CN112819714A - Target object exposure method, device, storage medium and equipment - Google Patents

Target object exposure method, device, storage medium and equipment Download PDF

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Publication number
CN112819714A
CN112819714A CN202110127188.6A CN202110127188A CN112819714A CN 112819714 A CN112819714 A CN 112819714A CN 202110127188 A CN202110127188 A CN 202110127188A CN 112819714 A CN112819714 A CN 112819714A
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image
target object
brightness
identified
recognized
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吴强
彭恩厚
李佳
张振宇
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Shenzhen Sensetime Technology Co Ltd
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Shenzhen Sensetime Technology Co Ltd
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Priority to CN202110127188.6A priority Critical patent/CN112819714A/en
Publication of CN112819714A publication Critical patent/CN112819714A/en
Priority to PCT/CN2021/110240 priority patent/WO2022160638A1/en
Priority to TW110134452A priority patent/TW202230277A/en
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration
    • G06T5/90Dynamic range modification of images or parts thereof
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/10Image acquisition
    • G06V10/12Details of acquisition arrangements; Constructional details thereof
    • G06V10/14Optical characteristics of the device performing the acquisition or on the illumination arrangements
    • G06V10/141Control of illumination
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16Human faces, e.g. facial parts, sketches or expressions
    • G06V40/161Detection; Localisation; Normalisation
    • G06V40/166Detection; Localisation; Normalisation using acquisition arrangements
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16Human faces, e.g. facial parts, sketches or expressions
    • G06V40/172Classification, e.g. identification
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10141Special mode during image acquisition
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20081Training; Learning
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20084Artificial neural networks [ANN]
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30196Human being; Person
    • G06T2207/30201Face
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00Indexing scheme relating to image or video recognition or understanding
    • G06V2201/07Target detection

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Multimedia (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • Human Computer Interaction (AREA)
  • Studio Devices (AREA)
  • Exposure Control For Cameras (AREA)

Abstract

In the embodiment of the disclosure, an exposure image is obtained by acquiring an image to be exposed, performing brightness identification on the image to be exposed, determining a brightness abnormal area on the image to be exposed, performing brightness adjustment on the brightness abnormal area to obtain the image to be identified, performing target object identification on the image to be identified and performing exposure processing on a target object under the condition that the target object is determined. The method and the device can improve the image originally obtained in an extreme environment through brightness adjustment, avoid exposure abnormity of the target object in the extreme environment, and lay a good foundation for image application after subsequent exposure.

Description

Target object exposure method, device, storage medium and equipment
Technical Field
The present disclosure relates to the field of computer vision technologies, and in particular, to a method, an apparatus, a storage medium, and a device for exposing a target object.
Background
At present, in the field of image recognition and artificial intelligence, the target recognition technology is correspondingly applied in various industries, for example, in the field of identity information recognition, the face recognition technology occupies an important position.
Optimization of images containing targets is a rigid demand in the market due to the importance of target identification, so that more and more manufacturers are also making target-based automatic exposure strategies. However, in some extreme environments, the target recognition module cannot detect the target that should be detected, so that some scenes cannot be automatically exposed based on the target, and therefore, the adverse effect that subsequent applications based on the exposed target cannot be performed is caused.
Disclosure of Invention
The present disclosure proposes a target object exposure solution.
The present disclosure provides a target object exposure method, which includes: acquiring an image to be exposed; carrying out brightness identification on an image to be exposed, and determining a brightness abnormal area on the image to be exposed; adjusting the brightness of the abnormal brightness area to obtain an image to be identified; and carrying out target object identification on the image to be identified and carrying out exposure processing on the target object under the condition of determining the target object to obtain an exposure image.
In some possible embodiments, performing target object recognition on an image to be recognized, and performing exposure processing on a target object to obtain an exposure image when the target object is determined includes: carrying out preset object identification on an image to be identified, wherein the preset object comprises a target object; under the condition that the preset object is identified, determining a region to be identified where the preset object is located; carrying out target object identification on the area to be identified; and in the case of identifying the target object, carrying out exposure processing on the target object to obtain an exposure image.
In some possible embodiments, after identifying the target object in the area to be identified, the method further includes:
under the condition that the target object is not identified, brightness adjustment corresponding to a plurality of brightnesses is carried out on the image to be identified, and a plurality of adjusted images to be identified are obtained; carrying out target object identification on the to-be-identified areas on the adjusted to-be-identified images; and under the condition that the target object is identified, carrying out exposure processing on the target object on the adjusted image to be identified with the target object to obtain an exposure image.
In some possible embodiments, after identifying the target object in the area to be identified, the method further includes: determining the brightness of the image to be recognized under the condition that the target object is not recognized; when the brightness is larger than the first brightness, dimming the image to be recognized according to the first brightness interval value to obtain a dimmed image to be recognized; carrying out target object identification on the to-be-identified area on the dimmed to-be-identified image; and under the condition that the target object is not identified, dimming the dimmed image to be identified according to the first brightness interval value to obtain the current dimmed image to be identified, identifying the target object in the region to be identified on the current dimmed image to be identified until the target object is identified, and exposing the target object on the dimmed image to be identified to obtain an exposed image.
In some possible embodiments, after identifying the target object in the area to be identified, the method further includes:
determining the brightness of the image to be recognized under the condition that the target object is not recognized; when the brightness is smaller than the second brightness, the image to be recognized is brightened according to the second brightness interval numerical value to obtain a brightened image to be recognized; carrying out target object identification on the area to be identified on the brightened image to be identified; and under the condition that the target object is not identified, brightening the brightened image to be identified according to the second brightness interval numerical value to obtain a current brightened image to be identified, identifying the target object in the area to be identified on the current brightened image to be identified until the target object is identified, and exposing the target object on the brightened image to be identified to obtain an exposed image.
In some possible embodiments, performing target object recognition on an image to be recognized, and performing exposure processing on a target object to obtain an exposure image when the target object is determined includes: carrying out preset object recognition on an image to be recognized; under the condition that the preset object is not identified, brightness adjustment corresponding to a plurality of brightnesses is carried out on the image to be identified, and a plurality of adjusted images to be identified are obtained; carrying out target object identification on a plurality of adjusted images to be identified; and under the condition that the target object is identified, carrying out exposure processing on the target object on the adjusted image to be identified with the target object to obtain an exposure image.
In some possible embodiments, the target object comprises a human face; the preset object comprises a human shape; the method for recognizing the preset object of the image to be recognized comprises the following steps: carrying out human shape recognition on the image to be recognized through a human shape recognition network;
the method for identifying the target object in the area to be identified comprises the following steps: and carrying out face recognition on the area to be recognized through a face recognition network.
In some possible embodiments, the luminance abnormal region includes a first luminance abnormal region;
adjusting the brightness of the abnormal brightness area to obtain an image to be identified, comprising: adjusting the brightness of the first brightness abnormal area based on the first brightness adjustment parameter to obtain an image to be identified; the brightness of the first brightness abnormal area in the image to be identified is lower than that of the first brightness abnormal area on the image to be exposed.
In some possible embodiments, the luminance abnormal region includes a second luminance abnormal region;
adjusting the brightness of the abnormal brightness area to obtain an image to be identified, comprising: adjusting the brightness of the second brightness abnormal area based on the second brightness adjustment parameter to obtain an image to be identified; and the brightness of the second brightness abnormal area in the image to be identified is higher than that of the second brightness abnormal area on the image to be exposed.
In some possible embodiments, after acquiring the image to be exposed, the method further includes: performing brightness identification on an image to be exposed, and determining a brightness non-abnormal area on the image to be exposed; and carrying out target object identification on the brightness non-abnormal area, and carrying out exposure processing on the target object to obtain an exposure image under the condition of determining the target object.
The present disclosure provides a target object exposure apparatus including:
the image acquisition module is used for acquiring an image to be exposed; the area determining module is used for carrying out brightness identification on the image to be exposed and determining a brightness abnormal area on the image to be exposed; the brightness adjusting module is used for adjusting the brightness of the abnormal brightness area to obtain an image to be identified; and the image exposure module is used for carrying out exposure processing on the target object to obtain an exposure image under the conditions that the target object is identified and determined for the image to be identified.
In some possible embodiments, the image exposure module comprises an identification module, an identification area determination module, and a processing module;
the identification module is used for identifying a preset object of an image to be identified, wherein the preset object comprises a target object; the identification area determining module is used for determining an area to be identified where the preset object is located under the condition that the preset object is identified; the identification module is used for identifying a target object in an area to be identified; and the processing module is used for carrying out exposure processing on the target object under the condition that the target object is identified to obtain an exposure image.
In some possible embodiments, the image exposure module further comprises an adjustment module,
the adjusting module is used for performing brightness adjustment corresponding to a plurality of brightnesses on the image to be recognized under the condition that the target object is not recognized to obtain a plurality of adjusted images to be recognized; the identification module is used for identifying the target object in the areas to be identified on the adjusted images to be identified; the processing module is used for carrying out exposure processing on the target object on the adjusted image to be recognized with the target object under the condition that the target object is recognized, so as to obtain an exposure image.
In some possible embodiments, the image exposure module further comprises a brightness determination module,
the brightness determining module is used for determining the brightness of the image to be recognized under the condition that the target object is not recognized; the brightness adjusting module is used for dimming the image to be recognized according to a first brightness interval value under the condition that the brightness is larger than a first brightness, so as to obtain a dimmed image to be recognized; the identification module is used for identifying the target object in the area to be identified on the dimmed image to be identified; and the image exposure module is used for dimming the dimmed image to be recognized according to the first brightness interval value under the condition that the target object is not recognized to obtain the current dimmed image to be recognized, recognizing the target object in the region to be recognized on the current dimmed image to be recognized until the target object is recognized, and exposing the target object on the dimmed image to be recognized to obtain an exposed image.
In some possible embodiments, the image exposure module further comprises a brightness determination module,
the brightness determining module is used for determining the brightness of the image to be recognized under the condition that the target object is not recognized; the brightness adjusting module is used for adjusting the brightness of the image to be recognized according to a second brightness interval value under the condition that the brightness is smaller than a second brightness, so as to obtain an adjusted and bright image to be recognized; the identification module is used for identifying the target object in the area to be identified on the brightened image to be identified; and the image exposure module is used for brightening the brightened image to be recognized according to the second brightness interval numerical value under the condition that the target object is not recognized to obtain a current brightened image to be recognized, recognizing the target object in the area to be recognized on the current brightened image to be recognized until the target object is recognized, and exposing the target object on the brightened image to be recognized to obtain an exposed image.
In some of the possible embodiments, the first and second,
the identification module is used for carrying out preset object identification on the image to be identified; the brightness adjusting module is used for adjusting the brightness of the image to be recognized corresponding to a plurality of brightnesses under the condition that the preset object is not recognized, so that a plurality of adjusted images to be recognized are obtained; the identification module is used for carrying out the target object identification on the plurality of adjusted images to be identified; and the image exposure module is used for carrying out exposure processing on the target object on the adjusted image to be identified with the target object under the condition that the target object is identified to obtain an exposure image.
In some possible embodiments, the target object comprises a human face; the preset object comprises a human shape;
the identification module is used for identifying the human shape of the image to be identified through a human shape identification network; and the system is also used for carrying out face recognition on the area to be recognized through a face recognition network.
In some possible embodiments, the luminance abnormal region includes a first luminance abnormal region;
the brightness adjusting module is used for adjusting the brightness of the first brightness abnormal area based on the first brightness adjusting parameter to obtain an image to be identified; the brightness of the first brightness abnormal area in the image to be identified is lower than that of the first brightness abnormal area on the image to be exposed.
In some possible embodiments, the luminance abnormal region includes a second luminance abnormal region;
the brightness adjusting module is used for adjusting the brightness of the second brightness abnormal area based on the second brightness adjusting parameter to obtain an image to be identified; and the brightness of the second brightness abnormal area in the image to be identified is higher than that of the second brightness abnormal area on the image to be exposed.
In some possible embodiments, after acquiring the image to be exposed, the method further includes: the area determining module is used for performing brightness identification on the image to be exposed and determining a brightness non-abnormal area on the image to be exposed; the image exposure module is used for identifying a target object in the brightness non-abnormal area and carrying out exposure processing on the target object under the condition of determining the target object to obtain an exposure image.
The present disclosure provides an electronic device comprising at least one processor, and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the at least one processor implementing a method of exposing a target object as claimed in any one of the first aspect by executing the instructions stored by the memory.
The present disclosure provides a computer-readable storage medium having at least one instruction or at least one program stored therein, the at least one instruction or the at least one program being loaded and executed by a processor to implement a target object exposure method of any one of the first aspect.
The present disclosure provides a computer program product containing instructions which, when run on a computer, cause the computer to perform any one of the target object exposure methods of the first aspect of the present disclosure.
In the embodiment of the disclosure, an image to be exposed is obtained, brightness identification is performed on the image to be exposed, a brightness abnormal region on the image to be exposed is determined, brightness adjustment is performed on the brightness abnormal region to obtain the image to be identified, and exposure processing is performed on a target object under the conditions that target object identification is performed on the image to be identified and the target object is determined to obtain an exposure image. The method and the device can improve the image originally obtained in an extreme environment through brightness adjustment, avoid exposure abnormity of the target object in the extreme environment, and lay a good foundation for image application after subsequent exposure.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.
Drawings
In order to more clearly illustrate the embodiments of the present specification or the technical solutions and advantages of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present specification, and other drawings can be obtained by those skilled in the art without inventive efforts.
FIG. 1 shows a schematic diagram of an application environment in accordance with an embodiment of the present disclosure;
FIG. 2 illustrates a flow chart of a method of exposing a target object in accordance with an embodiment of the present disclosure;
FIG. 3 illustrates a flow chart of a method of exposing a target object in accordance with an embodiment of the present disclosure;
FIG. 4 illustrates a flow chart of a method of exposing a target object in accordance with an embodiment of the present disclosure;
FIG. 5 illustrates a flow chart of a method of exposing a target object in accordance with an embodiment of the present disclosure;
FIG. 6 shows a block diagram of a target object exposure apparatus according to an embodiment of the present disclosure;
FIG. 7 shows a block diagram of an electronic device in accordance with an embodiment of the disclosure;
fig. 8 shows a block diagram of another electronic device in accordance with an embodiment of the disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments in the present description, belong to the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, C, and may mean including any one or more elements selected from the group consisting of A, B and C.
Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.
Referring to fig. 1, fig. 1 is a schematic diagram illustrating an application environment according to an embodiment of the present disclosure, and as shown in fig. 1, includes an image providing apparatus 01 and an image processing apparatus 02. Alternatively, the image providing apparatus 01 and the image processing apparatus 02 may be connected to each other through a wireless link or a wired link.
In an alternative embodiment, the image processing device 02 acquires an image to be exposed from the image providing device 01, performs brightness recognition on the image to be exposed, and determines a brightness abnormal region on the image to be exposed. The image processing device 02 performs brightness adjustment on the brightness abnormal region to obtain an image to be recognized, performs target object recognition on the image to be recognized, and performs exposure processing on the target object to obtain an exposure image under the condition that the target object is determined.
In another alternative embodiment, the image processing device 02 of FIG. 1 may be an image processing system or image processing platform. The image processing system or the image processing platform may include a plurality of servers or processing terminals therein. For example, assume that an image processing system includes 3 servers, namely, a first server, a second server, and a third server, where the first server may obtain an image to be exposed from the image providing device 01, perform brightness identification on the image to be exposed, determine a brightness abnormal region on the image to be exposed, transmit the image to be exposed with the marked brightness abnormal region to the second server, and the second server performs brightness adjustment on the brightness abnormal region to obtain an image to be identified, and transmit the image to be identified after the brightness adjustment to the third server. And the third server identifies the target object of the image to be identified, and exposes the target object to obtain an exposed image under the condition of determining the target object. Therefore, the image to be exposed is subjected to brightness adjustment, so that the image is in a normal brightness, the image processing equipment can better detect the target object, and subsequent exposure of the target object is facilitated.
The technical scheme provided by the embodiment of the disclosure can be applied to the expansion of application scenes such as target object exposure, target recognition and the like of images or videos, and the embodiment of the disclosure does not limit the application scenes.
The image processing device 02 provided by the embodiment of the present disclosure may be a terminal device, a server, or other types of electronic devices, wherein the terminal device may be a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a Personal Digital Assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, or the like. In some possible implementations, the target object exposure method may be implemented by a processor calling computer readable instructions stored in a memory. The target object exposure method according to the embodiment of the present disclosure will be described below by taking an electronic apparatus as an execution subject. The target object exposure method may be implemented by way of a processor calling computer readable instructions stored in a memory.
The image providing device 01 provided by the embodiment of the present disclosure may be a terminal device, a server, or other types of electronic devices, wherein the terminal device may include, but is not limited to, a video camera, a video recorder, and the like.
Fig. 2 shows a flow chart of a target object exposure method according to an embodiment of the present disclosure, as shown in fig. 1, the method comprising:
s21: and acquiring an image to be exposed.
In some alternative embodiments, the image processing device may obtain the reference picture through the image providing device, or the image providing device may obtain the image to be exposed from another device and provide the image to the image processing device, for example, the image providing device may obtain the image providing device from an image capturing device, a monitoring device, or the like. In some implementations, the image-rendering device may be a frame in a video. Optionally, each frame in the video may be an image to be exposed in the embodiment of the present disclosure, or some frames in the video may be referred to as an image to be exposed in the embodiment of the present disclosure, that is, after the image providing device acquires the video, the image providing device may sample the video, determine the image frame obtained by sampling as the image to be exposed, and transmit the image frame to the image processing device.
S22: and carrying out brightness identification on the image to be exposed, and determining a brightness abnormal area on the image to be exposed.
In the embodiment of the present disclosure, a variety of results can be obtained by identifying the image to be exposed, including that the image to be exposed is all a normal brightness region, or that the image to be exposed includes an abnormal brightness region and a normal brightness region, or that the image to be exposed is all an abnormal brightness region. The brightness abnormal region may include a backlight region, a weak light region, a strong light region or a frontlight region. The backlight area refers to the area of the image where objects are photographed completely against light, and the objects are not clearly seen or are dim. The low light area means that the image is dark although the object in the area is not photographed completely against the light. The smooth area means that objects in the area of the image are shot along with light, and the light is too strong and cannot be seen clearly. The highlight region means that objects in the image region are not photographed completely along with light, but the light is strong, so that the objects are not clearly seen.
S23: and adjusting the brightness of the abnormal brightness area to obtain an image to be identified.
In the embodiment of the disclosure, since the image to be exposed may be obtained in an abnormal environment, for example, photographed or recorded in an evening or an environment with dark illumination, the image to be exposed may present a phenomenon of backlight or weak light. For another example, the image to be exposed is photographed or recorded in the midday or in an environment with strong illumination, so that the image to be exposed may show a strong light or a direct light. These phenomena may cause adverse effects on the recognition in the process of recognizing the target object, and therefore, in an alternative embodiment, the brightness recognition may be performed on the image to be exposed, and the brightness abnormal region on the image to be exposed may be determined.
In one possible embodiment, the luminance abnormal region may include a first luminance abnormal region. In this case, in the above, performing brightness identification on the image to be exposed, and determining the abnormal brightness region on the image to be exposed may be expressed in that brightness adjustment is performed on the first abnormal brightness region based on the first brightness adjustment parameter, so as to obtain the image to be identified. The brightness of the first brightness abnormal area in the image to be identified is lower than that of the first brightness abnormal area on the image to be exposed.
Optionally, the first luminance abnormal region may be a front light region or a highlight region, where the luminance is brighter in both the front light region and the highlight region. In an alternative embodiment, the dimming parameter may include a predetermined first brightness, which is lower than the brightness before dimming, and the area with abnormal first brightness may be dimmed according to the predetermined first brightness no matter which image to be exposed identifies the area with abnormal first brightness. In another alternative embodiment, the dimming rule does not have a fixed first brightness, and as long as a first abnormal brightness region is identified in the picture to be exposed, the brightness to be adjusted is determined according to the brightness of the first abnormal brightness region, and the first abnormal brightness region is adjusted based on the adjusted brightness, wherein the adjusted brightness is lower than the brightness of the first abnormal brightness region.
In one possible embodiment, the luminance abnormal region may include a second luminance abnormal region. In this case, in the foregoing, performing brightness identification on the image to be exposed, and determining the abnormal brightness region on the image to be exposed may be expressed in that brightness adjustment is performed on the second abnormal brightness region based on the second brightness adjustment parameter, so as to obtain the image to be identified. And the brightness of the second brightness abnormal area in the image to be identified is higher than that of the second brightness abnormal area on the image to be exposed.
Alternatively, the second abnormal luminance area may be a backlight area or a low-light area, where the luminance is relatively dim. The second brightness adjustment parameter is a dimming parameter. In an alternative embodiment, the brightness-adjusting parameter may include a predetermined second brightness, and the predetermined second brightness is higher than the brightness before brightness adjustment, and no matter which image to be exposed has the second abnormal brightness region, the second abnormal brightness region may be adjusted according to the predetermined second brightness. In another alternative embodiment, the dimming rule does not have a fixed second brightness, and as long as a second abnormal brightness region is identified in the picture to be exposed, the adjusted brightness can be determined according to the brightness of the second abnormal brightness region, and the second abnormal brightness region is adjusted based on the adjusted brightness, wherein the adjusted brightness is higher than the brightness of the second abnormal brightness region.
In the embodiment, the area to be adjusted in brightness is determined by detecting the abnormal brightness area, and then the brightness of the area is adjusted according to the corresponding brightness adjustment parameter, so that a good basis is laid for the subsequent identification of the target object.
S24: and under the condition that the target object is identified and determined in the image to be identified, carrying out exposure processing on the target object to obtain an exposure image.
In one possible embodiment, the image processing device may directly perform target object recognition on the recognition image, and directly perform exposure processing on the target object to obtain an exposure image when it is determined that the target object exists in the image. The target object may be anything including, but not limited to, a pedestrian, a vehicle (car, truck, bicycle, etc.), an obstacle (trash can, tree, trash, traffic lights, etc.), an animal (dog, cat, etc.), even some part of an event, such as a human face, a license plate on a vehicle, etc.
In one possible embodiment, the image processing device may perform pre-recognition on the object including the target object, and in the case that the object including the target object is recognized, recognize the target object, so that the coarse recognition module for better recognizing the object including the target object in a larger area may be started first, and then the fine recognition module is started to recognize the target object after the coarse recognition module recognizes the object. The workload of the refined identification module can be reduced, and the calculation force of the refined identification module is reduced.
Fig. 3 shows a flow chart of a target object exposure method according to an embodiment of the present disclosure, as shown in fig. 3, the method comprising:
s301: carrying out preset object identification on an image to be identified, wherein the preset object comprises a target object; if the preset object is identified, go to step S302; otherwise, go to step S305.
In an alternative embodiment, the preset object includes a human shape, and the image processing device may perform human shape recognition on the image to be recognized by using a human shape recognition network built in the device.
Optionally, the human shape recognition network may include, but is not limited to, a deep learning network using a convolutional neural network, a cyclic neural network, or a recurrent neural network. Taking a convolutional neural network as an example, a large number of training data sets can be obtained, each training data set comprises a training image and a human figure marked on the training image, then, human figure recognition training is carried out on the convolutional neural network based on the large number of training data sets, and parameters of the convolutional neural network are adjusted in the training process until the human figure output by the convolutional neural network is matched with the human figure marked, so that a graph correlation recognition network is obtained.
S302: and under the condition that the preset object is identified, determining the area to be identified where the preset object is located.
S303: carrying out target object identification on the area to be identified; if the target object is identified, go to step S304; otherwise, go to step S305.
Based on the fact that the preset object is a human figure, in an alternative embodiment, the target object includes a human face, and the image processing device may perform face recognition on the region to be recognized by using a face recognition network built in the device.
Alternatively, the face recognition network may include, but is not limited to, a deep learning network using a convolutional neural network, a cyclic neural network, or a recurrent neural network. Taking a convolutional neural network as an example, a large number of training data sets can be obtained, each training data set comprises a human figure and a human face marked on the human figure, then, the convolutional neural network is subjected to face recognition training based on the large number of training data sets, and parameters of the convolutional neural network are adjusted in the training process until the human face output by the convolutional neural network is matched with the human face marked, so that the graph correlation recognition network is obtained.
In this embodiment, the training data in the training data set may be stored in a certain storage area, and the storage area may be a block chain. The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism and an encryption algorithm. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product services layer, and an application services layer.
S304: and in the case of identifying the target object, carrying out exposure processing on the target object to obtain an exposure image.
S305, ending the flow.
In an optional implementation manner, if the target object is not recognized when the target object is recognized in the region to be recognized in step S303, the brightness of the region to be recognized may not be adjusted to be more favorable for recognizing a human face only according to the first brightness adjustment parameter or the second brightness adjustment parameter.
Fig. 4 shows a flowchart of a target object exposure method according to an embodiment of the present disclosure, as shown in fig. 4, the method comprising:
s401: and under the condition that the target object is not identified, performing brightness adjustment corresponding to a plurality of brightnesses on the image to be identified to obtain a plurality of adjusted images to be identified.
In an optional embodiment, step S401 may be implemented on the premise that a preset object is recognized on an image to be recognized, and when a preset object is recognized, an area to be recognized where the preset object is located is determined, and then target object recognition may be performed on the area to be recognized.
S402: carrying out target object identification on the to-be-identified areas on the adjusted to-be-identified images; if the target object is identified in the multiple adjusted areas to be identified, go to step S403; otherwise, go to step S404.
Alternatively, if only one target object is identified in one of the adjusted to-be-identified regions, the process may go to step S403 to perform exposure processing on the target object in the adjusted to-be-identified image.
S403: and under the condition that the target object is identified, carrying out exposure processing on the target object on the adjusted image to be identified with the target object to obtain an exposure image.
S404: and ending the flow.
The above-mentioned embodiments of S401 to S404 illustrate a scheme of identifying a plurality of adjusted images to be identified after obtaining a plurality of adjusted images to be identified, however, in an actual operation process, brightness adjustment corresponding to a plurality of brightness is performed on the images to be identified at one time, obtaining a plurality of adjusted images to be identified may be a waste of hardware resources, and in order to reduce resource waste, the embodiment may be implemented by reducing the number of the adjusted images to be identified.
In an alternative embodiment, in the case that the target object is not recognized, the brightness of the image to be recognized may be determined, such as brightness a. When the brightness A is larger than the first brightness, dimming the image to be recognized according to a first brightness interval value (-1) to obtain a dimmed image to be recognized (the brightness is A-1), performing target object recognition on the dimmed area to be recognized on the dimmed image to be recognized, dimming the dimmed image to be recognized according to the first brightness interval value when the target object is not recognized to obtain a current dimmed image to be recognized (the brightness is A-2), performing target object recognition on the dimmed area to be recognized on the current image to be recognized, repeating … … until the target object is recognized, and performing exposure processing on the target object on the dimmed image to be recognized, wherein the dimmed image to be recognized is capable of recognizing the target object, so as to obtain an exposed image.
In another alternative embodiment, in the case that the target object is not recognized, the brightness of the image to be recognized may be determined, such as brightness B; and in the case that the brightness is smaller than the second brightness, brightening the image to be recognized according to the second brightness interval numerical value (+1) to obtain the image to be recognized after brightening (the image brightness is B + 1). And carrying out target object recognition on the to-be-recognized area on the brightened to-be-recognized image, brightening the brightened to-be-recognized image according to a second brightness interval numerical value under the condition that the target object is not recognized to obtain a current brightened to-be-recognized image (the brightness is B +2), carrying out target object recognition on the to-be-recognized area on the current brightened to-be-recognized image, repeating … … until the target object is recognized, and carrying out exposure treatment on the target object on the brightened to-be-recognized image capable of recognizing the target object to obtain an exposed image.
Fig. 5 shows a flowchart of a target object exposure method according to an embodiment of the present disclosure, as shown in fig. 5, the method comprising:
s501: and performing preset object identification on the image to be identified, and if the preset object is not identified, turning to the step S502.
S502: and carrying out brightness adjustment corresponding to a plurality of brightnesses on the image to be recognized to obtain a plurality of adjusted images to be recognized.
In the embodiment of the disclosure, if there is a case where the preset object is not recognized, it may be due to carelessness caused by the brightness, and therefore, the brightness may be directly adjusted to obtain a plurality of adjusted images to be recognized.
S503: performing target object identification on the plurality of adjusted images to be identified, and if the target object is identified, turning to the step S504; otherwise, the flow ends.
S504: and carrying out exposure processing on the target object on the adjusted image to be identified with the target object to obtain an exposure image.
Therefore, the algorithm pressure can be reduced, and the target object (such as a human face) can not be directly detected under the condition that the preset object (such as a human shape) is not detected.
In another alternative embodiment, the reason for not detecting the predetermined object (human figure) is not brightness, but may be that most of the human figure is blocked by the object, for example, a person hides under a big tree, but the human face is visible, when the human figure is recognized, the human figure is detected as the whole contour of the person, so that the result of not recognizing the human figure may be caused. In this case, if the preset object is not recognized, the target object may be directly recognized, and if the target object is recognized, the target object on the image to be recognized may be subjected to exposure processing to obtain an exposure image.
In an optional embodiment, after the image to be exposed is obtained, the image processing device performs brightness identification on the image to be exposed, may determine a brightness non-abnormal region on the image to be exposed, performs target object identification on the brightness non-abnormal region, and performs exposure processing on the target object to obtain an exposure image under the condition that the target object is determined.
Fig. 6 shows a block diagram of a target object exposure apparatus according to an embodiment of the present disclosure, which includes, as shown in fig. 6:
an image acquisition module 601, configured to acquire an image to be exposed;
the region determining module 602 is configured to perform brightness identification on an image to be exposed, and determine a brightness abnormal region on the image to be exposed;
the brightness adjusting module 603 is configured to perform brightness adjustment on the brightness abnormal region to obtain an image to be identified;
the image exposure module 604 is configured to perform exposure processing on a target object to obtain an exposure image when the target object is identified and determined in the image to be identified.
In some possible embodiments, the image exposure module comprises an identification module, an identification area determination module, and a processing module;
the identification module is used for identifying a preset object of an image to be identified, wherein the preset object comprises a target object; the identification area determining module is used for determining an area to be identified where the preset object is located under the condition that the preset object is identified; the identification module is used for identifying a target object in an area to be identified; and the processing module is used for carrying out exposure processing on the target object under the condition that the target object is identified to obtain an exposure image.
In some possible embodiments, the image exposure module further comprises an adjustment module,
the adjusting module is used for performing brightness adjustment corresponding to a plurality of brightnesses on the image to be recognized under the condition that the target object is not recognized to obtain a plurality of adjusted images to be recognized; the identification module is used for identifying the target object in the areas to be identified on the adjusted images to be identified; the processing module is used for carrying out exposure processing on the target object on the adjusted image to be recognized with the target object under the condition that the target object is recognized, so as to obtain an exposure image.
In some possible embodiments, the image exposure module further comprises a brightness determination module,
the brightness determining module is used for determining the brightness of the image to be recognized under the condition that the target object is not recognized; the brightness adjusting module is used for dimming the image to be recognized according to a first brightness interval value under the condition that the brightness is larger than a first brightness, so as to obtain a dimmed image to be recognized; the identification module is used for identifying the target object in the area to be identified on the dimmed image to be identified; and the image exposure module is used for dimming the dimmed image to be recognized according to the first brightness interval value under the condition that the target object is not recognized to obtain the current dimmed image to be recognized, recognizing the target object in the region to be recognized on the current dimmed image to be recognized until the target object is recognized, and exposing the target object on the dimmed image to be recognized to obtain an exposed image.
In some possible embodiments, the image exposure module further comprises a brightness determination module,
the brightness determining module is used for determining the brightness of the image to be recognized under the condition that the target object is not recognized; the brightness adjusting module is used for adjusting the brightness of the image to be recognized according to a second brightness interval value under the condition that the brightness is smaller than a second brightness, so as to obtain an adjusted and bright image to be recognized; the identification module is used for identifying the target object in the area to be identified on the brightened image to be identified; and the image exposure module is used for brightening the brightened image to be recognized according to the second brightness interval numerical value under the condition that the target object is not recognized to obtain a current brightened image to be recognized, recognizing the target object in the area to be recognized on the current brightened image to be recognized until the target object is recognized, and exposing the target object on the brightened image to be recognized to obtain an exposed image.
In some of the possible embodiments, the first and second,
the identification module is used for carrying out preset object identification on the image to be identified; the brightness adjusting module is used for adjusting the brightness of the image to be recognized corresponding to a plurality of brightnesses under the condition that the preset object is not recognized, so that a plurality of adjusted images to be recognized are obtained; the identification module is used for carrying out the target object identification on the plurality of adjusted images to be identified; and the image exposure module is used for carrying out exposure processing on the target object on the adjusted image to be identified with the target object under the condition that the target object is identified to obtain an exposure image.
In some possible embodiments, the target object comprises a human face; the preset object comprises a human shape;
the identification module is used for identifying the human shape of the image to be identified through a human shape identification network; and the system is also used for carrying out face recognition on the area to be recognized through a face recognition network.
In some possible embodiments, the luminance abnormal region includes a first luminance abnormal region;
the brightness adjusting module is used for adjusting the brightness of the first brightness abnormal area based on the first brightness adjusting parameter to obtain an image to be identified; the brightness of the first brightness abnormal area in the image to be identified is lower than that of the first brightness abnormal area on the image to be exposed.
In some possible embodiments, the luminance abnormal region includes a second luminance abnormal region;
the brightness adjusting module is used for adjusting the brightness of the second brightness abnormal area based on the second brightness adjusting parameter to obtain an image to be identified; and the brightness of the second brightness abnormal area in the image to be identified is higher than that of the second brightness abnormal area on the image to be exposed.
In some possible embodiments, after acquiring the image to be exposed, the method further includes: the area determining module is used for performing brightness identification on the image to be exposed and determining a brightness non-abnormal area on the image to be exposed; the image exposure module is used for identifying a target object in the brightness non-abnormal area and carrying out exposure processing on the target object under the condition of determining the target object to obtain an exposure image.
In some embodiments, functions of or modules included in the apparatus provided in the embodiments of the present disclosure may be used to execute the method described in the above method embodiments, and specific implementation thereof may refer to the description of the above method embodiments, and for brevity, will not be described again here.
The embodiment of the present disclosure also provides a computer-readable storage medium, in which at least one instruction or at least one program is stored, and the at least one instruction or the at least one program is loaded by a processor and when executed, implements the above method. The computer readable storage medium may be a non-volatile computer readable storage medium.
An embodiment of the present disclosure further provides an electronic device, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured as the above method.
The electronic device may be provided as a terminal, server, or other form of device.
Embodiments of the present disclosure provide a computer program product containing instructions which, when run on a computer, cause the computer to perform the target object exposure method of the present disclosure.
Fig. 7 shows a block diagram of an electronic device in accordance with an embodiment of the disclosure. For example, the electronic device 700 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, or the like terminal.
Referring to fig. 7, electronic device 700 may include one or more of the following components: a processing component 702, a memory 704, a power component 706, a multimedia component 708, an audio component 710, an input/output (I/O) interface 712, a sensor component 714, and a communication component 716.
The processing component 702 generally controls overall operation of the electronic device 700, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing components 702 may include one or more processors 720 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 702 may include one or more modules that facilitate interaction between the processing component 702 and other components. For example, the processing component 702 may include a multimedia module to facilitate interaction between the multimedia component 708 and the processing component 702.
The memory 704 is configured to store various types of data to support operations at the electronic device 700. Examples of such data include instructions for any application or method operating on the electronic device 700, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 704 may be implemented by any type or combination of volatile or non-volatile memory devices 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 disks.
The power supply component 706 provides power to the various components of the electronic device 700. The power components 706 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the electronic device 700.
The multimedia component 708 includes a screen that provides an output interface between the electronic device 700 and a 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 an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 708 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the electronic device 700 is in an operation mode, such as a photographing mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 710 is configured to output and/or input audio signals. For example, the audio component 710 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 700 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may further be stored in the memory 704 or transmitted via the communication component 716. In some embodiments, audio component 710 also includes a speaker for outputting audio signals.
The I/O interface 712 provides an interface between the processing component 702 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor assembly 714 includes one or more sensors for providing various aspects of status assessment for the electronic device 700. For example, the sensor assembly 714 may detect an open/closed state of the electronic device 700, the relative positioning of components, such as a display and keypad of the electronic device 700, the sensor assembly 714 may also detect a change in the position of the electronic device 700 or a component of the electronic device 700, the presence or absence of user contact with the electronic device 700, orientation or acceleration/deceleration of the electronic device 700, and a change in the temperature of the electronic device 700. The sensor assembly 714 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 714 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 714 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 716 is configured to facilitate wired or wireless communication between the electronic device 700 and other devices. The electronic device 700 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 716 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 716 further includes a Near Field Communication (NFC) module to facilitate short-range communications. 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, the electronic device 700 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 Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, a non-transitory computer readable storage medium, such as the memory 704 including computer program instructions executable by the processor 720 of the electronic device 700 to perform the above-described method, is also provided.
Fig. 8 shows a block diagram of another electronic device in accordance with an embodiment of the disclosure. For example, the electronic device 800 may be provided as a server. Referring to fig. 8, electronic device 800 includes a processing component 822, which further includes one or more processors, and memory resources, represented by memory 832, for storing instructions, such as applications, that are executable by processing component 822. The application programs stored in memory 832 may include one or more modules that each correspond to a set of instructions. Further, the processing component 822 is configured to execute instructions to perform the above-described methods.
The electronic device 800 may also include a power component 826 configured to perform power management of the electronic device 800, a wired or wireless network interface 850 configured to connect the electronic device 800 to a network, and an input/output (I/O) interface 858. The electronic device 700 may operate based on an operating system stored in memory 832, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, or the like.
In an exemplary embodiment, a non-transitory computer readable storage medium, such as the memory 832, is also provided that includes computer program instructions executable by the processing component 822 of the electronic device 800 to perform the above-described methods.
The present disclosure may be systems, methods, and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement various aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims (13)

1. A method of exposing a target object, the method comprising:
acquiring an image to be exposed;
performing brightness identification on the image to be exposed, and determining a brightness abnormal area on the image to be exposed;
adjusting the brightness of the abnormal brightness area to obtain an image to be identified;
and carrying out target object identification on the image to be identified, and carrying out exposure processing on the target object under the condition of determining the target object to obtain an exposure image.
2. The method according to claim 1, wherein the performing exposure processing on the target object to obtain an exposure image when the target object is determined and the target object is identified comprises:
carrying out preset object identification on the image to be identified, wherein the preset object comprises the target object;
under the condition that the preset object is identified, determining a region to be identified where the preset object is located;
carrying out the target object identification on the area to be identified;
and under the condition that the target object is identified, carrying out exposure processing on the target object to obtain an exposure image.
3. The method according to claim 2, wherein after the target object recognition is performed on the region to be recognized, the method further comprises:
under the condition that the target object is not identified, brightness adjustment corresponding to a plurality of brightnesses is carried out on the image to be identified, and a plurality of adjusted images to be identified are obtained;
performing the target object recognition on the to-be-recognized areas on the adjusted to-be-recognized images;
and under the condition that the target object is identified, carrying out exposure processing on the target object on the adjusted image to be identified with the target object to obtain an exposure image.
4. The method according to claim 2, wherein after the target object recognition is performed on the region to be recognized, the method further comprises:
determining the brightness of the image to be recognized under the condition that the target object is not recognized;
when the brightness is larger than a first brightness, dimming the image to be recognized according to a first brightness interval value to obtain a dimmed image to be recognized;
performing the target object recognition on the to-be-recognized area on the dimmed to-be-recognized image;
and under the condition that the target object is not identified, dimming the dimmed image to be identified according to the first brightness interval value to obtain a current dimmed image to be identified, identifying the target object in the region to be identified on the current dimmed image to be identified until the target object is identified, and exposing the target object on the dimmed image to be identified to obtain an exposed image.
5. The method according to claim 2, wherein after the target object recognition is performed on the region to be recognized, the method further comprises:
determining the brightness of the image to be recognized under the condition that the target object is not recognized;
when the brightness is smaller than a second brightness, the image to be recognized is brightened according to a second brightness interval numerical value to obtain a brightened image to be recognized;
performing the target object recognition on the to-be-recognized area on the brightened to-be-recognized image;
and under the condition that the target object is not identified, the brightened image to be identified is brightened according to the second brightness interval numerical value to obtain a current brightened image to be identified, the target object is identified in the area to be identified on the current brightened image to be identified until the target object is identified, and the target object on the brightened image to be identified is exposed to obtain an exposure image.
6. The method according to claim 1, wherein the performing exposure processing on the target object to obtain an exposure image when the target object is determined and the target object is identified comprises:
carrying out preset object recognition on the image to be recognized; under the condition that the preset object is not identified, brightness adjustment corresponding to a plurality of brightnesses is carried out on the image to be identified, and a plurality of adjusted images to be identified are obtained;
performing the target object recognition on the plurality of adjusted images to be recognized;
and under the condition that the target object is identified, carrying out exposure processing on the target object on the adjusted image to be identified with the target object to obtain an exposure image.
7. The method of any of claims 2-6, wherein the target object comprises a human face; the preset object comprises a human shape;
the preset object recognition of the image to be recognized comprises the following steps:
carrying out human shape recognition on the image to be recognized through a human shape recognition network;
the target object recognition of the region to be recognized includes:
and carrying out the face recognition on the area to be recognized through a face recognition network.
8. The method according to any one of claims 1 to 7, wherein the luminance abnormal region includes a first luminance abnormal region;
the brightness adjustment of the brightness abnormal area to obtain an image to be identified comprises the following steps:
adjusting the brightness of the first brightness abnormal area based on a first brightness adjusting parameter to obtain an image to be identified;
the brightness of the first brightness abnormal area in the image to be identified is lower than that of the first brightness abnormal area on the image to be exposed.
9. The method according to claims 1 to 8, wherein the luminance abnormal region comprises a second luminance abnormal region;
the brightness adjustment of the brightness abnormal area to obtain an image to be identified comprises the following steps:
adjusting the brightness of the second brightness abnormal area based on a second brightness adjusting parameter to obtain an image to be identified;
the brightness of the second brightness abnormal area in the image to be identified is higher than that of the second brightness abnormal area on the image to be exposed.
10. The method of claim 1, wherein after acquiring the image to be exposed, further comprising:
performing brightness identification on the image to be exposed, and determining a brightness non-abnormal area on the image to be exposed;
and carrying out target object identification on the brightness non-abnormal area, and carrying out exposure processing on the target object under the condition of determining the target object to obtain an exposure image.
11. An exposure apparatus for a target object, comprising:
the image acquisition module is used for acquiring an image to be exposed;
the area determining module is used for carrying out brightness identification on the image to be exposed and determining a brightness abnormal area on the image to be exposed;
the brightness adjusting module is used for adjusting the brightness of the abnormal brightness area to obtain an image to be identified;
and the image exposure module is used for carrying out exposure processing on the target object to obtain an exposure image under the conditions that the target object is identified and determined for the image to be identified.
12. A computer-readable storage medium, in which at least one instruction or at least one program is stored, which is loaded and executed by a processor to implement a target object exposure method according to any one of claims 1 to 10.
13. An electronic device comprising at least one processor, and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the at least one processor implementing a method of exposing a target object as claimed in any one of claims 1 to 10 by executing the instructions stored by the memory.
CN202110127188.6A 2021-01-29 2021-01-29 Target object exposure method, device, storage medium and equipment Pending CN112819714A (en)

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