Image state detection equipment based on dot matrix camera shooting

Abstract

The invention relates to an image state detection device based on dot matrix camera shooting, and the device comprises a dot matrix camera shooting mechanism which is used for obtaining an on-site camera shooting picture corresponding to the environment; the intelligent judgment mechanism is arranged at the monitoring server and is used for inputting the shutter speed, the aperture value and the camera shooting frame speed of the dot matrix camera shooting mechanism and item-by-item information of a field camera shooting picture into a manual analysis model in parallel; and obtaining different binary numerical values which are output by the manual analysis model and represent whether the on-site shooting picture is a real image which is not subjected to subsequent image processing or not. According to the invention, multiple items of information can be selected in a targeted manner as the basic data for intelligent judgment of judging whether the on-site shooting picture obtained in the set scene is a real image which is not subjected to subsequent image processing, and an artificial analysis model with a customized structural design is introduced to complete intelligent judgment processing. Therefore, more reliable reference content is provided for the monitoring server to judge the real scene of the set scene.

Description

Technical Field

[0001] The invention relates to the field of image processing, and in particular to an image state detection device based on dot matrix photography. Background Art

[0002] As the visual basis for human beings to perceive the world, images are an important means for humans to obtain, express and transmit information. Digital image processing, that is, processing images with computers, has a short history. Digital image processing technology originated in the 1920s, when a photo was transmitted from London, England to New York, USA via submarine cables, using digital compression technology. First of all, digital image processing technology can help people understand the world more objectively and accurately. Human visual devices can help humans obtain more than 3 / 4 of information from the outside world, and images and graphics are the carriers of all visual information. Although the human eye has a high discernment and can recognize thousands of colors, in many cases, images are blurry or even invisible to the human eye. Through image enhancement technology, blurry or even invisible images can be made clear and bright.

[0003] For the end that acquires the live camera images, since it is impossible to know the internal structure and working mode of the camera mechanism of the live camera images, it is difficult to know whether the live camera images are real images that have not undergone subsequent image processing, which can easily lead to misjudgment of the real image content of the live camera images. Summary of the invention

[0004] In order to solve the technical problems in related fields, the present invention provides an image state detection device based on dot matrix photography, which obtains comprehensive and effective multiple basic data by selecting the shutter speed, aperture value and camera frame rate of the dot matrix camera mechanism and the item-by-item information of the live camera picture as the basic data for intelligent judgment of whether the live camera picture obtained in a set scene is a real image without subsequent image processing, thereby introducing an artificial analysis model with customized structure design to complete the intelligent judgment processing, and the artificial analysis model outputs different binary values ​​to represent whether the live camera picture is a real image without subsequent image processing, thereby providing more reliable reference content for the monitoring server to judge the real scene of the set scene.

[0005] According to the present invention, there is provided an image state detection device based on dot matrix photography, the device comprising: A network construction mechanism is used to perform multiple learning operations on a single-layer neural network to obtain a single-layer neural network after completing multiple learning operations, and output the single-layer neural network after completing multiple learning operations as an artificial analysis model; The dot matrix camera mechanism is used to perform camera processing on the facing environment to obtain a live camera picture corresponding to the facing environment; A parameter capture mechanism, connected to the dot matrix camera mechanism, for obtaining various camera parameters of the dot matrix camera mechanism by reading the bottom layer driving module of the dot matrix camera mechanism, wherein the various camera parameters of the dot matrix camera mechanism include the shutter speed, aperture value and camera frame rate of the dot matrix camera mechanism; An information identification mechanism, connected to the dot matrix camera mechanism, is used to obtain the contrast, resolution, signal-to-noise ratio, maximum noise amplitude and number of noise types of the live camera image and output it as item-by-item information of the live camera image; an intelligent determination mechanism, arranged at the monitoring server and connected to the network construction mechanism, the parameter capture mechanism and the information identification mechanism respectively, for inputting the shutter speed, aperture value and camera frame rate of the dot matrix camera mechanism and the item-by-item information of the on-site camera picture into the artificial analysis model in parallel, so as to obtain different binary values ​​output by the artificial analysis model, wherein when the binary value output by the artificial analysis model is 0B01, it represents that the on-site camera picture is a real image without subsequent image processing, and when the binary value output by the artificial analysis model is 0B00, it represents that the on-site camera picture is a non-real image after subsequent image processing; Among them, the shutter speed, aperture value and camera frame rate of the dot matrix camera mechanism and the item-by-item information of the on-site camera picture are input into the manual analysis model in parallel to obtain different binary values ​​output by the manual analysis model. When the binary value output by the manual analysis model is 0B01, it represents that the on-site camera picture is a real image that has not undergone subsequent image processing. When the binary value output by the manual analysis model is 0B00, it represents that the on-site camera picture is a non-real image that has undergone subsequent image processing. The method includes: converting the shutter speed, aperture value and camera frame rate of the dot matrix camera mechanism and the item-by-item information of the on-site camera picture into binary values ​​respectively and then inputting them into the manual analysis model in parallel.

[0006] The present invention has at least the following three important inventive features: Firstly, the shutter speed, aperture value and camera frame rate of the dot matrix camera mechanism and the item-by-item information of the on-site camera picture are selected as the basic data for intelligent determination of whether the on-site camera picture obtained in the set scene is a real image without subsequent image processing, thereby obtaining comprehensive and effective basic data; Secondly: specifically, the contrast, resolution, signal-to-noise ratio, maximum noise amplitude and number of noise types of the live camera picture are output as item-by-item information of the live camera picture; Again: an artificial analysis model with customized structure design is introduced to complete intelligent judgment processing. The artificial analysis model outputs different binary values ​​to represent whether the on-site camera picture is a real image without subsequent image processing, thereby providing more reliable reference content for the monitoring server to judge the real scene of the set scene. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] The embodiments of the present invention will be described below with reference to the accompanying drawings, wherein: Figure 1 Schematic diagram of the internal structure of an image state detection device based on dot matrix photography according to Embodiment A of the present invention.

[0008] Figure 2 Schematic diagram of the internal structure of an image state detection device based on dot matrix photography according to Embodiment B of the present invention.

[0009] Figure 3 Schematic diagram of the internal structure of an image state detection device based on dot matrix photography according to Embodiment C of the present invention. DETAILED DESCRIPTION

[0010] Hereinafter, an embodiment of the image state detection device based on dot matrix imaging of the present invention will be described in detail with reference to the accompanying drawings.

[0011] Figure 1 The internal structure diagram of an image state detection device based on dot matrix photography according to Embodiment A of the present invention is shown, and the device comprises: A network construction mechanism is used to perform multiple learning operations on a single-layer neural network to obtain a single-layer neural network after completing multiple learning operations, and output the single-layer neural network after completing multiple learning operations as an artificial analysis model; For example, a network construction mechanism for performing multiple learning operations on a single-layer neural network to obtain a single-layer neural network after completing multiple learning operations, and outputting the single-layer neural network after completing multiple learning operations as an artificial analysis model includes: using a CPLD chip to implement the network construction mechanism for performing multiple learning operations on a single-layer neural network to obtain a single-layer neural network after completing multiple learning operations, and outputting the single-layer neural network after completing multiple learning operations as an artificial analysis model; The dot matrix camera mechanism is used to perform camera processing on the facing environment to obtain a live camera picture corresponding to the facing environment; A parameter capture mechanism, connected to the dot matrix camera mechanism, for obtaining various camera parameters of the dot matrix camera mechanism by reading the bottom layer driving module of the dot matrix camera mechanism, wherein the various camera parameters of the dot matrix camera mechanism include the shutter speed, aperture value and camera frame rate of the dot matrix camera mechanism; An information identification mechanism, connected to the dot matrix camera mechanism, is used to obtain the contrast, resolution, signal-to-noise ratio, maximum noise amplitude and number of noise types of the live camera image and output it as item-by-item information of the live camera image; an intelligent determination mechanism, arranged at the monitoring server and connected to the network construction mechanism, the parameter capture mechanism and the information identification mechanism respectively, for inputting the shutter speed, aperture value and camera frame rate of the dot matrix camera mechanism and the item-by-item information of the on-site camera picture into the artificial analysis model in parallel, so as to obtain different binary values ​​output by the artificial analysis model, wherein when the binary value output by the artificial analysis model is 0B01, it represents that the on-site camera picture is a real image without subsequent image processing, and when the binary value output by the artificial analysis model is 0B00, it represents that the on-site camera picture is a non-real image after subsequent image processing; The shutter speed, aperture value, and camera frame rate of the dot matrix camera mechanism and the item-by-item information of the on-site camera picture are inputted into the manual analysis model in parallel to obtain different binary values ​​outputted by the manual analysis model. When the binary value outputted by the manual analysis model is 0B01, it represents that the on-site camera picture is a real image that has not been processed subsequently. When the binary value outputted by the manual analysis model is 0B00, it represents that the on-site camera picture is a non-real image that has been processed subsequently. The method includes: converting the shutter speed, aperture value, and camera frame rate of the dot matrix camera mechanism and the item-by-item information of the on-site camera picture into binary values ​​respectively and then inputting them into the manual analysis model in parallel. Among them, the shutter speed, aperture value and camera frame rate of the dot matrix camera mechanism and the information of the on-site camera picture are input into the manual analysis model in parallel to obtain different binary values ​​output by the manual analysis model. When the binary value output by the manual analysis model is 0B01, it represents that the on-site camera picture is a real image that has not undergone subsequent image processing. When the binary value output by the manual analysis model is 0B00, it represents that the on-site camera picture is a non-real image that has undergone subsequent image processing. It also includes: using a numerical simulation mode to complete the simulation and test of the data processing process of inputting the shutter speed, aperture value and camera frame rate of the dot matrix camera mechanism and the information of the on-site camera picture in parallel into the manual analysis model to obtain different binary values ​​output by the manual analysis model.

[0012] Figure 2 Schematic diagram of the internal structure of an image state detection device based on dot matrix photography according to Embodiment B of the present invention.

[0013] Compared with implementation A, the image state detection device based on dot matrix photography shown in implementation B may also include the following components: A field editable logic device is connected to the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism respectively, and is used to provide configuration operations of working parameters for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner; The field editable logic device is respectively connected to the intelligent determination mechanism, the network construction mechanism, the parameter grabbing mechanism and the information identification mechanism, and is used to provide the configuration operation of the working parameters for the intelligent determination mechanism, the network construction mechanism, the parameter grabbing mechanism and the information identification mechanism in a time-sharing manner, including: the intelligent determination mechanism, the network construction mechanism, the parameter grabbing mechanism and the information identification mechanism share the same working parameter configuration interface; Wherein, the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism use different configuration address data; Wherein, a parallel connection of a communication data link is established between each of the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism through a parallel data bus; Among them, the parallel connection of the communication data link established between each of the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism through a parallel data bus includes: the parallel data bus is one of an 8-bit parallel data bus, a 16-bit parallel data bus and a 32-bit parallel data bus.

[0014] Figure 3 Schematic diagram of the internal structure of an image state detection device based on dot matrix photography according to Embodiment C of the present invention.

[0015] Compared with implementation A, the image state detection device based on dot matrix photography shown in implementation C may also include the following components: A power support device is connected to the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism respectively, and is used to provide power distribution support of different working voltages for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner; The power support device is respectively connected to the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism, and is used to provide power distribution support of different working voltages for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner, including: two or more devices with the same working voltage requirements in the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism use the same power supply line; Wherein, the power support device is respectively connected to the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism, and is used to provide power distribution support of different working voltages for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner, and further includes: the power support device is an uninterruptible power supply device; Among them, the power support device is respectively connected to the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism, and is used to provide power distribution support with different working voltages for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner, and further includes: providing different working voltages including 3.3V working voltage for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner; And wherein, the power support device is respectively connected to the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism, and is used to provide power distribution support with different working voltages for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner, and also includes: providing different working voltages including 5V working voltage for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner.

[0016] In addition, in the image state detection device based on dot matrix photography, an information identification mechanism is connected to the dot matrix photography mechanism, and is used to obtain the contrast, resolution, signal-to-noise ratio, maximum noise amplitude, and number of noise types of the live camera picture and output it as item-by-item information of the live camera picture, including: the information identification mechanism has multiple different parameter acquisition components built in, which are used to respectively obtain the contrast, resolution, signal-to-noise ratio, maximum noise amplitude, and number of noise types of the live camera picture; And wherein, the information identification mechanism is connected to the dot matrix camera mechanism, and is used to obtain the contrast, resolution, signal-to-noise ratio, maximum noise amplitude and number of noise types of the live camera picture and output it as the item-by-item information of the live camera picture, and also includes: using different parameter capture components to respectively obtain the contrast, resolution, signal-to-noise ratio, maximum noise amplitude and number of noise types of the live camera picture.

[0017] The image state detection device based on dot matrix camera of the present invention is used to solve the technical problem in the prior art that it is difficult to determine whether the on-site camera picture obtained under the set scene is a real image without subsequent image processing. By selectively selecting multiple pieces of information as basic data for intelligent determination of whether the on-site camera picture obtained under the set scene is a real image without subsequent image processing, an artificial analysis model with customized structure design is introduced to complete the intelligent determination processing, thereby providing more reliable reference content for the monitoring server to judge the real scene of the set scene.

[0018] In summary, many benefits resulting from utilizing the principles of the present invention have been described. One or more embodiments of the present invention have been described for purposes of explanation and illustration. This is not intended to be an exhaustive description of the present invention or to limit the present invention to the exact form disclosed. Obvious modifications and changes may be made in light of the above teachings. One or more embodiments are selected and described in order to better explain the principles and applications of the present invention, thereby enabling one of ordinary skill in the art to better apply the present invention in different embodiments and in a variety of modified forms suitable for particular applications. The claims appended hereto define the scope of the present invention.

Claims

1. An image state detection device based on dot matrix photography, characterized in that: The device comprises: A network construction mechanism is used to perform multiple learning operations on a single-layer neural network to obtain a single-layer neural network after completing multiple learning operations, and output the single-layer neural network after completing multiple learning operations as an artificial analysis model; The dot matrix camera mechanism is used to perform camera processing on the facing environment to obtain a live camera picture corresponding to the facing environment; A parameter capture mechanism, connected to the dot matrix camera mechanism, for obtaining various camera parameters of the dot matrix camera mechanism by reading the bottom layer driving module of the dot matrix camera mechanism, wherein the various camera parameters of the dot matrix camera mechanism include the shutter speed, aperture value and camera frame rate of the dot matrix camera mechanism; An information identification mechanism, connected to the dot matrix camera mechanism, is used to obtain the contrast, resolution, signal-to-noise ratio, maximum noise amplitude and number of noise types of the live camera image and output it as item-by-item information of the live camera image; an intelligent determination mechanism, arranged at the monitoring server and connected to the network construction mechanism, the parameter capture mechanism and the information identification mechanism respectively, for inputting the shutter speed, aperture value and camera frame rate of the dot matrix camera mechanism and the item-by-item information of the on-site camera picture into the artificial analysis model in parallel, so as to obtain different binary values ​​output by the artificial analysis model, wherein when the binary value output by the artificial analysis model is 0B01, it represents that the on-site camera picture is a real image without subsequent image processing, and when the binary value output by the artificial analysis model is 0B00, it represents that the on-site camera picture is a non-real image after subsequent image processing; Among them, the shutter speed, aperture value and camera frame rate of the dot matrix camera mechanism and the item-by-item information of the on-site camera picture are input into the manual analysis model in parallel to obtain different binary values ​​output by the manual analysis model. When the binary value output by the manual analysis model is 0B01, it represents that the on-site camera picture is a real image that has not undergone subsequent image processing. When the binary value output by the manual analysis model is 0B00, it represents that the on-site camera picture is a non-real image that has undergone subsequent image processing. The method includes: converting the shutter speed, aperture value and camera frame rate of the dot matrix camera mechanism and the item-by-item information of the on-site camera picture into binary values ​​respectively and then inputting them into the manual analysis model in parallel.

2. The image state detection device based on dot matrix photography as claimed in claim 1, characterized in that: The shutter speed, aperture value, camera frame rate and item-by-item information of the dot matrix camera mechanism are input into the manual analysis model in parallel to obtain different binary values ​​output by the manual analysis model. When the binary value output by the manual analysis model is 0B01, it represents that the live camera picture is a real image that has not undergone subsequent image processing. When the binary value output by the manual analysis model is 0B00, it represents that the live camera picture is a non-real image that has undergone subsequent image processing. The method also includes: using a numerical simulation mode to complete the simulation and test of the data processing process of inputting the shutter speed, aperture value, camera frame rate and item-by-item information of the dot matrix camera mechanism into the manual analysis model in parallel to obtain different binary values ​​output by the manual analysis model.

3. The image state detection device based on dot matrix photography as claimed in claim 2, characterized in that: The device also includes: A field editable logic device is connected to the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism respectively, and is used to provide configuration operations of working parameters for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner; Among them, the field editable logic device is respectively connected to the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism, and is used to provide the configuration operation of working parameters for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner, including: the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism share the same working parameter configuration interface.

4. The image state detection device based on dot matrix photography as claimed in claim 3, characterized in that: The intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism use different configuration address data.

5. The image state detection device based on dot-matrix photography as claimed in claim 3, characterized in that: Establishing parallel connections of communication data links between the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism through parallel data buses; Among them, the parallel connection of the communication data link established between each of the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism through a parallel data bus includes: the parallel data bus is one of an 8-bit parallel data bus, a 16-bit parallel data bus and a 32-bit parallel data bus.

6. The image state detection device based on dot matrix photography as claimed in claim 2, characterized in that: The device also includes: A power support device is connected to the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism respectively, and is used to provide power distribution support of different working voltages for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner; Among them, the power support device is respectively connected to the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism, and is used to provide power distribution support with different working voltages for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner, including: in the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism, two or more devices with the same working voltage requirements use the same power supply line.

7. The image state detection device based on dot matrix photography as claimed in claim 6, characterized in that: The power support device is respectively connected to the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism, and is used to provide power distribution support with different working voltages for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner, and also includes: the power support device is an uninterruptible power supply device.

8. The image state detection device based on dot-matrix photography as claimed in claim 7, characterized in that: The power support device is respectively connected to the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism, and is used to provide power distribution support with different working voltages for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner, and also includes: providing different working voltages including 3.3V working voltage for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner.

9. The image state detection device based on dot-matrix photography as claimed in claim 8, characterized in that: The power support device is respectively connected to the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism, and is used to provide power distribution support with different working voltages for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner, and also includes: providing different working voltages including 5V working voltage for the intelligent determination mechanism, the network construction mechanism, the parameter capture mechanism and the information identification mechanism in a time-sharing manner.

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