CN109089041A - Recognition methods, device, electronic equipment and the storage medium of photographed scene - Google Patents
Recognition methods, device, electronic equipment and the storage medium of photographed scene Download PDFInfo
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- CN109089041A CN109089041A CN201810962785.9A CN201810962785A CN109089041A CN 109089041 A CN109089041 A CN 109089041A CN 201810962785 A CN201810962785 A CN 201810962785A CN 109089041 A CN109089041 A CN 109089041A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/61—Control of cameras or camera modules based on recognised objects
- H04N23/611—Control of cameras or camera modules based on recognised objects where the recognised objects include parts of the human body
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/002—Diagnosis, testing or measuring for television systems or their details for television cameras
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- Physics & Mathematics (AREA)
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Abstract
The application proposes recognition methods, device, electronic equipment and the storage medium of a kind of photographed scene, wherein method includes: detection present filming scene, and obtains the corresponding scene detection results of present filming scene；When scene detection results are the scene of non-night scene scene and inhuman image field scape, judge in preview image with the presence or absence of face area-of-interest；If there are face area-of-interests in preview image, the ISO value of preview image is obtained；Judge whether the ISO value of preview image is greater than preset threshold；If the ISO value of preview image is greater than preset threshold, it is determined that present filming scene is night scene scene.This method is able to ascend the accuracy of night scene scene detection, and then promotes image quality and imaging effect, improves the shooting experience of user.
Description
Technical field
The present invention relates to technical field of imaging more particularly to a kind of recognition methods of photographed scene, device, electronic equipment and
Storage medium.
Background technique
With the continuous development of imaging technique and terminal technology, more and more users are clapped using electronic equipment
According to.In night scene scene, since the brightness value of ambient enviroment is lower, if electronic equipment can not correctly identify current shooting field
It is poor then to may cause image quality for scape.
In the prior art, it can determine whether present filming scene is night scene scene according to following three kinds of modes: the first
Mode determines present filming scene by user, and then is manually set to enter night scene mode；The second way passes through shooting
The ISO value of image and time for exposure determine present filming scene, specifically, are fixed by the way that the time for exposure is arranged, when ISO value is got over
When big, show that present filming scene is darker, at this point it is possible to determine that present filming scene is night scene mode；The third mode, passes through
Training night scene scene Recognition model, identifies present filming scene.
But first way, user's manual setting is needed, it is complex for operation step；The second way, according only to ISO value,
Determine whether that for night scene scene, in some scenes, the accuracy rate that may cause identification is lower, for example, when subscriber station is in night scene
When finding a view under lamp source, at this point, non-night scene scene may be identified as；The third mode, it is understood that there may be the feelings of missing inspection portrait scene
Condition is embodied in other scenes being identified as except night scene scene and portrait scene, when scene recognition result is other scenes
When, at this point, will be unable to enter super night scene mode.
Summary of the invention
The application proposes recognition methods, device, electronic equipment and the storage medium of a kind of photographed scene, for realizing promotion
The accuracy of night scene scene detection, and then image quality and imaging effect are promoted, improve the shooting experience of user, it is existing to solve
The lower technical problem of the accuracy rate of night scene scene Recognition in technology.
The application one side embodiment proposes a kind of recognition methods of photographed scene, comprising:
Present filming scene is detected, and obtains the corresponding scene detection results of the present filming scene；
When the scene detection results are the scene of non-night scene scene and inhuman image field scape, judge in preview image whether
There are face area-of-interests；
If there are the face area-of-interests in the preview image, the ISO value of the preview image is obtained；
Judge whether the ISO value of the preview image is greater than preset threshold；
If the ISO value of the preview image is greater than the preset threshold, it is determined that the present filming scene is night scene
Scene.
The recognition methods of the photographed scene of the embodiment of the present application by detecting present filming scene, and obtains current shooting
The corresponding scene detection results of scene, when scene detection results are the scene of non-night scene scene and inhuman image field scape, judgement is pre-
It lookes at the presence or absence of face area-of-interest in image, if so, the ISO value of preview image is obtained, next, it is determined that preview image
Whether ISO value is greater than preset threshold, if so, determining that present filming scene is night scene scene.In the application, in current shooting field
Scape be non-night scene scene and the scene of inhuman image field scape when, can also according in preview image whether there is face area-of-interest
And the ISO value of preview image, determine whether present filming scene is night scene scene, can promote the accurate of night scene scene detection
Property, and then image quality and imaging effect are promoted, improve the shooting experience of user.
The another aspect embodiment of the application proposes a kind of identification device of photographed scene, comprising:
Detection module for detecting present filming scene, and obtains the corresponding scene detection knot of the present filming scene
Fruit；
First judgment module, for when the scene detection results are the scene of non-night scene scene and inhuman image field scape,
Judge in preview image with the presence or absence of face area-of-interest；
Module is obtained, if for, there are the face area-of-interest, obtaining the preview in the preview image
The ISO value of image；
Second judgment module, for judging whether the ISO value of the preview image is greater than preset threshold；
First determining module, if the ISO value for the preview image is greater than the preset threshold, it is determined that described to work as
Preceding photographed scene is night scene scene.
The identification device of the photographed scene of the embodiment of the present application by detecting present filming scene, and obtains current shooting
The corresponding scene detection results of scene, when scene detection results are the scene of non-night scene scene and inhuman image field scape, judgement is pre-
It lookes at the presence or absence of face area-of-interest in image, if so, the ISO value of preview image is obtained, next, it is determined that preview image
Whether ISO value is greater than preset threshold, if so, determining that present filming scene is night scene scene.In the application, in current shooting field
Scape be non-night scene scene and the scene of inhuman image field scape when, can also according in preview image whether there is face area-of-interest
And the ISO value of preview image, determine whether present filming scene is night scene scene, can promote the accurate of night scene scene detection
Property, and then image quality and imaging effect are promoted, improve the shooting experience of user.
The another aspect embodiment of the application proposes a kind of electronic equipment, including processor, memory and is stored in described
On memory and the computer program that can run on the processor, the processor is for executing such as this Shen previous embodiment
The recognition methods of the photographed scene of proposition.
The another aspect embodiment of the application proposes a kind of non-transitorycomputer readable storage medium, is stored thereon with meter
Calculation machine program realizes the identification side of the photographed scene proposed such as this Shen previous embodiment when the computer program is executed by processor
Method.
The additional aspect of the present invention and advantage will be set forth in part in the description, and will partially become from the following description
Obviously, or practice through the invention is recognized.
Detailed description of the invention
Above-mentioned and/or additional aspect and advantage of the invention will become from the following description of the accompanying drawings of embodiments
Obviously and it is readily appreciated that, in which:
Fig. 1 is the flow diagram of the recognition methods of photographed scene provided by the embodiment of the present application one；
Fig. 2 is the flow diagram of the recognition methods of photographed scene provided by the embodiment of the present application two；
Fig. 3 is the flow diagram of the recognition methods of photographed scene provided by the embodiment of the present application three；
Fig. 4 is the structural schematic diagram of the identification device of photographed scene provided by the embodiment of the present application four；
Fig. 5 is the structural schematic diagram of the identification device of photographed scene provided by the embodiment of the present application five；
Fig. 6 is the module diagram of the electronic equipment of the application certain embodiments；
Fig. 7 is the module diagram of the image processing circuit of the application certain embodiments.
Specific embodiment
The embodiment of the present invention is described below in detail, examples of the embodiments are shown in the accompanying drawings, wherein from beginning to end
Same or similar label indicates same or similar element or element with the same or similar functions.Below with reference to attached
The embodiment of figure description is exemplary, it is intended to is used to explain the present invention, and is not considered as limiting the invention.
The application technical problem lower mainly for the accuracy rate of night scene scene Recognition in the prior art, proposes a kind of bat
Take the photograph the recognition methods of scene.
The recognition methods of the photographed scene of the embodiment of the present application by detecting present filming scene, and obtains current shooting
The corresponding scene detection results of scene, when scene detection results are the scene of non-night scene scene and inhuman image field scape, judgement is pre-
It lookes at the presence or absence of face area-of-interest in image, if so, the ISO value of preview image is obtained, next, it is determined that preview image
Whether ISO value is greater than preset threshold, if so, determining that present filming scene is night scene scene.In the application, in current shooting field
Scape be non-night scene scene and the scene of inhuman image field scape when, can also according in preview image whether there is face area-of-interest
And the ISO value of preview image, determine whether present filming scene is night scene scene, can promote the accurate of night scene scene detection
Property, and then image quality and imaging effect are promoted, improve the shooting experience of user.
Below with reference to the accompanying drawings recognition methods, device, electronic equipment and the storage of the photographed scene of the embodiment of the present application are described
Medium
Fig. 1 is the flow diagram of the recognition methods of photographed scene provided by the embodiment of the present application one.
As shown in Figure 1, the recognition methods of the photographed scene may comprise steps of:
Step 101, present filming scene is detected, and obtains the corresponding scene detection results of present filming scene.
In the embodiment of the present application, the corresponding preview image of present filming scene can be obtained by imaging device, according to pre-
It lookes at the image content of image, determines that the corresponding scene detection results of present filming scene, obtained scene detection results can be
Present filming scene is that perhaps present filming scene is people's image field scape to night scene scene or present filming scene is non-night scene field
The scene of scape and inhuman image field scape.Wherein, portrait scene can refer specifically to group photo scene.
It is alternatively possible to be determined according to the image content of preview image and/or the ambient brightness value in each region of preview image
Whether present filming scene is night scene scene.For example, the image content when preview image includes night sky or night scene lamp source
Etc., it can determine that present filming scene is night scene scene, alternatively, ambient brightness value meets night scene in each region of preview image
Under environment when the Luminance Distribution characteristic of image, it can determine that present filming scene is night scene scene.
It is alternatively possible to determine whether present filming scene is people's image field scape according to the image content of preview image.Example
Such as, it can be based on face recognition technology, detected with the presence or absence of at least two faces in the image content of preview image, when in the presence of extremely
When few two faces, it can determine that present filming scene is people's image field scape, alternatively, it is also based on edge feature detection technique,
Each imaging object in preview image is extracted, so as to determine whether present filming scene is people according to each imaging object
Image field scape, for example, when determining that there are when at least two people, can determine present filming scene behaviour according to the imaging object of extraction
Image field scape.Wherein, common face recognition algorithms may include: the recognizer (Feature-based based on human face characteristic point
Recognition algorithms), the recognizer (Appearance-based based on whole picture facial image
Recognition algorithms), recognizer (the Template-based recognition based on template
Algorithms), algorithm (the Recognition algorithms using neural identified using neural network
Network) etc..
Step 102, when scene detection results are the scene of non-night scene scene and inhuman image field scape, judge in preview image
With the presence or absence of face area-of-interest.
In the embodiment of the present application, when present filming scene is the scene of non-night scene scene and inhuman image field scape, it can sentence
It whether there is face area-of-interest (Regions of Interest, abbreviation ROI) in disconnected preview image.For example, can be based on
Face recognition technology determines in preview image with the presence or absence of face area-of-interest.It is interested that there are faces in preview image
When region, when can trigger step 103, and there is no face area-of-interest in preview image, current shooting can be determined
Scene is non-night scene scene, that is, determines that present filming scene is standard photographed scene.
Step 103, if there are face area-of-interests in preview image, the ISO value of preview image is obtained.
In the embodiment of the present application, there are when face area-of-interest in preview image, the ISO of available preview image
Value.Wherein, ISO value is used to refer to the sensitivity of camera, and common ISO value has 50,100,200,400,1000 etc., generally
In the case where bright and clear, ISO value can be 50 or 100, and in the case where insufficient light, ISO value can be 400 or more
It is high.
Optionally, camera can automatically adjust ISO value according to ambient brightness value, thus, in the application, it can pass through
Photosensitive element measurement obtains the ambient brightness value in each region of preview image in camera, determines the ISO value of preview image.
Step 104, judge whether the ISO value of preview image is greater than preset threshold.
In the embodiment of the present application, preset threshold can night scene scene be preset according to, and preset threshold can be electricity
The plug-in of sub- equipment is pre-set, alternatively, preset threshold can also be configured by user, with no restriction to this.
In the embodiment of the present application, when using fixed exposure time shooting preview image, it can be determined that the ISO of preview image
Whether value is greater than preset threshold, if so, showing that the ambient brightness value of present filming scene is lower, at this point it is possible to trigger step
105, if it is not, then showing that the ambient brightness value of present filming scene is higher, at this point it is possible to determine that present filming scene is non-night scene
Scene, as standard photographed scene.
Step 105, if the ISO value of preview image is greater than preset threshold, it is determined that present filming scene is night scene scene.
In the embodiment of the present application, when the IOS value of pre-set image is greater than preset threshold, show the environment of present filming scene
Brightness value is lower, at this point it is possible to determine that present filming scene is night scene scene.
It should be noted that when using revocable exposure time shooting preview image, it can also be according to exposure time
Determine whether present filming scene is night scene scene.Specifically, when longer upon exposure, shooting environmental is darker, therefore, this Shen
Please in, when the exposure time of preview image be greater than first threshold when, can determine present filming scene be night scene scene.Wherein,
First threshold can be preset according to night scene scene.
The recognition methods of the photographed scene of the embodiment of the present application by detecting present filming scene, and obtains current shooting
The corresponding scene detection results of scene, when scene detection results are the scene of non-night scene scene and inhuman image field scape, judgement is pre-
It lookes at the presence or absence of face area-of-interest in image, if so, the ISO value of preview image is obtained, next, it is determined that preview image
Whether ISO value is greater than preset threshold, if so, determining that present filming scene is night scene scene.In the application, in current shooting field
Scape be non-night scene scene and the scene of inhuman image field scape when, can also according in preview image whether there is face area-of-interest
And the ISO value of preview image, determine whether present filming scene is night scene scene, can promote the accurate of night scene scene detection
Property, and then image quality and imaging effect are promoted, improve the shooting experience of user.
In order to clearly illustrate above-described embodiment, this application provides the recognition methods of another photographed scene, Fig. 2 is this Shen
Please photographed scene provided by embodiment two recognition methods flow diagram.
As shown in Fig. 2, the recognition methods of the photographed scene may comprise steps of:
Step 201, judge whether present filming scene is night scene scene, if so, step 208 is executed, if it is not, executing step
202。
In the embodiment of the present application, when determination judges present filming scene for night scene scene, screening-mode can be switched
For super night scene mode, and when determining present filming scene is non-night scene scene, in order to promote the accuracy of testing result, also
Can according in preview image whether the ISO value comprising portrait and preview image, determine whether present filming scene is night scene
Scene.
Step 202, judge whether present filming scene is people's image field scape, if so, step 203 is executed, if it is not, executing step
204。
Step 203, judge whether the ISO value of preview image is greater than preset threshold, if so, step 207 is executed, if it is not, holding
Row step 209.
In the embodiment of the present application, when the ISO value of preview image is greater than preset threshold, show the environment of present filming scene
Brightness value is lower, at this point it is possible to determine that present filming scene is night scene scene, and the ISO value in preview image is less than or waits
It, can also be according to whether there is face sense in preview image at this point, in order to promote the accuracy of testing result when preset threshold
The ISO value of interest region and preview image determines whether present filming scene is night scene scene.
It should be noted that can also be utilized at image in the related technology when present filming scene is people's image field scape
Reason technology, portrait is deducted, and then calculates the grey level histogram of the background area in preview image in addition to portrait, thus
According to the distribution character of grey level histogram, determine whether present filming scene is night scene scene.
Step 204, judge with the presence or absence of face area-of-interest in preview image, if so, step 205 is executed, if it is not, holding
Row step 209.
Step 205, the ISO value of preview image is obtained.
Step 206, judge whether the ISO value of preview image is greater than preset threshold, if so, step 207 is executed, if it is not, holding
Row step 209.
Step 207, determine that present filming scene is night scene scene.
Step 208, screening-mode is switched to super night scene mode.
In the embodiment of the present application, after screening-mode is switched to super night scene mode, super night scene mode can be used
It is imaged.
Optionally, under super night scene mode, different exposures, shoot multi-frame images, and then to multiframe figure can be used
As being synthesized, target image is obtained.It should be noted that in the night mode, in order to promote the image quality of target image,
The corresponding exposure time of each exposure is no less than second threshold.Wherein, second threshold can be preset in the interior of electronic equipment
It sets in program, alternatively, second threshold can be configured by user, with no restriction to this.
Step 209, determine that present filming scene is standard photographed scene.
In the embodiment of the present application, when determining present filming scene is standard photographed scene, screening-mode can be switched
For common screening-mode, can be then imaged using common screening-mode.
The recognition methods of the photographed scene of the embodiment of the present application, by determining that present filming scene is non-night scene scene
When, further according to the ISO value that whether there is face area-of-interest and preview image in preview image, determine current shooting
Whether scene is night scene scene, can promote the accuracy of night scene scene detection, and then promote image quality and imaging effect, change
The shooting experience of kind user
As a kind of possible implementation, in order to promote the accuracy of scene detection results, machine learning can be based on
Mode, present filming scene is identified.Below with reference to Fig. 2, the above process is described in detail.
Fig. 3 is the flow diagram of the recognition methods of photographed scene provided by the embodiment of the present application three.
As shown in figure 3, step 101 can specifically include following sub-step:
Step 301, the corresponding preview image of present filming scene is obtained, and extracts the characteristics of image of preview image.
In the embodiment of the present application, the corresponding preview image of present filming scene can be obtained by imaging device, then may be used
To extract the characteristics of image of preview image based on technologies such as image feature extraction techniques, key point identifications.
Step 302, characteristics of image is input to the scene Recognition model pre-established, to identify present filming scene pair
The scene detection results answered.
In the embodiment of the present application, scene Recognition model is the model after training.
As a kind of possible implementation, the corresponding sample image of different photographed scenes can be acquired in advance, then
The photographed scene of sample image is labeled, using the sample image after mark, scene Recognition model is trained, it can be with
Scene Recognition model after being trained.To the scene Recognition mould after the characteristics of image for obtaining preview image is input to training
Type, it can obtain the corresponding scene detection results of present filming scene.
As alternatively possible implementation, photographed scene sample information can be acquired, and to scene sample information into
The description of row feature and definition, the scene sample information after then feature is described and defined are input to deep neural network and instruct
Practice, scene Recognition model can be generated.To the scene Recognition mould after the characteristics of image for obtaining preview image is input to training
Type, it can obtain the corresponding scene detection results of present filming scene.
The recognition methods of the photographed scene of the embodiment of the present application determines current shooting by way of based on machine learning
Scene can promote the accuracy of scene detection results.
In order to realize above-described embodiment, the application also proposes a kind of identification device of photographed scene.
Fig. 4 is the structural schematic diagram of the identification device of photographed scene provided by the embodiment of the present application four.
As shown in figure 4, the identification device 100 of the photographed scene may include: detection module 101, first judgment module
102, module 103, the second judgment module 104 and the first determining module 105 are obtained.
Detection module 101 for detecting present filming scene, and obtains the corresponding scene detection knot of present filming scene
Fruit.
First judgment module 102, for sentencing when scene detection results are the scene of non-night scene scene and inhuman image field scape
It whether there is face area-of-interest in disconnected preview image.
Module 103 is obtained, if obtaining the ISO of preview image for there are face area-of-interests in preview image
Value.
Second judgment module 104, for judging whether the ISO value of preview image is greater than preset threshold.
First determining module 105, if the ISO value for preview image is greater than preset threshold, it is determined that current shooting field
Scape is night scene scene.
Further, as a kind of possible implementation of the embodiment of the present application, referring to Fig. 5, embodiment shown in Fig. 4
On the basis of, the identification device 100 of the photographed scene can also include:
Second determining module 106 determines current shooting field when for face area-of-interest to be not present in preview image
Scape is standard photographed scene.
ISO value obtains module 107, for directly acquiring the ISO of preview image when scene detection results are people's image field scape
Value.
Third judgment module 108, for whether being greater than preset threshold in the ISO value for judging preview image.
Third determining module 109, if the ISO value for preview image is greater than preset threshold, it is determined that current shooting field
Scape is night scene scene.
4th determining module 110, if the ISO value for preview image is less than preset threshold, it is determined that current shooting field
Scape is standard photographed scene.
Switching module 111, for screening-mode being switched to super after determining that present filming scene is night scene scene
Night scene mode.
It should be noted that the explanation of the aforementioned recognition methods embodiment to photographed scene is also applied for the embodiment
To the identification device 100 of photographed scene, it is not repeated herein.
The identification device of the photographed scene of the embodiment of the present application by detecting present filming scene, and obtains current shooting
The corresponding scene detection results of scene, when scene detection results are the scene of non-night scene scene and inhuman image field scape, judgement is pre-
It lookes at the presence or absence of face area-of-interest in image, if so, the ISO value of preview image is obtained, next, it is determined that preview image
Whether ISO value is greater than preset threshold, if so, determining that present filming scene is night scene scene.In the application, in current shooting field
Scape be non-night scene scene and the scene of inhuman image field scape when, can also according in preview image whether there is face area-of-interest
And the ISO value of preview image, determine whether present filming scene is night scene scene, can promote the accurate of night scene scene detection
Property, and then image quality and imaging effect are promoted, improve the shooting experience of user.
In order to realize above-described embodiment, the application also proposes a kind of electronic equipment, comprising: memory, processor and storage
On a memory and the computer program that can run on a processor, it when processor executes program, realizes such as above-described embodiment
The recognition methods of photographed scene.
Referring to Fig. 6, the application also provides another electronic equipment 200.Electronic equipment 200 includes memory 50 and processing
Device 60.Computer-readable instruction is stored in memory 50.When computer-readable instruction is stored by 50 execution, so that processor
60 execute the recognition methods to photographed scene of any of the above-described embodiment.
Fig. 6 is the schematic diagram of internal structure of electronic equipment 200 in one embodiment.The electronic equipment 200 includes passing through to be
Processor 60, the memory 50 (for example, non-volatile memory medium), built-in storage 82,83 and of display screen of bus 81 of uniting connection
Input unit 84.Wherein, the memory 50 of electronic equipment 200 is stored with operating system and computer-readable instruction.The computer
Readable instruction can be executed by processor 60, to realize the recognition methods of the photographed scene of the application embodiment.The processor 60
For providing calculating and control ability, the operation of entire electronic equipment 200 is supported.The built-in storage 50 of electronic equipment 200 is to deposit
The operation of computer-readable instruction in reservoir 52 provides environment.The display screen 83 of electronic equipment 200 can be liquid crystal display
Or electric ink display screen etc., input unit 84 can be the touch layer covered on display screen 83, be also possible to electronic equipment
Key, trace ball or the Trackpad being arranged on 200 shells, are also possible to external keyboard, Trackpad or mouse etc..The electronics is set
Standby 200 can be mobile phone, tablet computer, laptop, personal digital assistant or wearable device (such as Intelligent bracelet, intelligence
Energy wrist-watch, intelligent helmet, intelligent glasses) etc..It will be understood by those skilled in the art that structure shown in Fig. 6, only and originally
The schematic diagram of the relevant part-structure of application scheme does not constitute the electronic equipment 200 being applied thereon to application scheme
Restriction, specific electronic equipment 200 may include than more or fewer components as shown in the figure, or the certain components of combination,
Or with different component layouts.
Referring to Fig. 7, including image processing circuit 90, image processing circuit in the electronic equipment 200 of the embodiment of the present application
90 can be realized using hardware and or software component, including define ISP (Image Signal Processing, at picture signal
Reason) pipeline various processing units.Fig. 7 is the schematic diagram of image processing circuit 90 in one embodiment.As shown in fig. 7, for just
In explanation, the various aspects of image processing techniques relevant to the embodiment of the present application are only shown.
As shown in fig. 7, image processing circuit 90 includes ISP processor 91 (ISP processor 91 can be processor 60) and controls
Logic device 92 processed.The image data that camera 93 captures is handled by ISP processor 91 first, and ISP processor 91 is to image data
It is analyzed to capture the image statistics for the one or more control parameters that can be used for determining camera 93.Camera 93 can
Including one or more lens 932 and imaging sensor 934.Imaging sensor 934 may include colour filter array (such as Bayer
Filter), imaging sensor 934 can obtain the luminous intensity and wavelength information that each imaging pixel captures, and provide and can be handled by ISP
One group of raw image data of the processing of device 91.Sensor 94 (such as gyroscope) can be based on 94 interface type of sensor the figure of acquisition
As the parameter (such as stabilization parameter) of processing is supplied to ISP processor 91.94 interface of sensor can be SMIA (Standard
Mobile Imaging Architecture, Standard Mobile Imager framework) interface, other serial or parallel camera interfaces or
The combination of above-mentioned interface.
In addition, raw image data can also be sent to sensor 94 by imaging sensor 934, sensor 94 can be based on sensing
Raw image data is supplied to ISP processor 91 or sensor 94 and arrives raw image data storage by 94 interface type of device
In video memory 95.
ISP processor 91 handles raw image data pixel by pixel in various formats.For example, each image pixel can have
There is the bit depth of 8,10,12 or 14 bits, ISP processor 91 can carry out one or more image procossing behaviour to raw image data
Make, statistical information of the collection about image data.Wherein, image processing operations can by identical or different bit depth precision into
Row.
ISP processor 91 can also receive image data from video memory 95.For example, 94 interface of sensor is by original image
Data are sent to video memory 95, and the raw image data in video memory 95 is available to ISP processor 91 for place
Reason.Video memory 95 can be independent special in memory 50, a part of memory 50, storage equipment or electronic equipment
It with memory, and may include DMA (Direct Memory Access, direct direct memory access (DMA)) feature.
When receiving the original from 934 interface of imaging sensor or from 94 interface of sensor or from video memory 95
When beginning image data, ISP processor 91 can carry out one or more image processing operations, such as time-domain filtering.Treated image
Data can be transmitted to video memory 95, to carry out other processing before shown.ISP processor 91 is stored from image
Device 95 receives processing data, and carries out at the image data in original domain and in RGB and YCbCr color space to processing data
Reason.Treated that image data may be output to display 97 (display 97 may include display screen 83) for ISP processor 91, for
Family is watched and/or is further processed by graphics engine or GPU (Graphics Processing Unit, graphics processor).This
Outside, the output of ISP processor 91 also can be transmitted to video memory 95, and display 97 can read image from video memory 95
Data.In one embodiment, video memory 95 can be configured to realize one or more frame buffers.In addition, ISP is handled
The output of device 91 can be transmitted to encoder/decoder 96, so as to encoding/decoding image data.The image data of coding can be protected
It deposits, and is decompressed before being shown in 97 equipment of display.Encoder/decoder 96 can be real by CPU or GPU or coprocessor
It is existing.
The statistical data that ISP processor 91 determines, which can be transmitted, gives control logic device Unit 92.For example, statistical data may include
The imaging sensors such as automatic exposure, automatic white balance, automatic focusing, flicker detection, black level compensation, 932 shadow correction of lens
934 statistical informations.Control logic device 92 may include the processing element and/or microcontroller for executing one or more routines (such as firmware)
Device, one or more routines can statistical data based on the received, determine the control parameter of camera 93 and the control of ISP processor 91
Parameter processed.For example, the control parameter of camera 93 may include 94 control parameter of sensor (such as the integral of gain, spectrum assignment
Time, stabilization parameter etc.), camera flash control parameter, 932 control parameter of lens (such as focus or zoom focal length) or
The combination of these parameters.ISP control parameter may include for automatic white balance and color adjustment (for example, during RGB processing)
932 shadow correction parameter of gain level and color correction matrix and lens.
The following are realize the recognition methods to photographed scene with image processing techniques in Fig. 7:
Present filming scene is detected, and obtains the corresponding scene detection results of the present filming scene；
When the scene detection results are the scene of non-night scene scene and inhuman image field scape, judge in preview image whether
There are face area-of-interests；
If there are the face area-of-interests in the preview image, the ISO value of the preview image is obtained；
Judge whether the ISO value of the preview image is greater than preset threshold；
If the ISO value of the preview image is greater than the preset threshold, it is determined that the present filming scene is night scene
Scene.
In order to realize above-described embodiment, the application also proposes a kind of computer readable storage medium, is stored thereon with calculating
Machine program, which is characterized in that the identification to photographed scene as described in above-described embodiment is realized when the program is executed by processor
Method.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means specific features, structure, material or spy described in conjunction with this embodiment or example
Point is included at least one embodiment or example of the invention.In the present specification, schematic expression of the above terms are not
It must be directed to identical embodiment or example.Moreover, particular features, structures, materials, or characteristics described can be in office
It can be combined in any suitable manner in one or more embodiment or examples.In addition, without conflicting with each other, the skill of this field
Art personnel can tie the feature of different embodiments or examples described in this specification and different embodiments or examples
It closes and combines.
In addition, term " first ", " second " are used for descriptive purposes only and cannot be understood as indicating or suggesting relative importance
Or implicitly indicate the quantity of indicated technical characteristic.Define " first " as a result, the feature of " second " can be expressed or
Implicitly include at least one this feature.In the description of the present invention, the meaning of " plurality " is at least two, such as two, three
It is a etc., unless otherwise specifically defined.
Any process described otherwise above or method description are construed as in flow chart or herein, and expression includes
It is one or more for realizing custom logic function or process the step of executable instruction code module, segment or portion
Point, and the range of the preferred embodiment of the present invention includes other realization, wherein can not press shown or discussed suitable
Sequence, including according to related function by it is basic simultaneously in the way of or in the opposite order, to execute function, this should be of the invention
Embodiment person of ordinary skill in the field understood.
Expression or logic and/or step described otherwise above herein in flow charts, for example, being considered use
In the order list for the executable instruction for realizing logic function, may be embodied in any computer-readable medium, for
Instruction execution system, device or equipment (such as computer based system, including the system of processor or other can be held from instruction
The instruction fetch of row system, device or equipment and the system executed instruction) it uses, or combine these instruction execution systems, device or set
It is standby and use.For the purpose of this specification, " computer-readable medium ", which can be, any may include, stores, communicates, propagates or pass
Defeated program is for instruction execution system, device or equipment or the dress used in conjunction with these instruction execution systems, device or equipment
It sets.The more specific example (non-exhaustive list) of computer-readable medium include the following: there is the electricity of one or more wirings
Interconnecting piece (electronic device), portable computer diskette box (magnetic device), random access memory (RAM), read-only memory
(ROM), erasable edit read-only storage (EPROM or flash memory), fiber device and portable optic disk is read-only deposits
Reservoir (CDROM).In addition, computer-readable medium can even is that can on it the paper of print routine or other suitable be situated between
Matter, because can then be edited, be interpreted or when necessary with other for example by carrying out optical scanner to paper or other media
Suitable method is handled electronically to obtain program, is then stored in computer storage.
It should be appreciated that each section of the invention can be realized with hardware, software, firmware or their combination.Above-mentioned
In embodiment, software that multiple steps or method can be executed in memory and by suitable instruction execution system with storage
Or firmware is realized.Such as, if realized with hardware in another embodiment, following skill well known in the art can be used
Any one of art or their combination are realized: have for data-signal is realized the logic gates of logic function from
Logic circuit is dissipated, the specific integrated circuit with suitable combinational logic gate circuit, programmable gate array (PGA), scene can compile
Journey gate array (FPGA) etc..
Those skilled in the art are understood that realize all or part of step that above-described embodiment method carries
Suddenly be that relevant hardware can be instructed to complete by program, program can store in a kind of computer readable storage medium
In, which when being executed, includes the steps that one or a combination set of embodiment of the method.
It, can also be in addition, each functional unit in each embodiment of the present invention can integrate in a processing module
It is that each unit physically exists alone, can also be integrated in two or more units in a module.Above-mentioned integrated mould
Block both can take the form of hardware realization, can also be realized in the form of software function module.If integrated module with
The form of software function module is realized and when sold or used as an independent product, also can store computer-readable at one
It takes in storage medium.
Storage medium mentioned above can be read-only memory, disk or CD etc..Although having been shown and retouching above
The embodiment of the present invention is stated, it is to be understood that above-described embodiment is exemplary, and should not be understood as to limit of the invention
System, those skilled in the art can be changed above-described embodiment, modify, replace and become within the scope of the invention
Type.
Claims (12)
1. a kind of recognition methods of photographed scene characterized by comprising
Present filming scene is detected, and obtains the corresponding scene detection results of the present filming scene；
When the scene detection results are the scene of non-night scene scene and inhuman image field scape, judge to whether there is in preview image
Face area-of-interest；
If there are the face area-of-interests in the preview image, the ISO value of the preview image is obtained；
Judge whether the ISO value of the preview image is greater than preset threshold；
If the ISO value of the preview image is greater than the preset threshold, it is determined that the present filming scene is night scene scene.
2. the method as described in claim 1, which is characterized in that further include:
If the face area-of-interest is not present in the preview image, it is determined that the present filming scene is standard bat
Take the photograph scene.
3. the method as described in claim 1, which is characterized in that further include:
When the scene detection results are people's image field scape, the ISO value of the preview image is directly acquired；
Judge whether the ISO value of the preview image is greater than preset threshold；
If the ISO value of the preview image is greater than the preset threshold, it is determined that the present filming scene is night scene scene.
4. method as claimed in claim 1 or 3, which is characterized in that further include:
If the ISO value of the preview image is less than the preset threshold, it is determined that the present filming scene is standard shooting
Scene.
5. the method as described in claim 1, which is characterized in that further include:
After determining that the present filming scene is night scene scene, screening-mode is switched to super night scene mode.
6. a kind of identification device of photographed scene characterized by comprising
Detection module for detecting present filming scene, and obtains the corresponding scene detection results of the present filming scene；
First judgment module, for judging when the scene detection results are the scene of non-night scene scene and inhuman image field scape
It whether there is face area-of-interest in preview image；
Module is obtained, if for, there are the face area-of-interest, obtaining the preview image in the preview image
ISO value；
Second judgment module, for judging whether the ISO value of the preview image is greater than preset threshold；
First determining module, if the ISO value for the preview image is greater than the preset threshold, it is determined that the current bat
Taking the photograph scene is night scene scene.
7. device as claimed in claim 6, which is characterized in that further include:
Second determining module, if for the face area-of-interest to be not present in the preview image, it is determined that described to work as
Preceding photographed scene is standard photographed scene.
8. device as claimed in claim 6, which is characterized in that further include:
ISO value obtains module, for directly acquiring the preview image when the scene detection results are people's image field scape
ISO value；
Third judgment module, for judging whether the ISO value of the preview image is greater than preset threshold；
Third determining module, if the ISO value for the preview image is greater than the preset threshold, it is determined that the current bat
Taking the photograph scene is night scene scene.
9. the device as described in claim 6 or 8, which is characterized in that further include:
4th determining module, if the ISO value for the preview image is less than the preset threshold, it is determined that the current bat
Taking the photograph scene is standard photographed scene.
10. device as claimed in claim 6, which is characterized in that further include:
Switching module, for after determining that the present filming scene is night scene scene, screening-mode to be switched to super night
Scape mode.
11. a kind of electronic equipment, including processor, memory and it is stored on the memory and can transports on the processor
Capable computer program, the processor are used to execute the recognition methods of photographed scene as described in any one in claim 1-5.
12. a kind of non-transitorycomputer readable storage medium, is stored thereon with computer program, the computer program is processed
Device realizes the recognition methods of photographed scene as described in any one in claim 1-5 when executing.
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| CN201810962785.9A CN109089041A (en) | 2018-08-22 | 2018-08-22 | Recognition methods, device, electronic equipment and the storage medium of photographed scene |
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| CN201810962785.9A CN109089041A (en) | 2018-08-22 | 2018-08-22 | Recognition methods, device, electronic equipment and the storage medium of photographed scene |
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