Image processing method, device, equipment, monitoring system and storage medium

Abstract

The embodiments of the present application provide an image processing method, apparatus, device, monitoring system and storage medium. The image processing method includes: acquiring a target image, identifying the facial information of a target object in the target image, and obtaining a recognition result; if the recognition result satisfies the set conditions for recognition failure, determining whether the target object is located in a preset target area; if the target object is located in the preset target area, sending a first alarm message. The embodiments of the present application can solve the monitoring problem caused by the difficulty in or failure of face recognition when the light intensity is insufficient, the exposure rate is low, or the light intensity is high and the exposure rate is too high. By sending the first alarm message when the target object is located in the preset target area, the embodiments of the present application can promptly issue an alarm when someone enters the target area that needs to be monitored, thereby improving the feasibility and accuracy of monitoring.

Description

Technical Field

[0001] The present application relates to the field of image processing technology. Specifically, the present application relates to an image processing method, device, equipment, monitoring system and storage medium. Background Art

[0002] At present, most monitoring systems use facial recognition to monitor, so that when a stranger enters, the alarm device can be notified to issue an alarm.

[0003] However, when the light intensity is insufficient, the exposure rate is low, or the light intensity is high, the exposure rate is too high, it is easy to have problems such as difficulty in face recognition or recognition failure, resulting in reduced feasibility and accuracy of monitoring. Summary of the Invention

[0004] In response to the shortcomings of existing methods, this application proposes an image processing method, device, equipment, monitoring system and storage medium to solve the technical problems of reduced feasibility or accuracy of monitoring in existing technologies.

[0005] In a first aspect, an embodiment of the present application provides an image processing method, comprising:

[0006] Acquire a target image, recognize facial information of a target object in the target image, and obtain a recognition result;

[0007] If the recognition result meets the set conditions for recognition failure, determining whether the target object is located in the preset target area;

[0008] If the target object is located within the preset target area, a first alarm message is sent.

[0009] In one possible implementation, determining whether the target object is located within a preset target area includes:

[0010] Determine the position to be identified corresponding to the target object in the target image and obtain position information of the position to be identified; the position to be identified is located in the area of ​​the target image corresponding to the target object in the target image;

[0011] Based on the position information of the position to be identified and the position information of the target area, it is determined whether the target object is located in the preset target area.

[0012] In one possible implementation, determining whether the target object is located within a preset target area based on the location information of the location to be identified and the location information of the target area includes:

[0013] Determining location information of at least three set locations of the target area based on the location information of the target area; the location information of the target area includes location information of at least three set locations;

[0014] Determine at least three sub-regions based on the position information of the position to be identified and the position information of at least three set positions; each sub-region is formed by a line connecting the position to be identified and any two adjacent set positions;

[0015] If the sum of the areas of all sub-regions is greater than the area of ​​the target region, the target object is determined to be outside the preset target region; if the sum of the areas of all sub-regions is equal to the area of ​​the target region, the target object is determined to be within the preset target region.

[0016] In one possible implementation, the step of determining whether the target object is located within the preset target area further includes:

[0017] In the target image, determining at least three set positions and obtaining position information of the at least three set positions;

[0018] Based on the position information of at least three set positions, a target area is determined; the target area is a closed area formed by sequentially connecting the at least three set positions.

[0019] In one possible implementation, recognizing facial information of a target object in a target image to obtain a recognition result includes:

[0020] The time for recognizing the facial information of the target object in the target image exceeds a set time, and a first recognition result is obtained;

[0021] Alternatively, the facial information of the target object in the target image is recognized more than a set number of times, and a second recognition result is obtained;

[0022] Alternatively, for a preset number of consecutive target images in the video stream, the facial information of the target object in each target image fails to be recognized, and a third recognition result is obtained;

[0023] The recognition result satisfies the set conditions for recognition failure, including: if the recognition result is a recognition failure result, then the recognition result satisfies the set conditions for recognition failure; the recognition failure result includes at least one of the following: the first recognition result, the second recognition result, and the third recognition result.

[0024] In one possible implementation, recognizing facial information of a target object in a target image to obtain a recognition result includes:

[0025] Performing setting processing on the facial information of the target object in the target image to obtain facial features corresponding to the target object;

[0026] If the facial features do not match the preset facial features, a recognition mismatch result is obtained as the recognition result;

[0027] After identifying the facial information of the target object in the target image and obtaining the recognition result, the following steps are performed:

[0028] Based on the recognition results, a snapshot of the target object corresponding to the facial features is captured from the target image;

[0029] Based on the captured image, a second warning message is generated.

[0030] In one possible implementation, the image processing method further includes:

[0031] Get real-time light information;

[0032] If the light intensity corresponding to the real-time light information exceeds the preset light intensity range, it is determined whether the target object is located within the preset target area.

[0033] In a second aspect, an embodiment of the present application provides an image processing device, comprising:

[0034] The recognition module is used to obtain a target image, recognize the facial information of the target object in the target image, and obtain a recognition result;

[0035] A determination module, configured to determine whether the target object is located within a preset target area if the recognition result satisfies a set recognition failure condition;

[0036] The alarm module is configured to send a first alarm message if the target object is located within a preset target area.

[0037] In a third aspect, an embodiment of the present application provides an image processing device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the image processing method of the first aspect.

[0038] In a fourth aspect, an embodiment of the present application provides a monitoring system, comprising: a monitoring device and the image processing apparatus of the third aspect;

[0039] The monitoring device is communicatively connected to the image processing device and is used to issue an alarm based on the first alarm information.

[0040] In one possible implementation, the monitoring system further includes: a light sensor;

[0041] The light sensor is connected to the image processing device for transmitting real-time light information to the image processing device.

[0042] According to a fifth aspect, a computer-readable storage medium stores a computer program, which implements the image processing method according to the first aspect when executed by an image processing device.

[0043] The beneficial technical effects brought about by the technical solutions provided in the embodiments of the present application include:

[0044] In the process of identifying the facial information of the target object in the target image by the image processing method provided in the embodiment of the present application, if the recognition result meets the set conditions for recognition failure, another monitoring area recognition mode can be switched, so that the embodiment of the present application can solve the monitoring problem caused by the difficulty in or failure of face recognition when the light intensity is insufficient, the exposure rate is low, or the light intensity is high and the exposure rate is too high. The embodiment of the present application sends a first alarm message when the target object is within the preset target area, so that when someone enters the target area that needs to be monitored, an alarm can be issued in time, thereby improving the feasibility and accuracy of monitoring.

[0045] Additional aspects and advantages of the present application will be given in part in the following description, which will become apparent from the following description, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0047] Figure 1 A schematic diagram of the structure of an image processing system provided in an embodiment of the present application;

[0048] Figure 2 A flowchart of an image processing method provided in an embodiment of the present application;

[0049] Figure 3 A flowchart of a face recognition mode of an image processing method provided in an embodiment of the present application;

[0050] Figure 4 A schematic diagram of determining at least three set positions in a target image to form a target area provided by an embodiment of the present application;

[0051] Figure 5 A flowchart of a regional monitoring recognition mode of an image processing method provided in an embodiment of the present application;

[0052] Figure 6 and Figure 7 Schematic diagrams of scenarios in which a target object is located within a preset target area and a target object is located outside the preset target area, respectively, provided in an embodiment of the present application;

[0053] Figure 8 A schematic diagram of a framework of an image processing device provided in an embodiment of the present application;

[0054] Figure 9A schematic diagram of the framework of an image processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] The following describes the embodiments of the present application in conjunction with the accompanying drawings. It should be understood that the embodiments described below in conjunction with the accompanying drawings are exemplary descriptions for explaining the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions of the embodiments of the present application.

[0056] Those skilled in the art will understand that, unless otherwise stated, the singular forms "a," "an," "said," and "the" used herein may also include the plural forms. It should be further understood that the term "comprising" used in the specification of this application refers to the presence of the described features, integers, steps, operations, elements, and / or components, but does not exclude the implementation of other features, information, data, steps, operations, elements, components, and / or combinations thereof supported by the technical field. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, the element may be directly connected or coupled to the other element, or it may refer to the element and the other element establishing a connection relationship through an intermediate element. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein refers to at least one of the items defined by the term, for example, "A and / or B" may be implemented as "A," or as "B," or as "A and B."

[0057] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0058] The following is a detailed description of the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems with specific embodiments. It should be noted that the following embodiments can refer to, draw on, or combine with each other, and the same terms, similar features, and similar implementation steps in different embodiments will not be repeated.

[0059] An embodiment of the present application provides a monitoring system, comprising: a monitoring device and an image processing device;

[0060] The monitoring device is communicatively connected to an image processing device, and the monitoring device is configured to issue an alarm based on the first alarm information. The image processing device is configured to acquire a target image, recognize facial information of a target object in the target image, and obtain a recognition result; if the recognition result satisfies a set recognition failure condition, determine whether the target object is within a preset target area; and if the target object is within the preset target area, issue the first alarm information.

[0061] In some embodiments, the monitoring system also includes: a light sensor; the light sensor is communicatively connected to the image processing device, and the light sensor is used to send real-time light information to the image processing device, so that the image processing device determines whether the target object is located within a preset target area when the light intensity corresponding to the real-time light information exceeds a preset light intensity range.

[0062] See also Figure 1 As shown, the embodiment of the present application provides a structural diagram of an image processing system, which is used as an application scenario of an image processing method. Figure 1 As shown, the camera device 101 is used to capture the target image, the terminal device 103 represents the monitoring device, the server 102 represents the image processing device, the server 102 obtains the target image of the camera device 101, and sends the first alarm information to the terminal device 103, and the terminal device 103 displays the alarm information or plays the alarm information.

[0063] Optionally, the camera device 101 may also be connected to a terminal device 103 for communication, and the terminal device 103 sends the target image to the server 102. The terminal device 103 may also be connected to an alarm device for communication, and control the alarm device to generate an alarm.

[0064] Optionally, the server 102 may be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device 103 may be a smartphone, a tablet computer, a laptop computer, a desktop computer, an intelligent voice interaction device (such as a smart speaker), a wearable image processing device (such as a smart watch), an in-vehicle terminal, a smart home appliance (such as a smart TV), etc., but is not limited thereto.

[0065] Based on the same inventive concept, an embodiment of the present application provides an image processing method, including:

[0066] Acquire a target image, recognize facial information of a target object in the target image, and obtain a recognition result;

[0067] If the recognition result meets the set conditions for recognition failure, determining whether the target object is located in the preset target area;

[0068] If the target object is located within the preset target area, a first alarm message is sent.

[0069] Optionally, the target image is any frame image in a video stream captured by a camera device, the target area is within the visible range of the camera device, and recognizing the facial information of the target object in the target image is recognizing the facial information of the target object in each frame image.

[0070] Optionally, the target object is a person walking within the visible range captured by the camera. The setting condition is a recognition failure condition, so that when face recognition fails, the monitoring area recognition mode can be switched to.

[0071] Optionally, the first alarm information is used to display the alarm information on a display screen of the terminal device or to play the alarm information, or the terminal device controls an alarm device to issue an alarm.

[0072] Optionally, the target image in the embodiment of the present application may include at least one moving object, and each moving object is used as a target object, and the image processing method of the embodiment of the present application is adopted respectively.

[0073] In the process of identifying the facial information of the target object in the target image by the image processing method provided in the embodiment of the present application, if the recognition result meets the set conditions for recognition failure, another monitoring area recognition mode can be switched, so that the embodiment of the present application can solve the monitoring problem caused by the difficulty in or failure of face recognition when the light intensity is insufficient, the exposure rate is low, or the light intensity is high and the exposure rate is too high. The embodiment of the present application sends a first alarm message when the target object is within the preset target area, so that when someone enters the target area that needs to be monitored, an alarm can be issued in time, thereby improving the feasibility and accuracy of monitoring.

[0074] In the embodiment of the present application, when there is sufficient light and the exposure rate is high, a face recognition mode is adopted, that is, a stranger recognition monitoring strategy is applied. When the light intensity is insufficient and the exposure rate is low, or the light intensity is high and the exposure rate is too high, a regional monitoring strategy is adopted, that is, when face recognition fails, the mode is switched to the monitoring area recognition mode.

[0075] As an example, see Figure 2 As shown, an embodiment of the present application provides an image processing method, which includes: steps S201 to S204.

[0076] S201: Acquire a target image, recognize facial information of a target object in the target image, and obtain a recognition result.

[0077] S202: Determine if the recognition result meets the set conditions and switch to the monitoring area recognition mode.

[0078] Optionally, if the recognition result is a recognition failure, it is determined that the recognition result meets the set conditions and the mode is switched to the monitoring area recognition mode.

[0079] In some embodiments, recognizing facial information of a target object in a target image to obtain a recognition result includes:

[0080] The time for recognizing the facial information of the target object in the target image exceeds a set time, and a first recognition result is obtained;

[0081] Alternatively, the facial information of the target object in the target image is recognized more than a set number of times, and a second recognition result is obtained;

[0082] Alternatively, for a preset number of consecutive target images in the video stream, the facial information of the target object in each target image fails to be recognized, and a third recognition result is obtained;

[0083] The recognition result satisfies the set conditions for recognition failure, including: if the recognition result is a recognition failure result, then the recognition result satisfies the set conditions for recognition failure; the recognition failure result includes at least one of the following: the first recognition result, the second recognition result, and the third recognition result.

[0084] The image processing method of the embodiment of the present application can switch to the monitoring area recognition mode when the face recognition rate is low or recognition fails. The setting time can be 10 minutes, the setting number of times can be 5, and the continuous preset number of frames can be 10 consecutive images with facial information recognition failure.

[0085] In some embodiments, the image processing method further includes: acquiring real-time light information; if the light intensity corresponding to the real-time light information exceeds a preset light intensity range, determining whether the target object is located within a preset target area.

[0086] Optionally, after determining that the recognition result meets the set conditions for recognition failure and before switching to the monitoring area recognition mode, it also includes: obtaining real-time light information, and determining whether the light intensity corresponding to the real-time light information exceeds a preset light intensity range.

[0087] Correspondingly, switching to the monitoring area identification mode includes: if it is determined that the light intensity corresponding to the real-time light information exceeds a preset light intensity range, switching to the monitoring area identification mode.

[0088] The embodiment of the present application can combine face recognition and light intensity. When face recognition fails and the light intensity exceeds the preset light intensity range, it is confirmed that the face recognition failure is caused by light problems, further improving the timeliness and effectiveness of monitoring, and thus improving the accuracy of monitoring.

[0089] S203: Determine whether the target object is located in the preset target area. If so, execute step S204; if not, end.

[0090] S204: Send a first warning message.

[0091] Optionally, the first alarm information is used to display the alarm information on a display screen of the terminal device or to play the alarm information, or the terminal device controls an alarm device to issue an alarm.

[0092] In some embodiments, facial information of a target object in a target image is identified to obtain an identification result, including: setting and processing the facial information of the target object in the target image to obtain facial features corresponding to the target object; if the facial features do not match the preset facial features, an identification mismatch result is obtained as the identification result.

[0093] Correspondingly, if the facial features match the preset facial features, a recognition matching result is obtained.

[0094] Optionally, for identification matching or non-matching, facial features can be extracted under sufficient lighting conditions, that is, face recognition can be completed, so the results of identification non-matching and identification matching do not meet the set conditions, and the identification method of the regional monitoring recognition mode is not performed.

[0095] Correspondingly, after the facial information of the target object in the target image is identified and the identification result is obtained, the method includes: based on the identification result, capturing a snapshot of the target object corresponding to the facial features from the target image; and generating a second alarm message based on the snapshot.

[0096] Optionally, when a person appears within the camera's capture area, the camera's video stream is pulled. The facial recognition module extracts the target subject from the video stream and processes the target subject's facial information to obtain facial features. These features are then compared with pre-set facial features in a face database. If the target subject's facial features are not found in the existing face database, a portrait image corresponding to the target subject in the video stream is captured and marked to form a snapshot.

[0097] As an example, the embodiment of the present application provides a method for extracting facial features and performing image processing using a face recognition mode under sufficient light conditions, see Figure 3 As shown, the image processing method includes:

[0098] S301: Perform setting processing on facial information of a target object in a target image to obtain facial features corresponding to the target object.

[0099] S302: Determine whether the facial features match the preset facial features. If so, execute step S303; if not, execute step S304.

[0100] S303: Generate a recognition matching result as a recognition result.

[0101] Optionally, an identification and matching result is generated without generating an alarm message.

[0102] S304: Generate a recognition mismatch result as a recognition result.

[0103] Optionally, for identification matching or non-matching, facial features can be extracted under sufficient lighting conditions and face recognition can be completed, so the results of identification non-matching and identification matching do not meet the set conditions.

[0104] S305 : Based on the recognition result, a snapshot image of the target object corresponding to the facial features is captured from the target image.

[0105] S306: Generate and send second warning information based on the captured image.

[0106] Optionally, the second alarm information includes a captured image and may further include captured camera information, such as capture time and camera number. The second alarm information is sent to the terminal device. After receiving the alarm information, the terminal device displays the captured image and camera information on a display screen and triggers an alarm.

[0107] In some embodiments, before determining whether the target object is located within the preset target area, the method further includes:

[0108] In the target image, determining at least three set positions and obtaining position information of the at least three set positions;

[0109] Based on the position information of at least three set positions, a target area is determined; the target area is a closed area formed by sequentially connecting the at least three set positions.

[0110] As an example, see Figure 4 As shown, a schematic diagram of determining at least three set positions in a target image to form a target area is given. Image 01 of the current frame of the video stream of the camera device is obtained as the target image. Three set positions A, B and C are determined in image 01 of the current frame. A, B and C are used as vertices, and the closed area formed by connecting lines in sequence is the target area. In the area monitoring mode, an alarm will be issued when a person enters the target area.

[0111] It is understandable that the target area is determined according to the actual situation, and more than three set positions may be required to determine the outline of the target area. The embodiment of the present application is only an example and does not limit the shape of the target area. Other shapes are also within the scope of protection of the embodiment of the present application.

[0112] In some embodiments, a specific method for determining whether a target object is located within a preset target area includes:

[0113] Determine the position to be identified corresponding to the target object in the target image, and obtain position information of the position to be identified; the position to be identified is located in the area where the target image corresponding to the target object in the target image is located.

[0114] Based on the position information of the position to be identified and the position information of the target area, it is determined whether the target object is located in the preset target area.

[0115] Optionally, the position to be identified is a point in the target image corresponding to the target object in the target image. This point may be a point on the head of the target object, and this point is used as the position to be identified to represent the position of the target object.

[0116] In some embodiments, determining whether the target object is located within a preset target area based on the location information of the location to be identified and the location information of the target area includes:

[0117] Determining location information of at least three set locations of the target area based on the location information of the target area; the location information of the target area includes location information of at least three set locations;

[0118] Determine at least three sub-regions based on the position information of the position to be identified and the position information of at least three set positions; each sub-region is formed by a line connecting the position to be identified and any two adjacent set positions;

[0119] If the sum of the areas of all sub-regions is greater than the area of ​​the target region, the target object is determined to be outside the preset target region; if the sum of the areas of all sub-regions is equal to the area of ​​the target region, the target object is determined to be within the preset target region.

[0120] Optionally, the position information of the target area is pre-stored, and the position of the target area is determined in advance in the target image based on at least three set positions. In the embodiment of the present application, the set position of the sub-area is determined by selecting the set position of the target area. In this way, the positions of each vertex of the target area are selected to facilitate determination of the area of ​​the sub-area.

[0121] Optionally, the area of ​​the target region is determined based on location information of the target region.

[0122] As an example, see Figure 5 As shown, an embodiment of the present application provides a method for image processing using a regional monitoring recognition mode. The image processing method includes: steps S501 to S506.

[0123] S501 , determining a position to be identified corresponding to a target object in a target image, and obtaining position information of the position to be identified; the position to be identified is located in an area where a target picture corresponding to the target object in the target image is located.

[0124] Optionally, the position to be identified is a point in a target image corresponding to the target object in the target image, and may be the center of the head of the target object in the target image.

[0125] S502 : Determine location information of at least three set locations of the target area based on the location information of the target area; the location information of the target area includes location information of at least three set locations.

[0126] As an example, see Figure 6 and Figure 7 As shown, a, b, c, d, e and f are all set positions, and the position information of the target area includes the position information of the set positions a, b, c, d, e and f. The target area is determined based on the set positions a, b, c, d, e and f, and the set position used to calculate the sub-area is used to determine the set position of the target area.

[0127] S503 : Determine at least three sub-regions based on the position information of the position to be identified and the position information of at least three set positions; each sub-region is formed by a line connecting the position to be identified and any two set positions.

[0128] Optional, see Figure 6 and Figure 7 As shown, the line connecting the position to be identified P and any two of the set positions a, b, c, d, e and f constitutes a sub-area, forming five sub-areas.

[0129] S504: Determine whether the sum of the areas of all sub-regions is greater than the area of ​​the target region; if not, execute step S505; if so, execute step S506.

[0130] Alternatively, to determine whether the person's location is within the target area, the area sum method can be used. If point P is within the area, the sum of the areas of the polygon formed by the lines connecting point P to each vertex is the sum of the polygon areas. Otherwise, point P is not within the area formed by each point. Using P as the reference point and a, b, c, d...n as the polygon vertices, the sum of the areas of all sub-areas can be obtained using the following formula:

[0131] S=0.5*((ax-px)*(ay-py)-(bx-px)*(by-py)+(bx-px)*(by-py)-(cx-px)*(cy-py)+...+(nx-px)*(ny-py)-(ax-px)*(ay-py)).

[0132] Among them, ax and ay are the coordinate values ​​of the x direction and y direction of the set position a respectively, ax and ay are the position information of the set position a, and the position information of the remaining points is the same.

[0133] Alternatively, see Figure 6 and Figure 7 As shown in , a, b, c, d, e and f are used as polygon vertices and put into the formula for finding the sum of the areas of all sub-regions to obtain the sum of the areas of all sub-regions. Figure 6 As shown in , the sum of the areas of all sub-regions is equal to the area of ​​the target region, and the target object is located in the target region. Figure 7 As shown, the sum of the areas of all sub-regions is larger than the area of ​​the target region, and the target object is located outside the target region.

[0134] S505: Determine that the target object is outside the preset target area, and do not issue a first alarm message.

[0135] S506: Determine that the target object is located in a preset target area and issue a first alarm message.

[0136] Optionally, the first alarm information is used to display the alarm information on a display screen of the terminal device or to play the alarm information, or the terminal device controls an alarm device to issue an alarm.

[0137] The image processing method of the embodiment of the present application can adopt a regional monitoring and recognition mode under conditions of insufficient lighting and low exposure, to make up for the deficiency that faces cannot be captured clearly or even cannot be captured in dark conditions.

[0138] The regional monitoring recognition mode adopted in the embodiment of the present application is to draw points on a two-dimensional image within the range that can be captured by the camera, and determine three or more points. These points form a closed area, forming a target area. When a person approaches, the person's position is obtained, and the person's position is calculated and compared with the position of the circled target area. If the person's position is within the range of the target area, a first alarm message is generated and sent to the monitoring device. After the monitoring device processes the first alarm message, it is distributed to the display screen and triggers an alarm.

[0139] Based on the same inventive concept, the present application provides an image processing device, see Figure 8 As shown, the image processing device 80 includes: an identification module 810 , a determination module 820 and an alarm module 830 .

[0140] The recognition module 810 is used to obtain a target image, recognize facial information of a target object in the target image, and obtain a recognition result.

[0141] The determination module 820 is configured to determine whether the target object is located within a preset target area if the recognition result satisfies a set condition of recognition failure.

[0142] The alarm module 830 is configured to send a first alarm message if the target object is located within a preset target area.

[0143] Optionally, the recognition module 810 is used to recognize the facial information of the target object in the target image for a time period exceeding a set time period, thereby obtaining a first recognition result; or, the facial information of the target object in the target image is recognized for a number of times exceeding a set number of times, thereby obtaining a second recognition result; or, for a continuous preset number of target frames of the video stream, the facial information of the target object in each target image fails to be recognized, thereby obtaining a third recognition result.

[0144] Optionally, the determination module 820 is configured to determine that if the recognition result is a recognition failure result, the recognition result satisfies a set condition for recognition failure; the recognition failure result includes at least one of the following: the first recognition result, the second recognition result, and the third recognition result.

[0145] Optionally, the determination module 820 is configured to obtain real-time light information; if the light intensity corresponding to the real-time light information exceeds a preset light intensity range, determine whether the target object is located within a preset target area.

[0146] Optionally, the recognition module 810 is used to set and process the facial information of the target object in the target image to obtain facial features corresponding to the target object; if the facial features do not match the preset facial features, a recognition mismatch result is obtained as the recognition result.

[0147] Optionally, the determination module 820 is used to determine at least three set positions in the target image and obtain position information of the at least three set positions; determine the target area based on the position information of the at least three set positions; the target area is a closed area formed by connecting the at least three set positions in sequence.

[0148] Optionally, the determination module 820 is configured to determine a location to be identified corresponding to a target object in a target image and obtain location information of the location to be identified; the location to be identified is located within an area of ​​a target image corresponding to the target object in the target image. Based on the location information of the location to be identified and the location information of the target area, it is determined whether the target object is located within a preset target area.

[0149] Optionally, the determination module 820 is used to determine the position information of at least three set positions of the target area based on the position information of the target area; the position information of the target area includes the position information of at least three set positions; based on the position information of the position to be identified and the position information of at least three set positions, at least three sub-areas are determined; each sub-area is formed by a line connecting the position to be identified and any two set positions; if the sum of the areas of all sub-areas is greater than the area of ​​the target area, it is determined that the target object is located outside the preset target area; if the sum of the areas of all sub-areas is equal to the area of ​​the target area, it is determined that the target object is located within the preset target area.

[0150] The device of the embodiment of the present application can execute the method provided by the embodiment of the present application, and its implementation principle is similar. The actions performed by each module in the device of each embodiment of the present application correspond to the steps in the method of each embodiment of the present application. For the detailed functional description of each module of the device, please refer to the description in the corresponding method shown in the previous text, and will not be repeated here.

[0151] Based on the same inventive concept, an embodiment of the present application provides an image processing device, including a memory, a processor, and a computer program stored in the memory, and the processor executes the computer program to implement the image processing method of any embodiment of the present application.

[0152] In an optional embodiment, the present application provides an image processing device, such as Figure 9 As shown, Figure 9 The image processing device 2000 shown includes a processor 2001 and a memory 2003 . The processor 2001 and the memory 2003 are communicatively connected to each other, for example, via a bus 2002 .

[0153] Processor 2001 can be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 2001 can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0154] The bus 2002 may include a path for transmitting information between the above components. The bus 2002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 2002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 9 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0155] The memory 2003 may be a ROM (Read-Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (random access memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read-Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0156] Optionally, the image processing device 2000 may further include a communication unit 2004. The communication unit 2004 may be used to receive and transmit signals. The communication unit 2004 may allow the image processing device 2000 to communicate with other devices wirelessly or by wire to exchange data. It should be noted that in actual applications, the number of communication units 2004 is not limited to one.

[0157] Optionally, the image processing device 2000 may further include an input unit 2005. The input unit 2005 may be configured to receive input digital, character, image, and / or sound information, or to generate key signal input related to user settings and function control of the image processing device 2000. The input unit 2005 may include, but is not limited to, one or more of a touch screen, a physical keyboard, function keys (such as a volume control key, a power key, etc.), a trackball, a mouse, a joystick, a camera, a microphone, and the like.

[0158] Optionally, the image processing device 2000 may further include an output unit 2006. The output unit 2006 may be used to output or display information processed by the processor 2001. The output unit 2006 may include, but is not limited to, one or more of a display device, a speaker, a vibration device, and the like.

[0159] Although Figure 9 The image processing apparatus 2000 is shown as having various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead.

[0160] Optionally, the memory 2003 is used to store application code for executing the solution of the present application, and the execution is controlled by the processor 2001. The processor 2001 is used to execute the application code stored in the memory 2003 to implement any image processing method provided in the embodiments of the present application.

[0161] Based on the same inventive concept, a computer-readable storage medium stores a computer program thereon, and when the computer program is executed by an image processing device, the image processing method of any embodiment of the present application is implemented.

[0162] The computer-readable medium of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, a system, device or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0163] In the embodiments of the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0164] A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0165] Those skilled in the art will appreciate that the steps, measures, and schemes in the various operations, methods, and processes discussed in this application may be interchanged, modified, combined, or deleted. Furthermore, other steps, measures, and schemes in the various operations, methods, and processes discussed in this application may also be interchanged, modified, rearranged, decomposed, combined, or deleted. Furthermore, steps, measures, and schemes in the prior art that are similar to those disclosed in this application may also be interchanged, modified, rearranged, decomposed, combined, or deleted.

[0166] In the description of this application, the directions or positional relationships indicated by words such as "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", and "outside" are exemplary directions or positional relationships based on the accompanying drawings. They are intended to facilitate or simplify the description of the embodiments of this application, and do not indicate or imply that the device or component referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, they should not be understood as limitations on this application.

[0167] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. Throughout this application, unless otherwise specified, "plurality" means two or more.

[0168] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to direct connections, indirect connections through an intermediate medium, or internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.

[0169] In the description of this specification, specific features, structures, materials or characteristics may be combined in an appropriate manner in any one or more embodiments or examples.

[0170] It should be understood that, although the various steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, the order of implementation of these steps is not limited to the order indicated by the arrows. Unless otherwise clearly stated herein, in some implementation scenarios of the embodiments of the present application, the steps in each process can be performed in other orders as required. Moreover, some or all of the steps in each flowchart may include multiple sub-steps or multiple stages based on actual implementation scenarios. Some or all of these sub-steps or stages may be executed at the same time, or may be executed at different times in different scenarios at the execution time. The execution order of these sub-steps or stages may be flexibly configured as required, and the embodiments of the present application do not limit this.

[0171] The above is only part of the implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, without departing from the technical concept of the solution of the present application, other similar implementation methods based on the technical ideas of the present application also fall within the protection scope of the embodiments of the present application.

Claims

1. An image processing method, characterized in that: include: Acquire a target image, and recognize facial information of a target object in the target image to obtain a recognition result; If the recognition result satisfies the set condition of recognition failure, determining whether the target object is located in a preset target area according to the target image; If the target object is located within the preset target area, sending a first alarm message; The method further comprises: Get real-time light information; If the light intensity corresponding to the real-time light information is greater than a preset light intensity range, determining whether the target object is located within a preset target area; The step of identifying facial information of a target object in the target image to obtain a recognition result includes: The time for recognizing the facial information of the target object in the target image exceeds a set time, thereby obtaining a first recognition result; Alternatively, the facial information of the target object in the target image is recognized more than a set number of times, and a second recognition result is obtained; Alternatively, for a preset number of consecutive target images in the video stream, the facial information of the target object in each target image fails to be recognized, and a third recognition result is obtained; The recognition result satisfies the set condition of recognition failure, including: if the recognition result is a result of recognition failure, then the recognition result satisfies the set condition of recognition failure; the result of recognition failure includes at least one of the following: the first recognition result, the second recognition result, and the third recognition result; Determining whether the target object is located within a preset target area includes: Determine a position to be identified corresponding to a target object in the target image, and obtain position information of the position to be identified; the position to be identified is located in an area where a target picture corresponding to the target object in the target image is located; Determining whether the target object is located within a preset target area based on the location information of the to-be-identified location and the location information of the target area; The determining whether the target object is located within a preset target area based on the position information of the position to be identified and the position information of the target area includes: Determining, based on the location information of the target area, location information of at least three set locations of the target area; the location information of the target area includes location information of at least three set locations; Determine at least three sub-regions based on the position information of the position to be identified and the position information of the at least three set positions; each of the sub-regions is formed by a line connecting the position to be identified and any two adjacent set positions; If the sum of the areas of all the sub-areas is greater than the area of ​​the target area, it is determined that the target object is outside the preset target area; if the sum of the areas of all the sub-areas is equal to the area of ​​the target area, it is determined that the target object is within the preset target area.

2. The image processing method according to claim 1, wherein: Before determining whether the target object is located within the preset target area, the method further includes: In the target image, determining at least three set positions, and acquiring position information of the at least three set positions; The target area is determined based on the position information of the at least three set positions; the target area is a closed area formed by sequentially connecting the at least three set positions.

3. The image processing method according to claim 1, wherein: The step of identifying facial information of a target object in the target image to obtain a recognition result includes: Performing setting processing on facial information of a target object in the target image to obtain facial features corresponding to the target object; If the facial features do not match the preset facial features, a recognition mismatch result is obtained as the recognition result; Recognizing facial information of a target object in the target image and obtaining a recognition result includes: Based on the recognition result, intercepting a snapshot of the target object corresponding to the facial feature from the target image; Based on the captured image, a second warning message is generated and sent.

4. An image processing device, characterized in that include: A recognition module is used to obtain a target image, recognize facial information of a target object in the target image, and obtain a recognition result; a determination module, configured to determine whether the target object is located within a preset target area based on the target image if the recognition result satisfies a set condition of recognition failure; an alarm module, configured to send a first alarm message if the target object is located within a preset target area; The determination module is further configured to obtain real-time light information; if the light intensity corresponding to the real-time light information is greater than a preset light intensity range, determine whether the target object is located within a preset target area; The recognition module is specifically configured to obtain a first recognition result when the time for recognizing facial information of a target object in the target image exceeds a set time; Alternatively, the facial information of the target object in the target image is recognized more than a set number of times, and a second recognition result is obtained; Alternatively, for a preset number of consecutive target images in the video stream, the facial information of the target object in each target image fails to be recognized, and a third recognition result is obtained; The recognition result satisfies the set condition of recognition failure, including: if the recognition result is a result of recognition failure, then the recognition result satisfies the set condition of recognition failure; the result of recognition failure includes at least one of the following: the first recognition result, the second recognition result, and the third recognition result; The determination module is specifically used to determine the position to be identified corresponding to the target object in the target image, and obtain the position information of the position to be identified; the position to be identified is located in the area where the target picture corresponding to the target object in the target image is located; based on the position information of the target area, the position information of at least three set positions of the target area is determined; the position information of the target area includes the position information of at least three set positions; based on the position information of the position to be identified and the position information of the at least three set positions, at least three sub-areas are determined; each sub-area is formed by a line connecting the position to be identified and any two adjacent set positions; if the sum of the areas of all the sub-areas is greater than the area of ​​the target area, it is determined that the target object is located outside the preset target area; if the sum of the areas of all the sub-areas is equal to the area of ​​the target area, it is determined that the target object is located within the preset target area.

5. An image processing device comprising a memory, a processor, and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the image processing method according to any one of claims 1 to 3.

6. A monitoring system, characterized in that: include: A monitoring device and an image processing apparatus as claimed in claim 5; The monitoring device is communicatively connected to the image processing device and is configured to issue an alarm based on the first alarm information.

7. The monitoring system according to claim 6, characterized in that: The monitoring system further includes: a light sensor; The light sensor is communicatively connected to the image processing device and is used to send real-time light information to the image processing device.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by an image processing device, the image processing method according to any one of claims 1 to 3 is implemented.

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