponent)

[0082] Referring to Table 4 above, it can be seen that, on the other hand, the synergistic effect of the coating layer on anti-fouling properties is low for Te1, Te5, and Te6. For Te2 to Te4, it was confirmed that dust adhesion is significantly reduced due to the uniform coating layer. In particular, for Te3 and Te4, it was confirmed that the synergistic effect on durability is greatly increased and the resistance to vibration is excellent.

[0083] Therefore, when using a lens with a coating layer formed according to Te3 to Te4, the maintenance cycle can be maintained for a very long period regardless of the external environment in which the camera (110) is installed.

[0084] 2-4. Water Resistance Evaluation

[0085] In order to evaluate water resistance according to the coating layer according to Te1 to Te6 above, the water repellency angle was measured for each lens with a coating layer formed. For objective evaluation, a lens without a coating layer was set as 'con' and evaluated in comparison. In particular, before evaluating the water repellency angle, a certain level of contamination and scratching was applied by hand, and then water was sprayed. If a water layer formed on the hydrophilic layer or pinning of water droplets was observed, it was evaluated as X, and if not, as O.

[0086] Con Te1 Te2 Te3 Te4 Te5 Te6 Water repellency evaluation X X O O O X O

[0087] Referring to Table 5 above, it can be seen that water resistance is improved when using Te2 to Te4 and Te6. Therefore, using the above ranges has the advantage of allowing data to be collected stably without affecting images or images when exposed to humid or moisture-containing environments, and making management easy.

[0088] In particular, when using Te2 to Te4, the coating layer is formed uniformly and stably overall, and physical properties are improved across the entire range of durability, stain resistance, and water resistance. Therefore, the system according to the present invention has the great advantage of being able to be applied indoors, outdoors, and in various other environments, as well as being very easy to manage and allowing the management cycle to be set long.

[0090] Meanwhile, the image module (230) described above may apply an image filter to image information collected from the camera (110) to extract moving object information and license plate information.

[0091] The above image filter may be subject to the following [Equation 1]. The following [Equation 1] is intended to change the arrangement structure of pixels of the collected image to optimize it, thereby transforming the overall image shape so that it is collected as a consistent image, and thus allows for the analysis of specific moving object information, the movement information of the moving object, and the license plate information of the moving object. Furthermore, based on the image information collected by applying the above image filter, matters such as driving route violations, failure to wear a helmet, and driving speed violations may be learned by an artificial neural network and applied to the enforcement module (220) so that the enforcement stage for the two-wheeled vehicle proceeds based on the learned information.

[0092] [Equation 1]

[0093]

[0094] (In Equation 1 above, x is the original image, x' is the transformed image, S is the scaling ratio, θ represents the rotation value)

[0095] Equation 1 above is based on affine transformation, which allows for maintaining pixel values ​​while keeping the overall image structure consistent by changing the pixel arrangement structure. Therefore, when applying Equation 1 above, it is possible to perform evaluation and analysis through rotation and scaling of the collected images, or to perform data transformation for the CNN processing, thereby eliminating image distortion caused by errors arising from lens curvature or the angle of the installed camera.

[0096] In addition, the following [Equation 1-1] may be applied to the image to which the above [Equation 1] is applied.

[0097] [Equation 1-1]

[0098]

[0099] (In the above Equation 1-1, RED, GREN, and BLUE are extracted RGB values, (a, b, and c are values ​​between 0.1 and 0.3, and for offset, a value selected between -10 and 10)

[0100] In the case where the video or image collected from the camera (110, 111, 112) or other additionally collected and merged image, such as CCTV video, is a multi-channel image, if the algorithm of [Equation 1-1] is applied, it can be converted into a single-channel image to reduce the width of the data and further increase the computation and learning speed.

[0101] In Equation 1-1 above, each RGB value is determined, and the arithmetic mean is calculated by multiplying the RGB values ​​by a pre-set variable value. If necessary, an offset is applied to convert the image into a single-channel image of the color desired by the user. In particular, the offset is determined within a range between -10 and 10. If the offset is outside this range, an excessive effect may occur, which may result in a significant degradation of the quality of the converted data.

[0102] Preferably, c in the above [Equation 1-1] may be determined by the following [Equation 1-2].

[0103] [Equation 1-2]

[0104]

[0105] When the above [Equation 1-2] is applied, a, b, and c in the above [Equation 1-1] are all determined to be values ​​of 0.3 or less, thereby maintaining the distinction between each color as much as possible, and the effect of significantly increasing the association and learning speed of the image after conversion can be achieved.

[0107] Meanwhile, preferably, the image filter may have gamma correction according to [Equation 2] below applied to images or images collected from a camera (400) or images or images applied for CNN learning.

[0108] [Equation 2]

[0109]

[0110] [Equation 2-1]

[0111]

[0112] (In the above Equations 2 and 2-1, Input and output represent the input and output values ​​for the brightness of the photograph, a, b, c, and d are values ​​ranging from 0.1 to 10, and r is a setting constant value that sets inputr to 0.1 to 10.)

[0113] Generally, failing to correct image contrast leads to problems such as degraded CNN training results or reduced detection or object extraction effects in images analyzed based on the trained results. Therefore, a certain range of contrast correction is applied to the collected images. While commonly used image contrast correction methods can utilize coefficients and gamma-squared values ​​in the input data, this can result in image distortion caused by mechanically constructed non-linear transfer functions.

[0114] Therefore, when applying the above [Equation 2] and [Equation 2-1], clearer results can be obtained from the CNN operation if the luminosity and brightness are pre-corrected and maintained to a constant level for data processing before starting the CNN on the collected images. In particular, as the offset is set according to [Equation 2-1], the light intensity can be corrected by non-linearly reflecting it without distortion of the image.

[0115] More preferably, the offset in [Equation 2] may be derived from [Equation 2-2] below.

[0116] [Equation 2-2]

[0117]

[0118] (In Equation 2-2 above, a is 0.1 to 10, and r is a setting constant value that causes inputr to be set to 0.1 to 10 in Equation 2.)

[0119] When the above [Equation 2-2] is applied, the offset for the nonlinear function can be configured in the shape of a double-humped camel. Through this, the recognition rate of objects based on general contrast correction can be significantly increased, and the effect of removing distortion in object recognition and extraction based on contrast correction can be achieved.

[0120] Preferably, an algorithm according to [Equation 3] below may be applied to extract the target of analysis from the image.

[0121] [Equation 3]

[0122]

[0123] (In Equation 3 above, σ T = Variance of the total pixel distribution, σ W = Variance within two classes (clusters), σ b = It is the variance between classes, and μ 1(t) is the mean value of cluster 1, μ 2(t) is the mean value of cluster 2. Also, ω 1(t) is the number of pixels included in cluster 1 out of the total pixels, and ω 2(t) is the number of pixels in cluster 2 out of the total pixels.

[0124] By applying the above [Equation 3], black and white pixels in the acquired image can be clearly distinguished. In particular, when the above [Equation 3] is applied, σ W Minimize and σ bThe value that maximizes can be set as the reference value, and the image can be changed to black and white around the reference value. Accordingly, the entire photo pixels are divided into pixel clusters (black, white), and for each cluster, the mean, variance, etc. are used to clearly distinguish white pixels as white and black pixels as black pixels, so that the background other than the object can be easily removed, allowing the target to be extracted and analyzed from the collected image to be clearly classified and identified.

[0125] 3. Algorithm Evaluation

[0126] CNN learning was applied to identical images that were specifically classified and collected, and based on this, the ability to extract specific objects from the images being evaluated was assessed. Cases where each algorithm was partially applied were classified to evaluate the recognition rate of the target specific object. As a comparative example (CB), the affine transformation according to Equation 1 was applied identically, and corresponding to [Equation 1-1], the grayscale was applied as OUTPUT=[RED+GREEN+BLUE] / 3 according to conventional technology, and no gamma correction corresponding to [Equation 2] or binarization correction corresponding to Equation 3 was performed. In addition, to evaluate the synergistic effect according to the algorithms applied in the present invention, U1 was obtained by applying [Equation 1-2], [Equation 2], and [Equation 2-2], and U2 was obtained by additionally applying [Equation 3] to U1. At this time, to verify the degree of improvement in object identification and recognition rate according to the application of each algorithm, the improvement information compared to the results of the above CB was evaluated as an index and is shown in [Table 6] below.

[0127] CB U1 U2 improvement rate index 1 1.24 1.33

[0128] Referring to [Table 6] above, it can be seen that when the algorithm according to the present invention is applied, the degree of extraction and recognition matching of objects within the collected images is improved. Therefore, it becomes possible to clearly recognize and identify specific targets or objects through the images collected from the cameras (110, 111, 112).

[0129] Therefore, based on the collected images, more accurate enforcement information can be provided through the enforcement module, and the enforcement stage can be effectively carried out through the aforementioned learning results.

[0130] A non-transient computer-readable medium according to another embodiment of the present invention is a non-transient computer-readable medium that stores instructions, and the instructions may cause the processor to perform the method when executed by the processor.

[0131] The present invention can be modeled as computer-readable code on a medium on which a program is recorded. Computer-readable media include all types of recording devices in which data readable by a computer system is stored. Examples of computer-readable media include Hard Disk Drives (HDDs), Solid State Disks (SSDs), Silicon Disk Drives (SDDs), ROMs, RAMs, CD-ROMs, magnetic tapes, floppy disks, optical data storage devices, etc. Accordingly, the above detailed description should not be interpreted restrictively in all respects and should be considered exemplary. The scope of this specification should be determined by a reasonable interpretation of the appended claims, and all modifications within the equivalent scope of this specification are included within the scope of this specification.

[0132] A traffic control, monitoring of moving objects, and enforcement system using image information according to another embodiment of the present invention comprises: a server (10); a communication unit (100) capable of transmitting and receiving data; a traffic management module (301) that evaluates the presence or absence of a moving object or a stationary object that has encroached upon a predetermined first boundary area and a second boundary area based on information collected from a first camera (111), specifies the location of the encroached boundary area when a boundary area encroachment signal occurs, and collects and combines image information of the boundary area where the encroachment occurred from one or more cameras (112) linked to the first camera (111); a traffic violation reporting module (302) that processes image information collected from a camera (110) to generate analysis information, and evaluates whether a traffic law has been violated by analyzing the analysis information according to a predetermined standard; and a display (400) that receives a signal from the traffic violation reporting module and outputs a warning signal to the collected image information and the moving object or stationary object. It may include an administrator terminal (500) that receives collected video information, the analysis information and the evaluation information of the traffic law violation reporting module (302), and transmits an evaluation signal regarding whether there is a traffic law violation.

[0133] The system according to the present invention may include a processor, memory, and a communication module (or communication device). The method may be performed through this.

[0134] To explain by example, a processor can control other components by executing instructions stored in memory. The processor can execute instructions stored in memory.

[0135] A processor is a component capable of performing calculations and controlling other devices. By processing signals, data, and information input or output through the components examined above, or by running applications stored in memory, the processor can provide or process appropriate information or functions for the user.

[0136] Each of the above components is as described above, and the traffic control, monitoring of moving objects, and enforcement system using the above-mentioned image information is not limited to the above components, nor are the types of each component specifically limited. Therefore, each component may be arbitrarily set or applied according to the choice of a person skilled in the art, and additional components may be combined.

[0137] Although preferred embodiments of the present invention have been described above, the present invention may use various variations, modifications, and equivalents. It is clear that the present invention can be applied in the same way by appropriately modifying the above embodiments. Therefore, the above description does not limit the scope of the present invention, which is defined by the limitations of the following claims. Explanation of the symbols

[0138] 10: Server 20: Database 100: Communications Department 110: Camera 111: First camera 112: Camera linked to the first camera 300: Control unit 301: Traffic Management Module 302: Traffic Violation Reporting Module 303: Image Module 400: Display 500: Administrator terminal

Claims

Claim 1 A traffic management step in which the traffic management module evaluates the presence or absence of a moving object or a stationary object that has encroached upon a predetermined first boundary area and a second boundary area based on information collected from a first camera; an image collection step in which, if a boundary area encroachment signal occurs in the traffic management step, the traffic management module specifies the location of the encroached boundary area and collects and combines image information capturing the boundary area where the encroachment occurred from a plurality of cameras linked to the first camera; a first evaluation step in which the traffic law violation reporting module processes the image information collected in the image collection step to generate analysis information and evaluates whether a traffic law violation has occurred by analyzing the analysis information according to predetermined criteria based on the analysis information; a warning step in which, if evaluated as a traffic law violation in the first evaluation step, the collected image information, the analysis information, and the evaluation information of the traffic law violation reporting module are transmitted to an administrator terminal, and from the administrator terminal The method includes a second evaluation stage in which a violation of traffic laws is evaluated; wherein the first camera is installed at a location where the movement path of moving objects on the road, including vehicles and pedestrians, can be collected; wherein a plurality of cameras linked to the first camera are cameras already installed around the first camera; wherein the first boundary area is an arbitrary boundary area set to control moving objects, including vehicles, centered on a crosswalk; wherein the second boundary area is an arbitrary boundary area set to control moving objects, including pedestrians, centered on a crosswalk; wherein in the first evaluation stage, an intrusion by a moving object or a stationary object onto the first boundary area is evaluated, and if it is evaluated that a stationary object for walking on the crosswalk exists on the second boundary area, the warning stage outputs a warning signal toward the stationary object.The above traffic management step includes a step of additionally setting a first preliminary boundary area, including the gap between the crosswalk and the vehicle stop line, based on video information collected from the first camera, to identify and warn of the movement and abnormal behavior of moving objects; and a step of additionally setting a second preliminary boundary area between the second boundary area and the first preliminary boundary area to detect jaywalking where a pedestrian deviates from part or all of the crosswalk, encroachment of moving objects on the pedestrian path, or illegal parking; in the above video collection step, regarding the encroachment of a moving object including a pedestrian or mobility into the boundary area, the encroachment value is determined based on information collected from the camera and the occurrence of encroachment is analyzed; the analysis is performed by identifying the moving object through image analysis and classifying the encroachment or preliminary encroachment stage within the boundary area to generate analysis information; in the above first evaluation step, the analysis information includes the type of moving object, movement speed, encroachment area, encroachment range, encroachment time, index information based on a predetermined risk index, and information on relevant laws expected to be violated, and based on the analysis information, the A method for traffic control, monitoring and enforcement of moving objects using video information, wherein the traffic violation reporting module completes a primary analysis according to a preset range through the first evaluation stage and receives a final evaluation through an administrator terminal in the second evaluation stage to make a final judgment on whether a traffic violation has occurred. Claim 2 delete Claim 3 delete Claim 4 A method for traffic control, monitoring and enforcement of moving objects using video information, wherein the analysis information includes specific information and classifies the type of moving or stationary object based on video information in a traffic law violation reporting module according to predetermined criteria. Claim 5 delete Claim 6 A method for traffic control, monitoring and enforcement of moving objects using image information, wherein, in claim 1, one or more of the first camera or a plurality of cameras linked to the first camera have an anti-contamination coating layer formed on the camera lens. Claim 7 A server; a communication unit capable of transmitting and receiving data; a traffic management module that evaluates the presence or absence of a moving object or a stationary object that has encroached upon a predetermined first boundary area and a second boundary area based on information collected from a first camera, specifies the location of the encroached boundary area when a boundary area encroachment signal occurs, and collects and combines image information capturing the boundary area where the encroachment occurred from a plurality of cameras linked to the first camera; a traffic violation reporting module that processes the image information collected from the camera to generate analysis information, and evaluates whether a traffic law has been violated by analyzing the analysis information according to predetermined criteria based on the analysis information; a display that receives a signal from the traffic violation reporting module and outputs a warning signal to the collected image information and the moving object or stationary object; and an administrator terminal that receives the collected image information, the analysis information, and the evaluation information from the traffic violation reporting module, and transmits an evaluation signal regarding whether a traffic law has been violated; wherein the first camera is positioned at a location where the movement path of a moving object on the road, including vehicles and pedestrians, can be collected. A plurality of cameras installed and linked to the first camera are cameras already installed centered on the first camera, the first boundary area is an arbitrary boundary area set to control moving objects including vehicles centered on the crosswalk, and the second boundary area is an arbitrary boundary area set to control moving objects including pedestrians centered on the crosswalk, and when the traffic violation reporting module evaluates in the first evaluation stage that an intrusion by a moving object or a stationary object onto the first boundary area and evaluates that a stationary object for walking on the crosswalk exists on the second boundary area, the display outputs a warning signal toward the stationary object, and the traffic management module additionally sets a first preliminary boundary area including the gap between the crosswalk and the vehicle stop line based on video information collected from the first camera, identifies the movement and abnormal behavior of moving objects, and issues a warning.A second preliminary boundary area is additionally established between the second boundary area and the first preliminary boundary area to detect jaywalking by a pedestrian deviating from part or all of the crosswalk, encroachment of a moving object on the pedestrian path, or illegal parking; the traffic violation reporting module determines the intrusion range value and analyzes whether an intrusion has occurred based on information collected from a camera regarding the boundary area encroachment by moving objects, including pedestrians or mobility; the analysis identifies the moving object through image analysis and classifies the intrusion or preliminary intrusion stage within the boundary area to generate analysis information; the analysis information generated by the traffic violation reporting module includes the type of moving object, movement speed, encroachment area, intrusion range, intrusion time, index information based on a predetermined risk index, and information on relevant laws where a violation is expected; based on the analysis information, the traffic violation reporting module completes a primary analysis according to a pre-set range through the first evaluation stage, and receives a final evaluation through an administrator terminal in the second evaluation stage regarding whether a traffic law has been violated A traffic control, monitoring, and enforcement system for moving objects using video information to enable final judgment. Claim 8 A non-transient computer-readable medium for storing instructions, wherein the instructions, when executed by a processor, cause the processor to perform the method of any one of claims 1, 4, and 6.

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