CN115499703A - Image processing method, device, equipment and storage medium - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/44—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
- H04N21/44008—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs involving operations for analysing video streams, e.g. detecting features or characteristics in the video stream
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
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Abstract
The embodiment of the invention relates to an image processing method, an image processing device, image processing equipment and a storage medium, wherein the image processing method comprises the following steps: acquiring a first target image; determining a first scene corresponding to a first target image; determining a target object to be processed corresponding to a first scene from a first target image; and processing the target object in the first target image to enable the processed first target image to have a difference with the first target image before processing. Therefore, according to the scene corresponding to the image, the target object corresponding to the scene in the image is processed to protect the content of the personal privacy of the user related in the image, and therefore the purpose that the personal privacy of the user is prevented from being leaked in the original image is achieved.
Description
Technical Field
The embodiment of the invention relates to the technical field of computers, in particular to an image processing method, an image processing device, image processing equipment and a storage medium.
Background
The image or video shot by the camera of the terminal contains personal privacy data information (such as biological information such as shooting time, shooting place, human face/iris and the like), and the information about the privacy data can be acquired by third-party software or others, so that the personal privacy of the terminal user is leaked.
At present, in the related art, after the user finishes shooting, third-party software is generally adopted to process the image and/or the video so as to erase the content of personal privacy contained in the image or the video. However, privacy is handled in the above manner, which is not only inconvenient to use but may ignore some information. If the original picture is acquired by other people, the personal privacy information can be leaked, and the personal privacy can not be effectively protected.
Disclosure of Invention
In view of the above, to solve the technical problems or some of the technical problems, embodiments of the present invention provide an image processing method, an apparatus, a device and a storage medium.
In a first aspect, an embodiment of the present invention provides an image processing method, including:
acquiring a first target image;
determining a first scene corresponding to the first target image;
determining a target object to be processed corresponding to the first scene from the first target image;
and processing the target object in the first target image so that the processed first target image is different from the first target image before processing.
In an optional embodiment, the determining a first scene corresponding to the first target image includes:
receiving input scene information representing a first scene;
and determining the first scene according to the scene information.
In an optional embodiment, the determining a first scene corresponding to the first target image includes:
acquiring target image characteristic data of the first target image;
and determining the first scene corresponding to the target image characteristic data based on the corresponding relation between the image characteristic data and the scene model.
In an optional embodiment, the image processing method further comprises:
acquiring video stream data;
the acquiring of the first target image comprises:
and performing frame processing on the video stream data to obtain a plurality of first target images before processing.
In an optional embodiment, the processing the target object in the first target image to make the processed first target image different from the first target image before processing includes:
sequentially processing the target object in each pre-processed first target image according to the time sequence relation of the plurality of pre-processed first target images obtained by framing processing to obtain a plurality of processed first target images;
generating the processed video stream data from the plurality of processed first target images based on the time sequence relationship so that the processed video stream data is different from the video stream data before processing.
In an optional embodiment, the image processing method further comprises:
acquiring a second scene;
closing the rights object corresponding to the second scene;
the determining a first scene corresponding to the first target image comprises:
determining a first scene corresponding to the acquired first target image based on the second scene.
In an optional embodiment, the image processing method further comprises:
acquiring a third scene;
processing a preset audio corresponding to the third scene in the acquired video stream data;
the step of performing frame processing on the video stream data to obtain a plurality of first target images before processing includes:
performing framing processing on the video stream data after the preset audio is processed to obtain a plurality of first target images before processing;
the determining a first scene corresponding to the first target image comprises:
determining a first scene corresponding to the first target image before a plurality of processes based on the third scene.
In an optional embodiment, the processing the target object in the first target image includes:
masking the target object in the first target image;
in an alternative embodiment, the masking process includes at least one of:
carrying out fuzzy processing on the target object; or the like, or, alternatively,
adding a preset element on the target object to cover the target object, wherein the preset element comprises at least one of the following elements: texture, picture, whiteboard, and mosaic.
In an optional embodiment, the image processing method further comprises:
receiving an input information clearing request;
and removing the processed attribute information of the first target image based on the information removing request.
In an optional embodiment, the determining, from the first target image, a target object to be processed corresponding to the first scene includes:
determining a protected object tag corresponding to the first scene based on the first scene;
and determining a target object to be processed corresponding to the protection object label from the first target image.
In an alternative embodiment, the protected object tag includes at least one of:
human body label, face label, characters label, pet label, furniture label, car label, sound label and position label.
In a second aspect, an embodiment of the present invention further provides an image processing apparatus, including:
the image acquisition module is used for acquiring a first target image;
a scene determining module for determining a first scene corresponding to the first target image;
an object determination module, configured to determine, from the first target image, a target object to be processed corresponding to the first scene;
and the object processing module is used for processing the target object in the first target image so that the processed first target image is different from the first target image before processing.
In a third aspect, an embodiment of the present invention further provides an electronic device, including: a processor and a memory, the processor being configured to execute an image processing method program stored in the memory to implement the image processing method as described above.
In a fourth aspect, embodiments of the present invention also provide a storage medium, where one or more programs are stored, and the one or more programs are executable by one or more processors to implement the image processing method as described above.
The image processing method provided by the embodiment of the invention comprises the following steps: the method comprises the steps of obtaining a first target image, determining a first scene corresponding to the first target image, determining a target object to be processed corresponding to the first scene from the first target image, and processing the target object in the first target image so that the processed first target image is different from the first target image before processing. According to the method and the device, the target object corresponding to the scene in the image is processed according to the scene corresponding to the image, so that the content of the personal privacy of the user in the image is protected, and the personal privacy of the user is prevented from being leaked in the original image.
Drawings
FIG. 1 is a flowchart illustrating an image processing method according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating another image processing method according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of an image processing apparatus according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention;
in the above figures: 10. an image acquisition module; 20. a scene determination module; 30. an object determination module; 40. an object processing module;
400. an electronic device; 401. a processor; 402. a memory; 4021. an operating system; 4022. an application program; 403. a user interface; 404. a network interface; 405. a bus system.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
For the convenience of understanding of the embodiments of the present invention, the following description will be further explained with reference to specific embodiments, which are not to be construed as limiting the embodiments of the present invention.
Referring to fig. 1, fig. 1 is a schematic flowchart of an image processing method according to an embodiment of the present invention. The image processing method provided by the embodiment of the invention comprises the following steps:
s10: a first target image is acquired.
In this embodiment, the first target image is acquired by a user through a camera of a terminal, where the terminal includes but is not limited to a mobile phone, a tablet computer, and the like. Specifically, the user turns on the camera of the terminal, and performs shooting with the camera to acquire the first target image.
S20: a first scene corresponding to a first target object is determined.
In this embodiment, the first scene is a preset privacy protection scene, and a protection object tag is preset in each privacy protection scene. In this embodiment, the privacy protection scene may be a self-timer scene, a conference scene, a home scene, and the like, and the privacy protection scene may be set according to actual needs, which is not specifically limited in this embodiment.
The protected object tag includes at least one of: human body label, people's face label, characters label, pet label, furniture label, car label, sound label and position label, of course, the protection object label also can set up according to actual need. When the protection object label is a human body label, the object to be protected is an integral human-shaped area comprising limbs, heads, clothes, ornaments and the like; when the protection object label is a face label, the object to be protected is biological information such as an iris and the like expressed in short-distance self-shooting; when the protection object tag is a character tag, the object to be protected is character information in an image, such as content in a presentation, writing on a writing board, notes and other character information; when a pet tag is labeled as a protection object, the object to be protected is an animal appearing in the image, such as a cat, a dog, or the like; when the protection object label is a furniture label, the object to be protected is furniture such as a sofa and a decorative picture appearing in the image; when the protected object label is an automobile label, the object to be protected is an automobile of a car, a bus or a truck in which the image appears; when the protection object label is a sound label, protecting the voice class, for example, presetting a recording closing authority when shooting a video, or carrying out silencing treatment on the audio related to the video after the video shooting is finished; when the protection object tag is a position tag, the content of the position information is protected, for example, a preset closing position authority is set when the image or video is shot, or the position information related to the image or video is eliminated after the image or video is shot.
In this embodiment, when the privacy protection scene is a self-timer scene, the protection object tags corresponding to the self-timer scene may be a face tag, an ornament tag, and the like; when the privacy protection scene is a conference scene, the protection object tags corresponding to the conference scene can be human body tags, character tags, sound tags and the like; when the privacy protection scene is a home scene, the protection object tags corresponding to the home scene may be a human body tag, an ornament tag, a furniture tag, a pet tag, a position tag, and the like. And the protection object label preset in each privacy protection scene can be set according to the actual situation.
In this embodiment, the determining the first scene corresponding to the first target image in step S20 specifically includes:
receiving input scene information representing a first scene;
a first scene is determined from the scene information.
In this embodiment, a user may input scene information through a terminal, for example, the user may input the scene information through touch control, voice control, and the like, and when the scene information is received, the scene information is processed to obtain a first scene corresponding to the scene information. Wherein, the user can input scene information after the image capturing is finished or when the image capturing is finished. When the user inputs scene information while taking an image, the first scene may be determined as follows. The method comprises the following specific steps:
acquiring a second scene;
closing the rights object corresponding to the second scene;
based on the second scene, a first scene corresponding to the acquired first target image is determined.
In this embodiment, the second scene may be obtained according to the received scene information representing the second scene. The rights object may be a sound object or a location object. When the rights object is not included in the second scene, the rights object corresponding to the second scene does not need to be closed. The second scenario in this embodiment is identical to the first scenario. For example, when the second scene is a home scene and the user takes an image, the scene information is input to acquire the second scene corresponding to the scene information, and the position object corresponding to the second scene is closed. And after the corresponding authority object is closed, acquiring a first target image, and processing the first target image according to the second scene.
In this embodiment, the method for determining the first scene in step S20 may also be determined in the following manner, specifically as follows:
acquiring target image characteristic data of a first target image;
and determining a first scene corresponding to the target image characteristic data based on the corresponding relation between the image characteristic data and the scene model.
In this embodiment, the scene model may learn, by a machine, image feature data in an image to establish a corresponding scene model, and specifically, may learn, by a neural network, the image feature data to establish a corresponding scene model, where the scene model includes a plurality of different privacy-preserving scenes, that is, when matching between target image feature data of a first target image and image feature data of the scene model is successful, the first scene may be determined according to the target image feature data.
In this embodiment, the method for determining the first scene in step S20 may also be determined in the following manner, specifically as follows:
receiving input scene information representing a self-defined scene;
determining a self-defined scene according to the scene information;
receiving input label information representing a protection object label corresponding to a user-defined scene based on a scene configuration interface;
determining a label of the protected object according to the label information;
configuring a custom scene based on the protected object tag;
and determining a first scene corresponding to the first target image based on the configured custom scene.
In this embodiment, the scene information corresponding to the custom scene may be input when the image is shot, or may be input after the image shooting is finished, specifically, the tag information of the protected object tag corresponding to the custom scene may be input according to actual needs.
In this embodiment, it should be noted that, after the user-defined scene is determined, a scene configuration interface pops up, and based on the scene interface, tag information representing a protected object tag input by a user is received, so that the user-defined scene is configured according to the protected object tag corresponding to the tag information. And after the user-defined scene is configured, storing the user-defined scene, and taking the user-defined scene as a preset privacy protection scene so as to facilitate the user to process the target image in the future.
S30: and determining a target object to be processed corresponding to the first scene from the first target image.
In this embodiment, the step S30 specifically includes: determining a protection object label corresponding to the first scene based on the first scene;
and determining a target object to be processed corresponding to the protection object label from the first target image.
In this embodiment, the target object to be processed is a protected object corresponding to the protected object tag in the first scene, and the target object to be processed is visible. For example, when the first scene is a home scene, the target object to be processed may be a protection object corresponding to a body tag, an ornament tag, a furniture tag, a pet tag, and the like.
In this embodiment, a semantic segmentation technology of image processing may be adopted to identify the first target image, so as to obtain a target object to be processed corresponding to the first scene in the first target image.
In this embodiment, when the first scene is a custom scene, if it is identified that the coincidence degree of a protected object tag corresponding to a target object to be processed and a protected object tag corresponding to a certain scene is greater than a preset threshold value, a replacement prompt is triggered, when an input replacement prompt is received, the custom scene is replaced with a scene with the highest coincidence degree, and the target object to be processed corresponding to the replaced scene is determined from the first target image based on the replaced scene; when the input replacement prompt is not received, step S40 is executed. The preset threshold may be set according to actual needs, and is not specifically limited in this embodiment. Through the mode, the target object to be protected is prevented from being omitted by the user, and the user can use the target object conveniently.
S40: and processing the target object in the first target image to enable the processed first target image to have a difference with the first target image before processing.
In this embodiment, it should be noted that the difference between the processed first target image and the first target image before processing specifically means that the target object is covered by the processed first target image.
In this embodiment, the processing the target object in the first target image in step S40 includes:
and carrying out covering processing on the target object in the first target image.
In this embodiment, the masking the target object in the first target image specifically includes:
carrying out fuzzy processing on a target object; or add a preset element on the target object to cover the target object. The preset elements include at least one of the following elements: texture, picture, whiteboard, and mosaic.
In this embodiment, the picture may be a preset picture such as a cartoon picture, and the preset elements may be set according to actual needs.
As an example, the present embodiment describes a method for performing blurring processing on a target object to obtain a processed first target image:
assuming that there are N target objects to be processed in the first target image, a corresponding Mask (Mask) is generated by using a semantic segmentation technique. The method comprises the following specific steps:
in the above formula, i represents the sequence number of the target object to be processed; mask i (x, y) represents a mask of an ith target object to be processed; x is expressed as the row coordinate of the pixel in the ith target object to be processed; y is expressed as the column coordinates of the pixel in the ith target object to be processed.
Performing fuzzy processing on the region of the target object to be processed, specifically as follows:
the fuzzy convolution kernel is:
in the above formula, F (i, j) is represented as a fuzzy convolution kernel of k × k size; x is the number of ij The values are expressed as row i and column j of the fuzzy convolution kernel, wherein x, j is less than or equal to k, k =2r +1, r is expressed as the radius of the fuzzy processing, and delta is expressed as the adjustable fuzzy parameter.
After fuzzy processing, a background image can be obtained:
bgimg (x, y) in the above formula is expressed as background data at pixel point (x, y); srcimg (x + i, y + j) represents data within r of the neighborhood inner radius of the pixel point (x, y) in the first target image before processing.
The background image is fused with the first target image before processing to obtain the processed first target image, which specifically comprises:
dastimg(x,y)＝(1-Mask i (x,y))*srcimg(x,y)+Mask i (x,y)*bgimg(x,y)
dastimg(x，y)＝(1-Maski(x，y))*srcimg(x，y)+Maski(x，y)*bgimg(x，y)
in the above equation, dastmg (x, y) is expressed as an image value at a pixel point (x, y) in the first target image after the blurring processing.
S50: and receiving an input information clearing request, and clearing the attribute information of the processed first target image based on the information clearing request.
In the present embodiment, the attribute information may include randomly generated time information, randomly generated position information, terminal information, exposure parameter information, and the like. The attribute information of the first target image after the removal processing may be that the attribute information of the first target image after the processing is completely removed, or may be that a random number replaces the attribute information of the first target image after the processing.
In this embodiment, it should be noted that, after step S50 is executed, the camera of the terminal is exited.
According to the image processing method provided by the embodiment, the target object and the authority object corresponding to the scene in the image are processed according to the scene corresponding to the image, so that the content of the personal privacy of the user related in the image is protected, and the personal privacy of the user is prevented from being leaked in the original image.
Referring to fig. 2, fig. 2 is a schematic flowchart of another image processing method according to an embodiment of the present invention. The image processing method provided by the embodiment of the invention comprises the following steps:
s11: video stream data is acquired.
In this embodiment, the video stream data is collected by the user through a camera of the terminal, wherein the terminal includes, but is not limited to, a mobile phone, a tablet computer, and the like. Specifically, the user turns on a camera of the terminal, and performs shooting with the camera to acquire video stream data.
S21: and performing frame processing on the video stream data to obtain a plurality of first target images before processing.
In this embodiment, frame division processing is performed on video stream data according to a time sequence relationship, so as to obtain a plurality of first target images before processing according to a time sequence relationship.
S31: a first scene corresponding to a plurality of pre-processed first target images is determined.
In this embodiment, the first scene is a preset privacy protection scene, and the privacy protection scene is consistent with the above description, which is not repeated herein.
In this embodiment, the determining the first scene corresponding to the plurality of first target images in step S31 specifically includes:
receiving input scene information representing a first scene;
a first scene is determined from the scene information.
In this embodiment, a user may input scene information through a terminal, for example, the user may input the scene information through touch control, voice control, and the like, and when the scene information is received, the scene information is processed to obtain a first scene corresponding to the scene information. Wherein, the user can input the scene information after the video shooting is finished or when the video shooting is carried out. When the user inputs scene information while shooting a video, a first scene may be determined as follows. The method comprises the following specific steps:
acquiring a second scene;
closing the rights object corresponding to the second scene;
based on the second scene, a first scene corresponding to the acquired first target image is determined.
In this embodiment, the second scene may be obtained according to the received scene information representing the second scene. The rights object may be a sound protection tag or a location protection tag. When the rights object is not included in the second scene, the rights object corresponding to the second scene does not need to be closed. The second scenario in this embodiment is identical to the first scenario. For example, when the second scene is a home scene and a user takes a video, receiving input scene information to acquire the second scene corresponding to the scene information, and closing the position object corresponding to the second scene. And after the corresponding authority object is closed, acquiring video stream data, performing framing processing on the video stream data to acquire a plurality of first target images before processing, and processing the plurality of first target images before processing according to the second scene.
When the user inputs a scene after the video shooting is finished, the first scene may be determined according to the following manner, specifically as follows:
acquiring a third scene;
processing a preset audio corresponding to a third scene in the acquired video stream data;
performing frame processing on the video stream data after the preset audio is processed to obtain a plurality of first target images before processing;
based on the third scene, a first scene corresponding to the plurality of pre-processed first target images is determined.
In this embodiment, after the user finishes shooting the video, the third scene may be obtained according to the received scene information representing the third scene. The preset audio may specifically refer to an audio object included in the video stream data. When the third scene does not include the preset audio, the preset audio corresponding to the third scene does not need to be processed. The third scenario in this embodiment is identical to the first scenario. The specific step of processing the preset audio in the video may be to separate image data from audio data in the video stream data, so as to remove the audio data, thereby achieving the purpose of muting the video.
In the embodiment, the protection of personal privacy in the video is further enhanced by processing the authority object corresponding to the scene in the video and the preset audio.
In this embodiment, the method for determining the first scenario in step S31 may also be determined in the following manner, specifically as follows:
acquiring target image characteristic data of a first target image;
and determining a first scene corresponding to the target image characteristic data based on the corresponding relation between the image characteristic data and the scene model.
The method for determining the scene model is the same as described above, and this embodiment is not described herein again.
In this embodiment, the method for determining the first scene may also be determined in the following manner, specifically as follows:
receiving input scene information representing a self-defined scene;
determining a self-defined scene according to the scene information;
receiving input label information representing a protection object label corresponding to a user-defined scene based on a scene configuration interface;
determining a label of the protected object according to the label information;
configuring a custom scene based on the protected object tag;
and determining a first scene corresponding to the first target image based on the configured custom scene.
In this embodiment, the scene information corresponding to the custom scene may be input during shooting or may be input during acquisition of video stream data, and specifically, the tag information of the protected object tag corresponding to the custom scene may be input according to actual needs.
In this embodiment, it should be noted that, after the user-defined scene is determined, a scene configuration interface pops up, and based on the scene interface, tag information representing a protected object tag input by a user is received, so that the user-defined scene is configured according to the protected object tag corresponding to the tag information. And after the user-defined scene is configured, storing the user-defined scene, and taking the user-defined scene as a preset privacy protection scene so as to facilitate the user to process the target image in the future.
S41: and determining a target object to be processed corresponding to the first scene from each first target image before processing.
In this embodiment, the step S41 specifically includes:
determining a protection object label corresponding to the first scene based on the first scene;
and determining a target object to be processed corresponding to the protection object tag from each first target image before processing.
The semantic segmentation technology of image processing can be adopted to identify each pre-processed first target image so as to obtain a target object to be processed corresponding to the protection object label in the first scene in the pre-processed first target image of each processor. The target object to be processed is visible.
S51: and according to the time sequence relation of the plurality of first target images before processing obtained by the framing processing, sequentially processing the target object of each first target image before processing to obtain a plurality of first target images after processing.
In this embodiment, the processing the target object in the first target image before the processing in step S51 includes:
and carrying out covering processing on the target object in the first target image.
In this embodiment, the step S51 of performing a masking process on the target object in the first target image specifically includes:
carrying out fuzzy processing on a target object; or add a preset element on the target object to cover the target object. The preset elements include at least one of the following elements: texture, picture, whiteboard, and mosaic.
In this embodiment, the picture may be a preset picture such as a cartoon picture, and the preset elements may be set according to actual needs.
In this embodiment, after obtaining a plurality of processed first target images, if an input information removal request is received, the attribute information of the plurality of processed first target images is sequentially removed based on the information removal request.
The attribute information may include randomly generated time information, randomly generated position information, terminal information, exposure parameter information, and the like, among others. The attribute information of the first target image after being cleared may be completely cleared from the attribute information of the first target image after being cleared, or may be a random number instead of the attribute information of the first target image after being cleared.
S61: and generating the processed video stream data by the plurality of processed first target images based on the time sequence relation, so that the processed video stream data and the video stream data before processing have difference.
In this embodiment, based on the time sequence relationship, after the multiple processed first target images are subjected to frame combination processing, processed video stream data may be generated. The difference between the processed video stream data and the video stream data before processing specifically means that the target object is masked by the processed video stream data.
In this embodiment, it should be noted that, after step S61 is executed, the camera of the terminal is exited.
According to the image processing method provided by the embodiment, the target object, the authority object and the preset audio corresponding to the scene in the image of the video are processed according to the scene corresponding to the video, so that the content of the personal privacy of the user related in the video is protected, and the personal privacy of the user is prevented from being leaked in the original video.
Referring to fig. 3, fig. 3 is a schematic structural diagram of an image processing apparatus according to an embodiment of the present invention. The image processing apparatus provided in the embodiment of the present invention includes an image obtaining module 10, a scene determining module 20, an object determining module 30, and an object processing module 40, where the image obtaining module 10 is configured to obtain a first target object, the scene determining module 20 is configured to determine a first scene corresponding to the first target image, the object determining module 30 is configured to determine a target object to be processed corresponding to the first scene from the first target image, and the object processing module 40 is configured to process the target object in the first target image, so that the processed first target image and the processed first target image have a difference.
In this embodiment, the object determining module 30 is further configured to determine, based on the first scene, a protection object tag corresponding to the first scene, and determine, from the first target image, a target object to be processed corresponding to the protection object tag.
In this embodiment, the protected object tag at least includes one of the following:
human body label, face label, characters label, pet label, furniture label, car label, sound label and position label.
In this embodiment, the scene determining module 20 is further configured to receive input scene information representing a first scene; a first scene is determined based on the scene information.
In this embodiment, the scene determining module 20 is further configured to obtain target image feature data of the first target image, and determine the first scene corresponding to the target image feature data based on a corresponding relationship between the image feature data and the scene model.
In this embodiment, the object processing module 40 is further configured to perform a masking process on the target object in the first target image to implement processing on the target object in the first target image.
In this embodiment, it should be noted that the masking process includes at least one of the following:
carrying out fuzzy processing on a target object; or add a preset element on the target object to cover the target object. The preset elements include at least one of the following elements: texture, picture, whiteboard, and mosaic.
The pictures can be preset pictures such as cartoon pictures, and the preset elements can be set according to actual needs.
In this embodiment, the image obtaining module 10 is further configured to obtain video stream data, and perform framing processing on the video stream data to obtain a plurality of first target images before processing.
In this embodiment, the object processing module 40 is further configured to sequentially process the target object of each first pre-processed target image according to a time sequence relationship of the plurality of first pre-processed target images obtained through framing processing, so as to obtain a plurality of processed first target images; and generating the processed video stream data by the plurality of processed first target images based on the time sequence relation, so that the processed video stream data and the video stream data before processing have difference.
In this embodiment, the scene determining module 20 is further configured to acquire a second scene, close the rights object corresponding to the second scene based on the second scene, and determine a first scene corresponding to the acquired first target image based on the second scene.
In this embodiment, the scene determining module 20 is further configured to obtain a third scene, process a preset audio corresponding to the third scene in the obtained video stream data, perform framing processing on the video stream data after the preset audio is processed, obtain a plurality of first target images before processing, and determine, based on the third scene, a first scene corresponding to the plurality of first target images before processing.
According to the shooting device provided by the embodiment, the objects corresponding to the scenes in the images and the videos are processed according to the scenes corresponding to the images and the videos, so that the content of the personal privacy of the user involved in the images is protected, and the purpose of preventing the personal privacy of the user from being leaked in the original images is achieved.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, where the electronic device 400 shown in fig. 4 includes: at least one processor 401, memory 402, at least one network interface 404, and other user interfaces 403. The various components in the electronic device 400 are coupled together by a bus system 405. It is understood that the bus system 405 is used to enable connection communication between these components. The bus system 405 includes a power bus, a control bus, and a status signal bus in addition to a data bus. For clarity of illustration, however, the various buses are labeled as bus system 405 in fig. 4.
The user interface 403 may include, among other things, a display, a keyboard or a pointing device (e.g., a mouse, trackball (trackball), a touch pad or touch screen, etc.
It will be appreciated that memory 402 in embodiments of the invention may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The non-volatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), dynamic Random Access Memory (DRAM), synchronous Dynamic random access memory (Synchronous DRAM, SDRAM), double Data Rate Synchronous Dynamic random access memory (ddr Data Rate SDRAM, ddr SDRAM), enhanced Synchronous SDRAM (ESDRAM), synchlronous SDRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 402 described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
In some embodiments, memory 402 stores the following elements, executable units or data structures, or a subset thereof, or an expanded set thereof: an operating system 4021 and application programs 4022.
The operating system 4021 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is configured to implement various basic services and process hardware-based tasks. The application programs 4022 include various application programs, such as a Media Player (Media Player), a Browser (Browser), and the like, for implementing various application services. A program for implementing the method according to the embodiment of the present invention may be included in the application 4022.
In this embodiment of the present invention, by calling a program or an instruction stored in the memory 402, specifically, a program or an instruction stored in the application 4022, the processor 401 is configured to execute the method steps provided by the method embodiments, for example, including: acquiring a first target image; determining a first scene corresponding to a first target image; determining a target object to be processed corresponding to a first scene from a first target image; and processing the target object in the first target image to enable the processed first target image to have a difference with the first target image before processing.
The method disclosed in the above embodiments of the present invention may be applied to the processor 401, or implemented by the processor 401. The processor 401 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 401. The Processor 401 may be a general-purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software elements in the decoding processor. The software elements may be located in ram, flash, rom, prom, or eprom, registers, among other storage media that are well known in the art. The storage medium is located in the memory 402, and the processor 401 reads the information in the memory 402 and completes the steps of the method in combination with the hardware.
It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the Processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units configured to perform the functions described herein, or a combination thereof.
For a software implementation, the techniques described herein may be implemented by means of units performing the functions described herein. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
The electronic device provided in this embodiment may be the electronic device shown in fig. 4, and may execute all the steps of the image processing method shown in fig. 1-2, so as to achieve the technical effect of the image processing method shown in fig. 1-2, and for brevity, it is not described herein again.
The embodiment of the invention also provides a storage medium (computer readable storage medium). The storage medium herein stores one or more programs. Among others, the storage medium may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as read-only memory, flash memory, a hard disk, or a solid state disk; the memory may also comprise a combination of memories of the kind described above.
When one or more programs in the storage medium are executable by one or more processors to implement the image processing method described above as being performed on the side of the photographing apparatus.
The processor is configured to execute the photographing program stored in the memory to implement the following steps of the image processing method performed on the photographing apparatus side: acquiring a first target image; determining a first scene corresponding to a first target image; determining a target object to be processed corresponding to a first scene from a first target image; and processing the target object in the first target image to enable the processed first target image to have a difference with the first target image before processing.
Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the technical solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, a software module executed by a processor, or a combination of the two. A software module may reside in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, circuit, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, circuit, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, circuit, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present invention, which enable those skilled in the art to understand or practice the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention.
Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (15)
1. An image processing method, comprising:
acquiring a first target image;
determining a first scene corresponding to the first target image;
determining a target object to be processed corresponding to the first scene from the first target image;
and processing the target object in the first target image to enable the processed first target image to have a difference with the first target image before processing.
2. The method according to claim 1, wherein the determining a first scene corresponding to the first target image comprises:
receiving input scene information representing a first scene;
and determining the first scene according to the scene information.
3. The method of claim 1, wherein the determining the first scene corresponding to the first target image comprises:
acquiring target image characteristic data of the first target image;
and determining the first scene corresponding to the target image characteristic data based on the corresponding relation between the image characteristic data and the scene model.
4. The image processing method according to claim 1, characterized in that the image processing method further comprises:
acquiring video stream data;
the acquiring of the first target image comprises:
and performing frame processing on the video stream data to obtain a plurality of first target images before processing.
5. The image processing method according to claim 4, wherein the processing the target object in the first target image so that the processed first target image is different from the first target image before processing comprises:
sequentially processing the target object in each pre-processed first target image according to the time sequence relation of the plurality of pre-processed first target images obtained by framing processing to obtain a plurality of processed first target images;
generating the processed video stream data from the plurality of processed first target images based on the time sequence relationship so that the processed video stream data is different from the video stream data before processing.
6. The image processing method according to claim 1, characterized in that the image processing method further comprises:
acquiring a second scene;
closing the rights object corresponding to the second scene;
the determining a first scene corresponding to the first target image comprises:
determining a first scene corresponding to the acquired first target image based on the second scene.
7. The image processing method according to claim 4, characterized in that the image processing method further comprises:
acquiring a third scene;
processing a preset audio corresponding to the third scene in the acquired video stream data;
the step of performing frame processing on the video stream data to obtain a plurality of first target images before processing includes:
performing framing processing on the video stream data after the preset audio is processed to obtain a plurality of first target images before processing;
the determining a first scene corresponding to the first target image comprises:
determining a first scene corresponding to the first target image before a plurality of processes based on the third scene.
8. The method according to claim 1, wherein the processing the target object in the first target image comprises:
performing a masking process on the target object in the first target image.
9. The image processing method according to claim 8, wherein the mask processing includes at least one of:
carrying out fuzzy processing on the target object; or the like, or, alternatively,
adding a preset element on the target object to cover the target object; the preset elements include at least one of the following elements: texture, picture, whiteboard, and mosaic.
10. The image processing method according to claim 1, characterized in that the image processing method further comprises:
receiving an input information clearing request;
and removing the processed attribute information of the first target image based on the information removing request.
11. The image processing method according to claim 1, wherein the determining, from the first target image, a target object to be processed corresponding to the first scene comprises:
determining a protected object tag corresponding to the first scene based on the first scene;
and determining a target object to be processed corresponding to the protection object label from the first target image.
12. The image processing method of claim 11, wherein the protected object tag comprises at least one of:
human body label, face label, characters label, pet label, furniture label, car label, sound label and position label.
13. An image processing apparatus characterized by comprising:
the image acquisition module is used for acquiring a first target image;
a scene determining module for determining a first scene corresponding to the first target image;
an object determination module, configured to determine, from the first target image, a target object to be processed corresponding to the first scene;
and the object processing module is used for processing the target object in the first target image so that the processed first target image is different from the first target image before processing.
14. An electronic device, comprising: a processor and a memory, the processor being configured to execute an image processing method program stored in the memory to implement the image processing method of any one of claims 1 to 12.
15. A storage medium characterized in that the storage medium stores one or more programs executable by one or more processors to implement the image processing method of any one of claims 1 to 12.
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| PCT/CN2022/125963 WO2023109299A1 (en) | 2021-12-13 | 2022-10-18 | Image processing method and apparatus, and device and storage medium |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2023109299A1 (en) * | 2021-12-13 | 2023-06-22 | 中兴通讯股份有限公司 | Image processing method and apparatus, and device and storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011101161A (en) * | 2009-11-05 | 2011-05-19 | Canon Inc | Imaging device, control method of the same, reproducing device, and program |
| US20160148068A1 (en) * | 2014-08-15 | 2016-05-26 | Sony Corporation | Image processing apparatus and method, and electronic device |
| CN109274919A (en) * | 2017-07-18 | 2019-01-25 | 福州瑞芯微电子股份有限公司 | Method for secret protection, system, video call terminal and system in video calling |
| CN110443744A (en) * | 2018-05-03 | 2019-11-12 | 安讯士有限公司 | The method, apparatus and system of fog-level for image data to be applied to |
| CN110502974A (en) * | 2019-07-05 | 2019-11-26 | 深圳壹账通智能科技有限公司 | A kind of methods of exhibiting of video image, device, equipment and readable storage medium storing program for executing |
| CN112270018A (en) * | 2020-11-11 | 2021-01-26 | 中国科学院信息工程研究所 | Scene-sensitive system and method for automatically placing hook function |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2002037856A1 (en) * | 2000-11-06 | 2002-05-10 | Dynapel Systems, Inc. | Surveillance video camera enhancement system |
| CN106961559B (en) * | 2017-03-20 | 2019-03-05 | 维沃移动通信有限公司 | A kind of production method and electronic equipment of video |
| CN110298862A (en) * | 2018-03-21 | 2019-10-01 | 广东欧珀移动通信有限公司 | Method for processing video frequency, device, computer readable storage medium and computer equipment |
| CN108985176B (en) * | 2018-06-20 | 2022-02-25 | 阿里巴巴（中国）有限公司 | Image generation method and device |
| CN109743579A (en) * | 2018-12-24 | 2019-05-10 | 秒针信息技术有限公司 | A kind of method for processing video frequency and device, storage medium and processor |
| CN110933299B (en) * | 2019-11-18 | 2022-03-25 | 深圳传音控股股份有限公司 | Image processing method and device and computer storage medium |
| CN113627339A (en) * | 2021-08-11 | 2021-11-09 | 普联技术有限公司 | Privacy protection method, device and equipment |
| CN115499703A (en) * | 2021-12-13 | 2022-12-20 | 中兴通讯股份有限公司 | Image processing method, device, equipment and storage medium |
-
2021
- 2021-12-13 CN CN202111521605.1A patent/CN115499703A/en active Pending
-
2022
- 2022-10-18 WO PCT/CN2022/125963 patent/WO2023109299A1/en unknown
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011101161A (en) * | 2009-11-05 | 2011-05-19 | Canon Inc | Imaging device, control method of the same, reproducing device, and program |
| US20160148068A1 (en) * | 2014-08-15 | 2016-05-26 | Sony Corporation | Image processing apparatus and method, and electronic device |
| CN109274919A (en) * | 2017-07-18 | 2019-01-25 | 福州瑞芯微电子股份有限公司 | Method for secret protection, system, video call terminal and system in video calling |
| CN110443744A (en) * | 2018-05-03 | 2019-11-12 | 安讯士有限公司 | The method, apparatus and system of fog-level for image data to be applied to |
| CN110502974A (en) * | 2019-07-05 | 2019-11-26 | 深圳壹账通智能科技有限公司 | A kind of methods of exhibiting of video image, device, equipment and readable storage medium storing program for executing |
| CN112270018A (en) * | 2020-11-11 | 2021-01-26 | 中国科学院信息工程研究所 | Scene-sensitive system and method for automatically placing hook function |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2023109299A1 (en) * | 2021-12-13 | 2023-06-22 | 中兴通讯股份有限公司 | Image processing method and apparatus, and device and storage medium |
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| Publication number | Publication date |
|---|---|
| WO2023109299A1 (en) | 2023-06-22 |
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