CN114418865A - Image processing method, device, equipment and storage medium - Google Patents

Abstract

The present disclosure relates to an image processing method, apparatus, device, and storage medium. The method includes: acquiring a target image to be processed; determining a face area and a target area in the target image, where the target area includes a face area and the surrounding preset area; in response to detecting that the target object in the target area meets the processing conditions, the target object is processed; the processed target image is determined based on the processed face area and the processed target object . The present disclosure can avoid the problem of distortion and deformation of the target area due to the processing of the face area, avoid image distortion, and further improve the processing quality of the image.

Description

Image processing method, device, device and storage medium

technical field

The present disclosure relates to the field of terminal technologies, and in particular, to an image processing method, apparatus, device, and storage medium.

Background technique

With the popularization of terminal devices such as smartphones, more and more users use mobile phones to capture images. For the needs of beautiful images, many users will process the captured images. In response to this demand, many beauty apps have emerged. Nowadays, most of the cameras that come with terminal devices also add a beauty function to process the captured user images during the user's photographing process.

However, the image processing algorithms in the related art usually only process the user's face, resulting in image distortion and affecting the quality of image processing.

SUMMARY OF THE INVENTION

In order to overcome the problems existing in the related art, the embodiments of the present disclosure provide an image processing method, apparatus, device, and storage medium, so as to solve the defects in the related art.

According to a first aspect of the embodiments of the present disclosure, there is provided an image processing method, the method comprising:

Get the target image to be processed;

determining a target area in the target image, the target area includes a face area and a surrounding preset area;

processing the target object in response to detecting that the target object in the target area satisfies the processing condition;

The processed target image is determined based on the processed face region and the processed processed target object.

In one embodiment, the target object satisfies processing conditions, including at least one of the following:

The position of the target object in the target image satisfies the set position condition;

The scale of the target object in the target image satisfies the set scale condition.

In one embodiment, the target object includes a hand;

The processing of the target object includes:

determining the characteristic information of the hand;

Searching for a sample image matching the hand in a preset hand image library based on the feature information;

The target object after processing the hand based on the sample image.

In one embodiment, the feature information includes target ratios of palms and fingers;

The searching for a sample image matching the hand in the preset hand image library based on the feature information includes:

In the preset hand image library, a sample image whose proportions of the palm and fingers are most similar to the target proportion is searched.

In one embodiment, the processing of the hand based on the sample image includes:

The target scale of the palm and the fingers in the hand is adjusted based on the scale of the palm and the fingers in the sample image.

In one embodiment, the processing of the hand based on the sample image includes:

acquiring the first image parameter of the face region and the second image parameter of the sample image, the first image parameter and the second image parameter including at least one of color and texture;

The image parameters of the hand are processed based on the first image parameters and the second image parameters.

In one embodiment, determining the processed target image based on the processed face region and the processed target object includes:

determining a second positional relationship between the processed face region and the processed target object based on the first relationship between the face region in the target image and the target object;

Based on the second positional relationship, the positional relationship between the first layer corresponding to the processed face region and the second layer corresponding to the processed target object is adjusted to obtain a processed target image.

In one embodiment, the method further includes:

In response to detecting that there is a blank area between the adjusted first layer and the second layer, the blank area is filled with a preset image filling method.

According to a second aspect of the embodiments of the present disclosure, there is provided an image processing apparatus, the apparatus comprising:

a target image acquisition module, used to acquire the target image to be processed;

a target area determination module, configured to determine a target area in the target image, the target area including a face area and a peripheral preset area;

a target object processing module, configured to process the target object in response to detecting that the target object in the target area meets the processing conditions;

The processed image determination module is configured to determine the processed target image based on the processed face region and the processed target object.

In one embodiment, the target object satisfies processing conditions, including at least one of the following:

The position of the target object in the target image satisfies the set position condition;

The scale of the target object in the target image satisfies the set scale condition.

In one embodiment, the target area includes a hand;

The target object processing module includes:

a feature information determination unit, configured to determine the feature information of the hand;

a sample image search unit, configured to search for a sample image matching the hand in a preset hand image library based on the feature information;

A target object processing unit, configured to process the hand based on the sample image.

In one embodiment, the feature information includes target ratios of palms and fingers;

The sample image search unit is further configured to search the preset hand image library for a sample image whose proportions of the palm and fingers are the closest to the target proportion.

In one embodiment, the target object processing unit is further configured to adjust the target ratio of the palm and the fingers in the hand based on the ratio of the palm and the fingers in the sample image.

In one embodiment, the target object processing unit is further used for:

acquiring the first image parameter of the face region and the second image parameter of the sample image, the first image parameter and the second image parameter including at least one of color and texture;

The image parameters of the hand are processed based on the first image parameters and the second image parameters.

In one embodiment, the processing image determination module includes:

a positional relationship determining unit, configured to determine a second positional relationship between the processed face region and the processed target object based on the first relationship between the face region in the target image and the target object ;

A processed image determination unit, configured to adjust the positional relationship between the first layer corresponding to the processed face region and the second layer corresponding to the processed target object based on the second positional relationship, to obtain The processed target image.

In one embodiment, the processing image determination module further includes:

The blank area filling unit is configured to fill the blank area with a preset image filling method in response to detecting that there is a blank area between the adjusted first layer and the second layer.

According to a third aspect of the embodiments of the present disclosure, there is provided an electronic device, the device comprising:

a processor and a memory for storing instructions executable by the processor;

wherein the processor is configured to:

Get the target image to be processed;

Determine the face area and the target area in the target image, and the target area includes the face area and the surrounding preset area;

processing the target object in response to detecting that the target object in the target area satisfies the processing condition;

The processed target image is determined based on the processed face region and the processed target object.

According to a fourth aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium on which a computer program is stored, and the program is executed by a processor to realize:

Get the target image to be processed;

Determine the face area and the target area in the target image, and the target area includes the face area and the surrounding preset area;

processing the target object in response to detecting that the target object in the target area satisfies the processing condition;

The processed target image is determined based on the processed face region and the processed target object.

The technical solutions provided by the embodiments of the present disclosure may include the following beneficial effects:

The present disclosure obtains the target image to be processed, determines the face area and the target area in the target image, and then processes the target object in response to detecting that the target object in the target area meets the processing conditions, Then, the processed target image is determined based on the processed face area and the processed target object, which can avoid the problem of distortion of the target area due to the processing of the face area, avoid image distortion, and improve the image quality. Handling quality.

It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description serve to explain the principles of the disclosure.

1 is a flowchart of an image processing method according to an exemplary embodiment;

FIG. 2 is a flowchart showing how to process the target object according to an exemplary embodiment;

3 is a flowchart showing how to process the target object based on the sample image according to an exemplary embodiment;

4 is a flowchart illustrating how to determine a processed target image based on a processed face region and a processed target object, according to an exemplary embodiment;

5 is a block diagram of an image processing apparatus according to an exemplary embodiment;

6 is a block diagram of an image processing apparatus according to another exemplary embodiment;

Fig. 7 is a block diagram of an electronic device according to an exemplary embodiment.

Detailed ways

Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. Where the following description refers to the drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as recited in the appended claims.

FIG. 1 is a flowchart of an image processing method according to an exemplary embodiment; the method in this embodiment can be applied to a terminal device with image processing function (eg, a smart phone, a tablet computer, a notebook computer, or a wearable device) Wait).

As shown in Figure 1, the method includes the following steps S101-S104:

In step S101, a target image to be processed is acquired.

In this embodiment, after the user collects the target image through the image acquisition device (eg, camera, etc.) of the terminal device, the terminal device can acquire the target image through its own image processing device.

The above target image may be a preview image acquired by the terminal device in the process of collecting the user's image, or may be an image to be processed selected by the user from an electronic album stored in the terminal device, which is not limited in this embodiment.

In step S102, the face area and the target area in the target image are determined.

In this embodiment, after acquiring the target image to be processed, the terminal device can determine the face area and the target area in the target image, where the target area includes a face area and a surrounding preset area, wherein the face area The partial region may be the region of the user's face corresponding to the target image.

For example, after obtaining the above-mentioned target image, face recognition can be performed on the target image to determine the area where the recognized face is located as the face area; and then the face area can be regarded as the surrounding preset area (such as , the preset size area around the face area) is determined as the target area.

In step S103, in response to detecting that the target object in the target area satisfies the processing condition, the target object is processed.

In this embodiment, after determining the face area and the target area in the target image, it can be detected whether there is a target object (eg, the user's hand, or cutlery such as chopsticks, knives, and forks) in the target area, and then When there is a target object, it can be further detected whether the target object satisfies the processing conditions; on this basis, when it is determined that the target object satisfies the processing conditions, the target object is processed to obtain the processed target object.

In one embodiment, the above-mentioned target object satisfies the processing conditions, which may include at least one of the following:

(1) The position of the target object in the target image satisfies the set position conditions, such as being in the central area of the image, or in a preset area such as in front of the face or on both sides of the chin;

(2) The ratio of the target object in the target image satisfies the set ratio condition, for example, the ratio of the target object to the target image is greater than or equal to the set ratio threshold.

For example, after determining the face area in the target image, beautification processing may be performed on the face area in the target image based on a preset beauty method. The preset beautifying method may be set based on actual needs, for example, it is set to perform treatments such as face-lifting, whitening, acne removal, eye enlargement, skin resurfacing, etc., which is not limited in this embodiment. On the other hand, when the face area in the target image is determined, and the above-mentioned target area is determined based on the face area, it can be detected whether the target object in the target area satisfies the processing condition, and then when it is determined that the condition is satisfied, the The target object in the target image is processed. Taking the target object as an elongated object such as chopsticks as an example, when it is detected that the target object meets the processing conditions, for example, the chopsticks are located in a preset area such as the front of the face or the sides of the chin in the target image, and the chopsticks are in the target image. If the ratio in the target image is greater than the set ratio threshold (for example, 10%), the chopsticks that are bent in the current target image can be processed according to the normal image of the object (for example, a slender strip), so that the processed chopsticks The shape of the face is restored to its original shape, that is, to the slender strip that it appeared before the beautification process was performed on the face.

In another embodiment, for the above-mentioned manner of processing the target object, reference may be made to the embodiment shown in FIG. 2 below, which will not be described in detail here.

In step S104, a processed target image is determined based on the processed face region and the processed target object.

In this embodiment, after processing the target object in response to detecting that the target object in the target area meets the processing conditions, the processed target may be determined based on the processed face area and the processed target object image.

For example, after the target object in the target area is processed, the processed face area and the processed target object can be replaced on the basis of the original target image to obtain the processed target image.

In another embodiment, for the above-mentioned manner of processing the target object, reference may be made to the embodiment shown in FIG. 2 below, which will not be described in detail here.

As can be seen from the above description, the method of this embodiment obtains the target image to be processed, determines the face area and the target area in the target image, and then responds to detecting that the target object in the target area satisfies the processing conditions, Processing the target object, and then determining the processed target image based on the processed face region and the processed target object, so as to avoid the problem that the target region is distorted due to the processing of the face region. The image is distorted, which in turn can improve the processing quality of the image.

FIG. 2 is a flow chart showing how to process the target object according to an exemplary embodiment; this embodiment, on the basis of the above-mentioned embodiment, takes how to process the target object as an example to illustrate. The aforementioned target object may include a hand. On this basis, as shown in FIG. 2 , the processing of the target object in the above step S103 may include the following steps S201-S203:

In step S201, the characteristic information of the hand is determined.

In one embodiment, the above-mentioned feature information may include target ratios of palms and fingers.

In step S202, a sample image matching the hand is searched in a preset hand image library based on the feature information.

For example, if the above-mentioned feature information includes the target ratio of palm and fingers, such as 25%, the ratio of palm and fingers in each sample image in the preset hand image library can be determined, and then the ratio with the target ratio that is the most suitable can be selected. A similar sample image. Wherein, a plurality of sample images that meet aesthetic requirements may be preset in the above-mentioned hand image library, which is not limited in this embodiment.

In step S203, the hand is processed based on the sample image.

In this embodiment, after searching for a sample image matching the hand in a preset hand image library based on the feature information, the hand may be processed based on the sample image.

For example, in the case where the feature information includes the target ratio of the palm and the fingers, the target ratio of the palm and the fingers in the hand can be adjusted based on the ratio of the palm and the fingers in the sample image, for example, the target ratio in the target image can be adjusted. The target ratio of the palm and fingers is the same as the ratio of the palm and fingers in the sample image, and the shape of the hand can be orthodontic, adjusted and beautified, making the hand more beautiful and meeting the set aesthetic needs.

For another example, FIG. 3 is a flowchart showing how to process the target object based on the sample image according to an exemplary embodiment. As shown in FIG. 3, the above step 303 may include the following steps S301-S302:

In step S301, a first image parameter of the face region and a second image parameter of the sample image are acquired.

Wherein, the first image parameter and the second image parameter include at least one of color and texture. For example, the colors in the above image parameters may correspond to the skin tone of the human body (eg, white, black, yellow, or bright white, dull, etc.), and the textures in the image parameters may correspond to the skin texture of the human body (eg, rough or fine, etc.).

In step S302, the image parameters of the hand are processed based on the first image parameters and the second image parameters.

In this embodiment, after acquiring the first image parameter of the face area and the second image parameter of the sample image, the color and/or texture of the face area in the target image and the hand in the sample image may be The hand in the current image to be processed is processed according to the color and/or texture of the part, so as to make the hand in the current image to be processed more beautiful.

It can be seen from the above description that in this embodiment, the characteristic information of the hand is determined, a sample image matching the hand is searched in a preset hand image library based on the characteristic information, and a pair of sample images matching the hand is based on the sample image. The hand processing can achieve the acquisition of a matching sample image in the preset hand image library based on the feature information of the hand in the target area, and then the hand in the target area can be beautified based on the sample image, which can improve the performance of the hand. The processing quality of the target object in the target area other than the face area in the target image can improve the processing quality of the image.

FIG. 4 is a flowchart showing how to determine a processed target image based on a processed face region and a processed target object according to an exemplary embodiment; this embodiment is based on the above The facial region and the processed target object are determined as an example to illustrate the processed target image. As shown in FIG. 4 , the determination of the processed target image based on the processed face region and the processed target object in the above step S104 may include the following steps S401-S402:

In step S401, a second positional relationship between the processed face region and the processed target object is determined based on the first relationship between the face region in the target image and the target object.

In this embodiment, after processing the target object in response to detecting that the target object in the target area meets the processing conditions, the first relationship between the face area in the target image and the target object can be determined , and then a second positional relationship between the processed face region and the processed target object may be determined based on the first relationship.

In step S402, the positional relationship between the first layer corresponding to the processed face region and the second layer corresponding to the processed target object is adjusted based on the second positional relationship.

In this embodiment, based on the first relationship between the face region in the target image and the target object, the relationship between the processed face region and the processed target object may be determined based on the first relationship. The second positional relationship between the two, and then the positional relationship between the first layer corresponding to the processed face region and the second layer corresponding to the processed target object can be adjusted based on the second positional relationship. , so that the positional relationship between the processed target object and the face area remains unchanged.

In step S403, in response to detecting that there is a blank area between the adjusted first layer and the second layer, use a preset image filling method to fill the blank area to obtain a processed image target image.

In this embodiment, after adjusting the positional relationship between the first layer corresponding to the processed face region and the second layer corresponding to the processed target object based on the second positional relationship, the It can be detected whether there is a blank area between the adjusted first layer and the second layer, and then when it is detected that there is a blank area between the first layer and the second layer, the preset The blank area is filled in the image filling method to obtain the processed target image.

Wherein, the above-mentioned preset image filling method may be set based on actual business needs. For example, it is set as the filling method based on content recognition in the related art, which is not limited in this embodiment.

It can be seen from the above description that in this embodiment, the second relationship between the processed face region and the processed target object is determined based on the first relationship between the face region in the target image and the target object. positional relationship, and adjust the positional relationship between the first layer corresponding to the processed face region and the second layer corresponding to the processed target object based on the second positional relationship, so that target-based The relationship between the face area and the target area in the image accurately determines the positional relationship between the first layer corresponding to the processed face area and the second layer corresponding to the processed target object, so as to ensure the face in the image. The positional relationship with the target area remains unchanged, and in response to detecting that there is a blank area between the adjusted first layer and the second layer, a preset image filling method is used to fill the blank area. Filling the area can avoid blank areas due to image processing and improve the processing quality of the image.

FIG. 5 is a block diagram of an image processing apparatus according to an exemplary embodiment; the apparatus in this embodiment can be applied to a terminal device with an image processing function (such as a smart phone, a tablet computer, a notebook computer, or a wearable device, etc.) ). As shown in FIG. 5 , the device includes: a target image acquisition module 110, a target area determination module 120, a target object processing module 130, and a processed image determination module 140, wherein:

a target image acquisition module 110, configured to acquire a target image to be processed;

a target area determination module 120, configured to determine a target area in the target image, where the target area includes a face area and a peripheral preset area;

a target object processing module 130, configured to process the target object in response to detecting that the target object in the target area meets the processing condition;

The processed image determination module 140 is configured to determine the processed target image based on the processed face region and the processed target object.

It can be seen from the above description that the device of this embodiment obtains the target image to be processed, determines the face area and the target area in the target image, and then responds to detecting that the target object in the target area satisfies the processing conditions, Processing the target object, and then determining the processed target image based on the processed face area and the processed target object, so as to avoid the problem that the target area is distorted due to the processing of the face area. The image is distorted, which in turn can improve the processing quality of the image.

FIG. 6 is a block diagram of an image processing apparatus according to another exemplary embodiment; the apparatus in this embodiment can be applied to a terminal device with an image processing function (eg, a smart phone, a tablet computer, a notebook computer, or a wearable device) Wait). Among them: the target image acquisition module 210, the target area determination module 220, the target object processing module 230 and the processed image determination module 240 are the same as the target image acquisition module 110, the target area determination module 120, the target object processing module in the embodiment shown in FIG. The functions of the module 130 and the processing image determination module 140 are the same, and will not be repeated here.

In this embodiment, the above-mentioned target object meets the processing conditions, and may include at least one of the following:

The position of the target object in the target image satisfies the set position condition;

The target area is distorted after processing the face area;

The scale of the target object in the target image satisfies the set scale condition.

As shown in FIG. 6 , the above-mentioned target object may include a hand; on this basis, the target object processing module 230 may include:

a feature information determination unit 231, configured to determine the feature information of the hand;

a sample image search unit 232, configured to search for a sample image matching the hand in a preset hand image library based on the feature information;

The target object processing unit 233 is configured to process the hand based on the sample image.

In one embodiment, the above-mentioned characteristic information may include the target ratio of palm and fingers;

On this basis, the sample image search unit 232 may also be configured to search the preset hand image library for a sample image whose proportions of the palm and fingers are the closest to the target proportion.

In an embodiment, the target object processing unit 233 may be further configured to adjust the target ratio of the palm and the fingers in the hand based on the ratio of the palm and the fingers in the sample image.

In one embodiment, the target object processing unit 233 may also be used for:

acquiring the first image parameter of the face region and the second image parameter of the sample image, the first image parameter and the second image parameter including at least one of color and texture;

The image parameters of the hand are processed based on the first image parameters and the second image parameters.

In one embodiment, the above-mentioned processing image determination module 240 may include:

A position relationship determining unit 241, configured to determine a second position between the processed face region and the processed target object based on the first relationship between the face region in the target image and the target object relation;

The processed image determination unit 242 is configured to adjust the positional relationship between the first layer corresponding to the processed face region and the second layer corresponding to the processed target object based on the second positional relationship, Get the processed target image.

In one embodiment, the processing image determination module 240 may further include:

The blank area filling unit 243 is configured to, in response to detecting that there is a blank area between the adjusted first layer and the second layer, fill the blank area with a preset image filling method.

Regarding the apparatus in the above-mentioned embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be described in detail here.

Fig. 7 is a block diagram of an electronic device according to an exemplary embodiment. For example, apparatus 900 may be a mobile phone, computer, digital broadcast terminal, messaging device, game console, tablet device, medical device, fitness device, personal digital assistant, and the like. In this embodiment, the electronic device may include a normally-on image acquisition device for acquiring image information.

7, the apparatus 900 may include one or more of the following components: a processing component 902, a memory 904, a power supply component 906, a multimedia component 908, an audio component 910, an input/output (I/O) interface 912, a sensor component 914, And the communication component 916 .

The processing component 902 generally controls the overall operation of the apparatus 900, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing element 902 may include one or more processors 920 to execute instructions to perform all or part of the steps of the methods described above. Additionally, processing component 902 may include one or more modules to facilitate interaction between processing component 902 and other components. For example, processing component 902 may include a multimedia module to facilitate interaction between multimedia component 908 and processing component 902.

Memory 904 is configured to store various types of data to support operation at device 900 . Examples of such data include instructions for any application or method operating on device 900, contact data, phonebook data, messages, pictures, videos, and the like. Memory 904 may be implemented by any type of volatile or non-volatile storage device or combination thereof, such as static random access memory (SRAM), electrically erasable programmable read only memory (EEPROM), erasable Programmable Read Only Memory (EPROM), Programmable Read Only Memory (PROM), Read Only Memory (ROM), Magnetic Memory, Flash Memory, Magnetic or Optical Disk.

Power component 906 provides power to various components of device 900 . Power components 906 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power to device 900 .

Multimedia component 908 includes a screen that provides an output interface between the device 900 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touch, swipe, and gestures on the touch panel. The touch sensor may not only sense the boundaries of a touch or swipe action, but also detect the duration and pressure associated with the touch or swipe action. In some embodiments, the multimedia component 908 includes a front-facing camera and/or a rear-facing camera. When the apparatus 900 is in an operation mode, such as a shooting mode or a video mode, the front camera and/or the rear camera may receive external multimedia data. Each of the front and rear cameras can be a fixed optical lens system or have focal length and optical zoom capability.

Audio component 910 is configured to output and/or input audio signals. For example, audio component 910 includes a microphone (MIC) that is configured to receive external audio signals when device 900 is in operating modes, such as call mode, recording mode, and voice recognition mode. The received audio signal may be further stored in memory 904 or transmitted via communication component 916 . In some embodiments, audio component 910 also includes a speaker for outputting audio signals.

The I/O interface 912 provides an interface between the processing component 902 and a peripheral interface module, which may be a keyboard, a click wheel, a button, or the like. These buttons may include, but are not limited to: home button, volume buttons, start button, and lock button.

Sensor assembly 914 includes one or more sensors for providing status assessment of various aspects of device 900 . For example, the sensor assembly 914 can detect the open/closed state of the device 900, the relative positioning of components, such as the display and keypad of the device 900, and the sensor assembly 914 can also detect a change in the position of the device 900 or a component of the device 900 , the presence or absence of user contact with the device 900 , the orientation or acceleration/deceleration of the device 900 and the temperature change of the device 900 . Sensor assembly 914 may also include a proximity sensor configured to detect the presence of nearby objects in the absence of any physical contact. Sensor assembly 914 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 914 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

Communication component 916 is configured to facilitate wired or wireless communication between apparatus 900 and other devices. Device 900 may access wireless networks based on communication standards, such as WiFi, 2G or 3G, 4G or 5G, or a combination thereof. In one exemplary embodiment, the communication component 916 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 916 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

In an exemplary embodiment, apparatus 900 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable A gate array (FPGA), controller, microcontroller, microprocessor or other electronic component implementation is used to perform the above method.

In an exemplary embodiment, there is also provided a non-transitory computer-readable storage medium including instructions, such as a memory 904 including instructions, executable by the processor 920 of the apparatus 900 to perform the method described above. For example, the non-transitory computer-readable storage medium may be ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, and the like.

Other embodiments of the present disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common general knowledge or techniques in the technical field not disclosed by this disclosure . The specification and examples are to be regarded as exemplary only, with the true scope and spirit of the disclosure being indicated by the following claims.

It is to be understood that the present disclosure is not limited to the precise structures described above and illustrated in the accompanying drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims (18)

1. An image processing method, characterized in that the method comprises:

acquiring a target image to be processed;

determining a target area in the target image, wherein the target area comprises a face area and a peripheral preset area;

in response to detecting that a target object in the target area satisfies a processing condition, processing the target object;

and determining a processed target image based on the processed face area and the processed target object.

2. The method of claim 1, wherein the target object satisfies a processing condition comprising at least one of:

the position of the target object in the target image meets a set position condition;

the proportion of the target object in the target image meets a set proportion condition.

3. The method of claim 1, wherein the target object comprises a hand;

the processing the target object comprises:

determining characteristic information of the hand;

searching a sample image matched with the hand in a preset hand image library based on the characteristic information;

and processing the hand part based on the sample image to obtain a target object.

4. The method of claim 3, wherein the characteristic information includes a target ratio of palm and fingers;

the searching for the sample image matched with the hand in a preset hand image library based on the characteristic information comprises:

and searching a sample image with the palm and finger ratio closest to the target ratio in the preset hand image library.

5. The method of claim 4, wherein the processing the hand based on the sample image comprises:

adjusting a target ratio of the palm and fingers in the hand based on the ratio of the palm and fingers in the sample image.

6. The method of claim 3, wherein the processing the hand based on the sample image comprises:

acquiring a first image parameter of the face region and a second image parameter of the sample image, wherein the first image parameter and the second image parameter comprise at least one of color and texture;

processing image parameters of the hand based on the first image parameters and the second image parameters.

7. The method of claim 1, wherein determining a processed target image based on the processed face region and the processed target object comprises:

determining a second positional relationship between the processed face region and the processed target object based on a first relationship between the face region and the target object in the target image;

and adjusting the position relation between the first image layer corresponding to the processed face area and the second image layer corresponding to the processed target object based on the second position relation to obtain a processed target image.

8. The method of claim 7, further comprising:

and in response to the fact that a blank area exists between the adjusted first image layer and the adjusted second image layer, filling the blank area by adopting a preset image filling mode.

9. An image processing apparatus, characterized in that the apparatus comprises:

the target image acquisition module is used for acquiring a target image to be processed;

a target area determination module, configured to determine a target area in the target image, where the target area includes a face area and a peripheral preset area;

the target object processing module is used for processing the target object in response to the fact that the target object in the target area meets the processing condition;

and the processed image determining module is used for determining a processed target image based on the processed face area and the processed target object.

10. The apparatus of claim 9, wherein the target object satisfies a processing condition comprising at least one of:

the position of the target object in the target image meets a set position condition;

the proportion of the target object in the target image meets a set proportion condition.

11. The device of claim 10, wherein the target area comprises a hand;

the target object processing module comprising:

a feature information determination unit configured to determine feature information of the hand;

the sample image searching unit is used for searching a sample image matched with the hand in a preset hand image library based on the characteristic information;

a target object processing unit for processing the hand based on the sample image.

12. The apparatus of claim 11, wherein the characteristic information comprises a target ratio of palm and fingers;

the sample image searching unit is further used for searching a sample image with the palm and finger ratio closest to the target ratio in the preset hand image library.

13. The apparatus of claim 12, wherein the target object processing unit is further configured to adjust the target palm and finger ratio in the hand based on the palm and finger ratio in the sample image.

14. The apparatus of claim 11, wherein the target object processing unit is further configured to:

acquiring a first image parameter of the face region and a second image parameter of the sample image, wherein the first image parameter and the second image parameter comprise at least one of color and texture;

processing image parameters of the hand based on the first image parameters and the second image parameters.

15. The apparatus of claim 9, wherein the process image determination module comprises:

a position relation determining unit configured to determine a second position relation between the processed face region and the processed target object based on a first relation between the face region and the target object in the target image;

and the processed image determining unit is used for adjusting the position relationship between the first image layer corresponding to the processed face area and the second image layer corresponding to the processed target object based on the second position relationship to obtain a processed target image.

16. The apparatus of claim 15, wherein the process image determination module further comprises:

and the blank area filling unit is used for responding to the fact that a blank area exists between the first image layer and the second image layer after the adjustment, and filling the blank area by adopting a preset image filling mode.

17. An electronic device, characterized in that the device comprises:

a processor and a memory for storing processor-executable instructions;

wherein the processor is configured to:

acquiring a target image to be processed;

determining a face region and a target region in the target image, wherein the target region comprises the face region and a peripheral preset region;

in response to detecting that a target object in the target area satisfies a processing condition, processing the target object;

and determining a processed target image based on the processed face area and the processed target object.

18. A computer-readable storage medium on which a computer program is stored, the program, when executed by a processor, implementing:

acquiring a target image to be processed;

determining a face region and a target region in the target image, wherein the target region comprises the face region and a peripheral preset region;

in response to detecting that a target object in the target area satisfies a processing condition, processing the target object;

and determining a processed target image based on the processed face area and the processed target object.

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