Data compression-based video communication system in IoT environment, and method thereof

Abstract

A data compression-based video communication system in an IoT environment, according to an embodiment of the present invention, comprises: a video transmission device which includes a camera module for continuously capturing a target video, and which uses a data transformation model to transform and encode the target video captured by the camera module, thereby generating compressed video data; and a video management server which receives and decodes the compressed video data from the video transmission device and which generates a restored video on the basis of the decoded data, wherein the data transformation model can be defined to collect data related to pixels with allocated pixel values exceeding a preset reference value range from among a plurality of pixels included in the target video, and perform data compression thereon.

Description

Data compression-based video communication system and method in an IoT environment

[0001] The present invention relates to a data compression-based video communication system and method in an IoT environment.

[0002] The recent rapid growth of artificial intelligence technology has led to the adoption of Internet of Things (IoT) devices in diverse industrial environments, including manufacturing processes, construction, and transportation facilities. This has significantly reduced the costs and labor required to manage and supervise each process and site, and has also demonstrated high adaptability and speed in system improvements, such as error correction and the reflection of changes.

[0003] In this IoT environment, continuous video capture and data transmission are required, particularly for monitoring specific objects or locations. Conventional systems, however, rely on transmitting all captured video data directly to a central management server. This massive data volume, captured and transmitted in real time at microsecond intervals, leads to excessive data communication costs, and overload issues are inevitable.

[0004] As dependence on IoT devices in industrial environments rapidly increases, there is an urgent need for technological development to overcome the aforementioned limitations of cost and overload. Specifically, a system is needed that compresses real-time video data as much as possible before transmitting it to a central management server, thereby reducing data traffic volume while maintaining and preserving the quality (resolution, etc.) and reliability of the video collected and output from the central management server.

[0005] The purpose of the present invention is to provide a data compression-based video communication system and method that reduces the amount of data transmitted to a server and saves communication costs by collecting and compressing only data for areas where color or brightness has changed among image areas of a video captured in real time.

[0006] In addition, the present invention aims to provide a data compression-based video communication system and method thereof that can easily identify and deal with a situation in which a significant change is detected in an environment in which the image change of the video is not large.

[0007] In addition, the present invention aims to provide a data compression-based video communication system and method that can efficiently reduce the amount of video data communication without deteriorating the quality of an image restored from a server.

[0008] In addition, the present invention aims to provide a data compression-based video communication system and method that can adjust the sensitivity detected as an image change according to the characteristics of the site to be monitored.

[0009] The problem to be solved by the present invention is not limited to this, and it can be said that the purpose or effect that can be understood from the solution or embodiment of the problem described below is also included.

[0010] A data compression-based video communication system according to one embodiment of the present invention comprises: a camera module that continuously captures target images, an image transmission device that converts and encodes the target images captured by the camera module using a data conversion model to generate compressed image data; and an image management server that receives and decodes the compressed image data from the image transmission device and generates a restored image based on the decoded data; wherein the data conversion model may be defined to perform data compression by collecting data regarding pixels whose assigned pixel values ​​exceed a preset reference value range among a plurality of pixels included in the target image.

[0011] Additionally, the compressed image data may be characterized as having the form of a compressed sparse matrix.

[0012] In addition, the data conversion module may be characterized in that, for each of a plurality of pixels included in the target image, if a pixel value assigned to the pixel is outside the reference value range, the assigned pixel value is maintained, and if the pixel value assigned to the pixel is within the reference value range, the pixel value is converted to a value of 0.

[0013] In addition, the preset reference value range is characterized in that it is set by the image management server and provided to the image transmission device, and the image management server receives a plurality of target images from the image transmission device for a predetermined period of time, calculates an average value and a distribution for a plurality of pixel values ​​assigned to the same point for each pixel constituting the plurality of target images, and sets a reference value range including a highest reference value and a lowest reference value based on the average value and the distribution for each pixel.

[0014] In addition, the reference value range is reset at predetermined time intervals by the image management server and provided to the image transmission device, and the image management server generates the restored images from the plurality of compressed image data received at the predetermined time intervals, calculates a new average value and distribution for the plurality of pixel values ​​assigned to the same point for each pixel constituting the generated plurality of restored images, and sets a new reference value range for each pixel based on the new average value and distribution.

[0015] In addition, the image management server may store a data restoration algorithm that derives a restoration matrix including a value of 0 based on pixel values ​​and coordinate information included in the compressed image data, and the image management server may be characterized in that, when generating the restoration image, a pixel having a value of 0 in the derived restoration matrix is ​​determined to be a non-changing point in the image and thus maintains the existing pixel value, and a pixel having a non-zero value is determined to be a changing point in the image and thus applies a new pixel value included in the restoration matrix.

[0016] In addition, the image management server may be connected to a plurality of image transmission devices so as to be able to communicate with them, and when the compressed image data is received from any one of the plurality of image transmission devices, the image management server may be characterized by recognizing registration information of the one image transmission device and transmitting reference value range information corresponding to the recognized registration information to the image transmission device.

[0017] A data compression-based video communication method according to one embodiment of the present invention comprises: a step in which a camera module included in an image transmission device continuously captures a target image; a step in which the image transmission device converts and encodes the target image captured by the camera module using a data conversion model to generate compressed image data; and a step in which the image management server receives and decodes the compressed image data from the image transmission device and generates a restored image based on the decoded data; wherein the data conversion model may be defined to perform data compression by collecting data regarding pixels whose assigned pixel values ​​among a plurality of pixels included in the target image exceed a preset reference value range.

[0018] According to a data compression-based video communication system and method according to an embodiment of the present invention, only data for areas where color or brightness has changed among image areas of a video captured in real time is collected and compressed, thereby reducing the amount of data communication transmitted to a server and saving communication costs.

[0019] In addition, according to the data compression-based video communication system and method according to an embodiment of the present invention, it is possible to easily identify and deal with a situation in which a significant change is detected in an environment in which the image change of the video is not large.

[0020] In addition, according to the data compression-based video communication system and method according to an embodiment of the present invention, the amount of video data communication can be efficiently reduced without deteriorating the quality of the image restored from the server.

[0021] In addition, according to the data compression-based video communication system and method according to an embodiment of the present invention, the sensitivity detected as an image change can be adjusted according to the characteristics of the site to be monitored.

[0022] The various advantageous and beneficial effects of the present invention are not limited to the above-described contents, and will be more easily understood in the course of explaining specific embodiments of the present invention.

[0023] FIG. 1 is a conceptual diagram schematically illustrating a data compression-based video communication system according to an embodiment of the present invention.

[0024] Figure 2 is a block diagram showing an example of a detailed configuration of the image management server illustrated in Figure 1.

[0025] FIG. 3 is a flowchart schematically illustrating a data compression-based video communication method according to an embodiment of the present invention.

[0026] FIG. 4 illustrates an example of extracting each pixel value from a target image and converting it into data according to one embodiment of the present invention.

[0027] FIG. 5 illustrates an example of performing data conversion by comparing each pixel value with a reference value range according to one embodiment of the present invention.

[0028] FIG. 6 illustrates an example of generating compressed image data from converted data according to one embodiment of the present invention.

[0029] FIG. 7 illustrates an example of deriving a restoration matrix from compressed image data according to one embodiment of the present invention.

[0030] FIG. 8 illustrates an example of generating a restored image from a restored matrix according to one embodiment of the present invention.

[0031] The present invention is susceptible to various modifications and embodiments. Specific embodiments are illustrated and described in the drawings. However, this is not intended to limit the present invention to specific embodiments, but rather to encompass all modifications, equivalents, and alternatives falling within the spirit and technical scope of the present invention.

[0032] Terms including ordinal numbers, such as first, second, etc., may be used to describe various components, but the components are not limited by these terms. These terms are used solely to distinguish one component from another. For example, without departing from the scope of the present invention, a second component may be referred to as a first component, and similarly, a first component may also be referred to as a second component. The term "and / or" includes a combination of a plurality of related described items or any of a plurality of related described items.

[0033] When a component is referred to as being "connected" or "connected" to another component, it should be understood that it may be directly connected or connected to that other component, but that there may be other components intervening. Conversely, when a component is referred to as being "directly connected" or "connected" to another component, it should be understood that there are no other components intervening.

[0034] The terminology used in this application is only used to describe specific embodiments and is not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly indicates otherwise. In this application, it should be understood that the terms "comprise" or "have" indicate the presence of a feature, number, step, operation, component, part, or combination thereof described in the specification, but do not exclude in advance the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0035] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and shall not be interpreted in an idealized or overly formal sense unless explicitly defined herein.

[0036] Hereinafter, embodiments will be described in detail with reference to the attached drawings. Regardless of the drawing numbers, identical or corresponding components are given the same reference numbers, and redundant descriptions thereof will be omitted.

[0037]

[0038] FIG. 1 is a conceptual diagram schematically illustrating a data compression-based video communication system according to an embodiment of the present invention.

[0039] As illustrated in FIG. 1, a compression-based video communication system according to one embodiment of the present invention may include a video transmission device (100) and a video management server (200). The video transmission device (100) and the video management server (200) are connected to each other so as to be able to communicate with each other and transmit or receive necessary signals or information.

[0040] The image transmission device (100) may refer to a device that captures an image of a designated object and / or location and transmits the image to an image management server (200). For example, the image transmission device (100) is a device that captures an area of ​​a specific manufacturing process, and may include a device for monitoring whether irregular image changes (e.g., detection of impurities, appearance of obstacles, collapse of equipment, etc.) occur in the area. In the following description, the image of the object and / or location captured by the image transmission device (100) will be referred to as a target image.

[0041] According to one embodiment of the present invention, the image transmission device (100) may include a camera module that captures a target image. The target image captured by the camera module may be converted and encoded using a data conversion model. The resulting data, in which the data capacity is compressed from the original data of the target image after the conversion and encoding are completed, is referred to as compressed image data. The image transmission device (100) may generate compressed image data.

[0042] The video transmission device (100) can be connected to the video management server (200) via various communication methods. According to one embodiment, the video transmission device (100) can be connected to the video management server (200) via wireless communication such as WiFi, LTE, or 3G. In addition, the video transmission device (100) can be connected to the video management server (200) via wired communication such as LAN.

[0043] The video management server (200) may refer to a server that receives and stores video data captured by the video transmission device (100), analyzes or processes the video data as needed, and generates information and / or signals required by the user. Here, the server may refer to a device that includes a processing unit and memory for processing data.

[0044] According to one embodiment of the present invention, the image management server (200) can receive compressed image data from the image transmission device (100). The image management server (200) can then decode the received compressed image data and generate a restored image based on the decoded data. Here, the restored image may refer to an image generated by the image management server (200) to be provided to a user or output through a device such as an external display.

[0045] The image management server (200) can generate a restored image and provide it to a user terminal (310) and / or a user electronic device (320) connected to communicate with the server (200). A user monitoring a designated target image in an industrial environment such as a manufacturing process or facility can check the current status of the target image output in real time through the user terminal (310) or the user electronic device (320).

[0046] Additionally, at least some of the restored images, for example, restored images generated during a specific time interval, may be stored within the image management server (200) and then provided to the user in the form of an image file. For example, if a persistent image change is detected in a portion of the restored image, the image management server (200) may store consecutive restored images during the time interval in which the change persisted in the form of an image file.

[0047]

[0048] FIG. 2 is a block diagram showing an example of a detailed configuration of the image management server (200) illustrated in FIG. 1.

[0049] As illustrated in FIG. 2, the image management server (200) may include a communication module (210), a processor (230), and a database (250). The processor (230) may be a module that performs various operations, and may include a decoder (231), a data restoration unit (233), a device recognition unit (235), and an update unit (237).

[0050] The communication module (210) can perform communication with at least one image transmission device (100). The communication module (210) is provided so that the image management server (200) can be directly connected to the outside or connected via a network, and may be a wired and / or wireless communication module. For example, the communication module (210) may be a device that communicates via LAN, WCDMA (Wideband Code Division Multiple Access), LTE (Long Term Evolution), WiBro (Wireless Broadband Internet), RF (Radio Frequency) communication, Wireless LAN, Wi-Fi (Wireless Fidelity), NFC (Near Field Communication), Bluetooth, infrared communication, etc. However, this is exemplary, and various wired and wireless communication technologies applicable in the relevant technical field may be used depending on the embodiment to which the present invention is applied.

[0051] The processor (230) is electrically connected to the communication module (210) and the database (250), and can execute operations or data processing related to control and / or communication of other components according to commands, programs, or software stored during operation. That is, the execution of the commands, programs, or software can be understood as the operation of the processor (130), and the processor (230) can include at least one or more of a central processing unit (CPU), an application processor (AP), or a communication processor (CP). The method of performing operations according to the specific configuration of the processor (230) will be described together with FIGS. 3 to 8 described below.

[0052] The database (250) can store all the contents, details, etc. of data transmitted and received with at least one image transmission device (100). In addition, the database (250) can store all the contents, details, etc. of data transmitted and received with various external devices such as a user terminal (310). The data stored in the database (250) can be regularly updated according to a predetermined cycle, and can be updated periodically when new data is input through various external devices including the image transmission device (100).

[0053] For example, the database (250) may store target image data and compressed image data received from the image transmission device (100). If necessary, the database (250) may be implemented so that the most recent data for a predetermined time interval among the target image data and / or compressed image data is stored, and the remaining data previously stored is deleted.

[0054]

[0055] Hereinafter, a method of performing a data compression-based video communication method in an IoT environment according to an embodiment of the present invention will be described.

[0056]

[0057] First, referring to FIG. 3, FIG. 3 is a flowchart schematically illustrating a data compression-based video communication method according to an embodiment of the present invention.

[0058] According to one embodiment of the present invention, in the image transmission device (100), a target image is captured (S310), and the captured target image can be converted and encoded to generate compressed image data (S320). At this time, when the image transmission device (100) generates the compressed image data, a data conversion model can be used. The data conversion model can be defined to perform data compression by collecting data about pixels whose assigned pixel values ​​among a plurality of pixels included in the target image exceed a preset reference value range.

[0059] Then, when compressed image data is transmitted from the image transmission device (100) to the image management server (200), the image management server (200) can decode the compressed image data and generate a restored image (S330). At this time, when the image management server (200) generates the restored image, a data restoration algorithm can be executed. The data restoration algorithm may refer to an algorithm that derives a restoration matrix that includes a value of 0 based on the pixel values ​​and their coordinate information included in the compressed image data.

[0060] Meanwhile, the reference value range used in the data conversion module can be preset in the image management server (200) and can be reset periodically as needed. For example, the reference value range can be reset at predetermined time intervals and transmitted to the image transmission device (100). When the image transmission device (100) receives data regarding the reset reference value range, it can perform a data conversion model to which the changed reference value range is applied.

[0061]

[0062] A specific data compression-based video communication method as illustrated in FIG. 3 is exemplarily illustrated in FIGS. 4 to 8, and will be described with reference thereto. Specifically, the video transmission device (100) can generate compressed image data from a target image as in the embodiments illustrated in FIGS. 4 to 6.

[0063] FIG. 4 illustrates an example of extracting each pixel value from a target image and converting it into data according to one embodiment of the present invention, FIG. 5 illustrates an example of performing data conversion by comparing each pixel value with a reference value range according to one embodiment of the present invention, and FIG. 6 illustrates an example of generating compressed image data from converted data according to one embodiment of the present invention. The examples illustrated in FIGS. 4 to 6 may be performed sequentially.

[0064] First, as illustrated in FIG. 4, the image transmission device (100) can extract pixel values ​​of each image from the target image captured by the camera module and convert them into data. Here, the pixel values ​​may be implemented as pixel values ​​corresponding to the brightness of a black-and-white image (grayscale) as illustrated in FIG. 4, but may also be implemented as pixel values ​​composed of RGB values ​​of a color image. In the following specification, for the convenience of explanation, pixel values ​​according to a black-and-white image will be described as an example.

[0065] When a pixel value is extracted for each pixel included in the target image, as shown in Fig. 4, this can be expressed in the form of a single data matrix. For example, since the pixel corresponding to the (0,0) coordinate of the target image has a pixel value of 220, a data value of 220 can be entered at the (0,0) location in the matrix.

[0066] And, as illustrated in FIG. 5, the image transmission device (100) can perform a data conversion model on the result data from which pixel values ​​are extracted. At this time, the data conversion model may be characterized in that, if the pixel value assigned to a data conversion model pixel is outside a preset reference value range, the assigned pixel value is maintained, and if the pixel value assigned to the pixel is within the reference value range, the pixel value is converted to a value of 0.

[0067] Meanwhile, the preset reference value range here may be set and provided by the image management server (200). For example, the image management server (200) may receive multiple target images from the image transmission device (100) for a predetermined period of time, and may calculate the average value and distribution for multiple pixel values ​​assigned to the same point for each pixel constituting the multiple target images. In addition, for each pixel, a reference value range including the highest reference value and the lowest reference value may be set based on the average value and distribution.

[0068] As an example, the image management server (200), in the initial stage of receiving image data from the image transmission device (100), can set a reference value range using multiple target images received over a predetermined period of time, i.e., 1 minute. If the number of target images received over 1 minute is 600, the average value and distribution can be calculated using the pixel values ​​assigned to the same point of each target image. For example, if the average value of 600 pixel values ​​assigned to the point (0,0) is 220, the reference value range can be set to a range within +10 and -10 from the average value of 220 (i.e., 210 to 230), as shown in FIG. 5. In this way, the average value and distribution of multiple target images for the pixel values ​​of all points can be calculated, and the reference value range can be set accordingly.

[0069] Then, the image transmission device (100) can perform a data conversion model by comparing the pixel value data of the target image with a preset reference value range. That is, if the pixel value assigned to the pixel is outside the preset reference value range, the assigned pixel value is maintained. For example, the pixel values ​​at points (0,3) and (0,4) are 251 and 250, respectively, which are outside the reference value range, and therefore the assigned pixel values ​​of 251 and 250 are maintained as is. On the other hand, if the pixel value assigned to the pixel is within the reference value range, the pixel value is converted to a value of 0. For example, the pixel values ​​at points (0,0), (0,1), and (0,2) are 220, 223, and 252, respectively, which are within the reference value range, and therefore the pixel values ​​are converted to 0. When data conversion is performed on pixels at all points in this way, matrix data including a large number of 0 values, as illustrated in FIG. 5, can be generated. In Fig. 5, it can be confirmed that since there are a total of 5 pixel values ​​that are outside the reference value range, all pixel values ​​except for these have been converted to a value of 0.

[0070] Meanwhile, instead of maintaining the assigned pixel values ​​when they deviate from the reference value, it is also possible to convert them by assigning an error value based on the degree to which the pixel values ​​have changed. For example, the pixel values ​​at points (0,3) and (0,4) mentioned above are 251 and 250, respectively, which deviate from the reference value range, and therefore can be converted by assigning them an error value of 166 and 160 based on the degree to which the pixel values ​​have changed from the reference value of 85.

[0071] Next, referring to FIG. 6, according to the converted data, data corresponding to a value of 0 may be eliminated, leaving only data having a non-zero value. In this way, data that only retains data according to non-zero pixel values ​​may be referred to as compressed image data. That is, the compressed image data may be characterized by having the form of a compressed sparse matrix, as shown in FIG. 6. In this way, it can be confirmed that the compressed image data is compressed rapidly compared to the target image data that was initially captured and received.

[0072] Meanwhile, the reference value range used in the aforementioned data conversion model may be reset at predetermined time intervals by the image management server (200) and provided to the image transmission device (100). The image management server (200) may generate restored images from a plurality of compressed image data received at predetermined time intervals, and may calculate a new average value and distribution for a plurality of pixel values ​​assigned to the same point for each pixel constituting the generated plurality of restored images. In addition, a new reference value range may be set for each pixel based on the new average value and distribution.

[0073]

[0074] Next, the image management server (200) can generate a restored image from compressed image data as in the embodiments illustrated in FIGS. 7 and 8.

[0075] FIG. 7 illustrates an example of deriving a restoration matrix from compressed image data according to one embodiment of the present invention, and FIG. 8 illustrates an example of generating a restoration image from a restoration matrix according to one embodiment of the present invention. The examples illustrated in FIGS. 7 and 8 may be performed sequentially.

[0076] The image management server (200) may store a data restoration algorithm that derives a restoration matrix including a value of 0 based on pixel values ​​and coordinate information included in compressed image data. The method by which this data restoration algorithm is performed is the same as the method illustrated in FIG. 7. That is, the compressed image data includes coordinate information to which each remaining pixel value after compression was assigned. For example, it can be confirmed that the pixel value of 150 is the value assigned to the point (2, 5). Accordingly, when the data restoration algorithm is performed, a restoration matrix including a value of 0 again can be derived, as illustrated in FIG. 7.

[0077] Next, the image management server (200) may determine that pixels having a value of 0 in the derived restoration matrix are unchanged points in the image and maintain the existing pixel values, and may determine that pixels having a non-0 value are changed points in the image and apply new pixel values ​​included in the restoration matrix. At this time, maintaining the existing pixel values ​​means that the brightness according to the pixel value of the same point in the existing video image immediately before the current point in time is maintained as is. Conversely, applying a new pixel value means that the brightness applied to the existing video image immediately before the current point in time is not maintained, and the brightness according to the new pixel value is reflected in the corresponding pixel area. Accordingly, as illustrated in FIG. 8, a restored image can be generated in which only the new pixel values ​​are changed.

[0078] Meanwhile, according to an additional embodiment of the present invention, the image management server (200) may be connected to a plurality of image transmission devices (100) so as to be able to communicate with them, and when compressed image data is received from any one of the plurality of image transmission devices (100), the image management server (200) may be characterized by recognizing registration information of one of the image transmission devices (100) and transmitting reference value range information corresponding to the recognized registration information to the image transmission device (100). Accordingly, images of various objects or locations can be monitored through a single image management server (200).

[0079]

[0080] As described above, according to the data compression-based video communication system and method according to the embodiment of the present invention, only data for areas where color or brightness has changed among image areas of a video captured in real time is collected and compressed, thereby reducing the amount of data communication transmitted to the server and saving communication costs.

[0081] In addition, according to the data compression-based video communication system and method according to an embodiment of the present invention, it is possible to easily identify and deal with a situation in which a significant change is detected in an environment in which the image change of the video is not large.

[0082] In addition, according to the data compression-based video communication system and method according to an embodiment of the present invention, the amount of video data communication can be efficiently reduced without deteriorating the quality of the image restored from the server.

[0083] In addition, according to the data compression-based video communication system and method according to an embodiment of the present invention, the sensitivity detected as an image change can be adjusted according to the characteristics of the site to be monitored.

[0084]

[0085] The term '~ part' used in this embodiment means a software or hardware component such as an FPGA (field-programmable gate array) or an ASIC, and the '~ part' performs certain roles. However, the '~ part' is not limited to software or hardware. The '~ part' may be configured to be on an addressable storage medium and may be configured to play one or more processors. Thus, as an example, the '~ part' includes components such as software components, object-oriented software components, class components, and task components, processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functionality provided within the components and '~ parts' may be combined into a smaller number of components and '~ parts' or further separated into additional components and '~ parts'. Additionally, components and '~parts' may be implemented to regenerate one or more CPUs within a device or secure multimedia card.

[0086] Although the above description focuses on examples, these are merely examples and do not limit the present invention. Those skilled in the art will appreciate that various modifications and applications not exemplified above are possible without departing from the essential characteristics of the present invention. For example, each component specifically shown in the examples can be modified and implemented. In addition, differences related to such modifications and applications should be construed as being included within the scope of the present invention defined in the appended claims.

Claims

1. Includes a camera module that continuously captures target images, An image transmission device that converts and encodes a target image captured by the above camera module using a data conversion model to generate compressed image data; and An image management server that receives and decodes the compressed image data from the image transmission device and generates a restored image based on the decoded data; Including, The above data transformation model is, It is defined to perform data compression by collecting data on pixels among multiple pixels included in the target image whose assigned pixel value exceeds a preset reference value range. A video communication system based on data compression.

2. In paragraph 1, The above compressed image data is characterized in that it has the form of a COMPRESSED SPARSE MATRIX. A video communication system based on data compression.

3. In paragraph 1, The above data conversion module, for each of the plurality of pixels included in the target image, If the pixel value assigned to the above pixel is outside the above reference value range, the assigned pixel value is maintained, Characterized in that if the pixel value assigned to the pixel falls within the reference value range, the pixel value is converted to a value of 0. A video communication system based on data compression.

4. In paragraph 1, The above-mentioned preset reference value range is characterized in that it is set by the image management server and provided to the image transmission device. The above video management server, Receive multiple target images from the image transmission device for a predetermined period of time, For each pixel constituting the above multiple target images, the average value and distribution for multiple pixel values ​​assigned to the same point are calculated, For each pixel above, a reference value range including the highest reference value and the lowest reference value is set based on the average value and distribution. A video communication system based on data compression.

5. In paragraph 4, The above reference value range is reset at a predetermined time interval by the image management server and provided to the image transmission device. The above video management server, Each of the restored images is generated from a plurality of compressed image data received at the above-described predetermined time intervals, For each pixel constituting the plurality of restored images generated above, a new average value and distribution for the plurality of pixel values ​​assigned to the same point are calculated, For each pixel above, a new reference value range is set based on the new average value and distribution. A video communication system based on data compression.

6. In paragraph 1, In the above image management server, a data restoration algorithm that derives a restoration matrix including a value of 0 based on pixel values ​​and coordinate information included in the compressed image data is stored, The above image management server, in creating the above restoration image, In the above-derived restoration matrix, pixels having a value of 0 are judged as non-changing points in the image and the existing pixel values ​​are maintained, and pixels having a non-zero value are judged as changing points in the image and the new pixel values ​​included in the restoration matrix are applied. A video communication system based on data compression.

7. In paragraph 1, The above video management server is connected to enable communication with multiple video transmission devices, When the compressed image data is received from one of the plurality of image transmission devices, the registration information of the one image transmission device is recognized, and reference value range information corresponding to the recognized registration information is transmitted to the image transmission device. A video communication system based on data compression.

8. A step in which a camera module included in an image transmission device continuously captures target images; The step of the image transmission device converting and encoding the target image captured by the camera module using a data conversion model to generate compressed image data; and A step in which the image management server receives the compressed image data from the image transmission device, decodes it, and generates a restored image based on the decoded data; Including, The above data transformation model is, It is defined to perform data compression by collecting data on pixels among multiple pixels included in the target image whose assigned pixel value exceeds a preset reference value range. A video communication method based on data compression.

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