CN105472239B - Photo processing method and device - Google Patents
Photo processing method and device Download PDFInfo
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- CN105472239B CN105472239B CN201510792628.4A CN201510792628A CN105472239B CN 105472239 B CN105472239 B CN 105472239B CN 201510792628 A CN201510792628 A CN 201510792628A CN 105472239 B CN105472239 B CN 105472239B
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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
- H04N23/80—Camera processing pipelines; Components thereof
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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
-
- 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
- H04N23/68—Control of cameras or camera modules for stable pick-up of the scene, e.g. compensating for camera body vibrations
- H04N23/682—Vibration or motion blur correction
- H04N23/683—Vibration or motion blur correction performed by a processor, e.g. controlling the readout of an image memory
Abstract
The disclosure is directed to photo processing method and devices.This method comprises: being grouped to photo to be processed by preset rules；Quality testing is carried out to every group of photo to be processed, obtains the credit rating of every group of photo to be processed；The photo to be processed is stored according to the credit rating.The technical solution saves the memory space of terminal or server, reduces it and stores pressure.Meanwhile filtering out the preferable photo of shooting quality accurately for user, enable and shoots preferable photo and accurately completely save.
Description
Technical field
This disclosure relates to technical field of image processing more particularly to photo processing method and device.
Background technique
Currently, the popularization degree with mobile phone is higher and higher, user often worries the photo effect of shooting when shooting photo
It is bad, so often shooting multiple pictures to Same Scene.In this way, the backing up photos storage to cloud or mobile phone brings pole
Big pressure wastes many memory spaces.
Summary of the invention
The embodiment of the present disclosure provides photo processing method and device.The technical solution is as follows:
According to the first aspect of the embodiments of the present disclosure, a kind of photo processing method is provided, comprising:
Photo to be processed is grouped by preset rules；
Quality testing is carried out to every group of photo to be processed, obtains the credit rating of every group of photo to be processed；
The photo to be processed is stored according to the credit rating.
It is optionally, described that photo to be processed is grouped by preset rules, comprising:
Obtain the attribute information of photo to be processed, the attribute information include in the shooting time and shooting location of photo extremely
One item missing information；
The photo to be processed is grouped in advance according to the attribute information；
Similarity calculation is carried out between the photo to be processed in the pre- grouping；
Photo to be processed similar in the pre- grouping is divided into same group according to the similarity being calculated, is obtained pair
The grouping of the photo to be processed.
Optionally, described that quality testing is carried out to every group of photo to be processed, obtain the quality of every group of photo to be processed
Grade, comprising:
The mass parameter of each photo to be processed in every group is detected, the mass parameter includes at least one of following parameter:
Clarity, color saturation and face；
The credit rating of each photo to be processed in every group is determined according to the mass parameter.
It is optionally, described that quality testing is carried out to every group of photo to be processed when the mass parameter includes face parameter,
Obtain the credit rating of every group of photo to be processed, comprising:
Whether detect in the photo to be processed includes face；
When in the photo to be processed including face, determines that the credit rating of the photo to be processed is higher than and do not include people
The credit rating of the photo to be processed of face.
Optionally, described that quality testing is carried out to every group of photo to be processed when in the photo including face, obtain institute
State the credit rating of every group of photo to be processed, further includes:
The image information of facial image in the photo to be processed is obtained, described image information includes at least one of following letter
Breath: the facial image is in the position in the photo to be processed, facial image institute's accounting in the photo to be processed
The clarity of example and the facial image；
The credit rating of the photo to be processed is determined according to the image information of the facial image；Wherein, the face
Position of the image in the photo to be processed is that the credit rating of predeterminated position is higher than the facial image described to be processed
Position in photo is not the photo of predeterminated position；Facial image proportion in the photo to be processed is higher, institute
The credit rating for stating photo to be processed is higher；The clarity of the facial image is higher, the credit rating of the photo to be processed
It is higher.
Optionally, at least one of described that the photo to be processed is stored according to the credit rating including following
Operation:
According to the corresponding default compression ratio of the credit rating to being stored after the picture compression to be processed；
The photo to be processed is deleted or stored according to the credit rating；
The photo to be processed is stored in the corresponding storage location of the credit rating.
Optionally, the attribute information for obtaining photo to be processed, comprising:
Obtain the exchangeable image file of the photo to be processed；
At least one from the shooting time and shooting location for extracting the photo to be processed in the exchangeable image file
Item information.
According to the second aspect of an embodiment of the present disclosure, a kind of picture processing device is provided, comprising:
Grouping module, for being grouped to photo to be processed by preset rules；
Detection module obtains the matter of every group of photo to be processed for carrying out quality testing to every group of photo to be processed
Measure grade；
Memory module, for being stored according to the credit rating to the photo to be processed.
Optionally, the grouping module includes:
Acquisition submodule, for obtaining the attribute information of photo to be processed, when the attribute information includes the shooting of photo
Between and at least one of shooting location information；
First grouping submodule, for being grouped in advance according to the attribute information to the photo to be processed；
Computational submodule, for carrying out similarity calculation between the photo to be processed in the pre- grouping；
Second packet submodule, for according to the similarity that is calculated by photo to be processed similar in the pre- grouping
It is divided into same group, obtains the grouping to the photo to be processed.
Optionally, the detection module includes:
First detection sub-module, for detecting the mass parameter of each photo to be processed in every group, the mass parameter packet
Include at least one of following parameter: clarity, color saturation and face；
Submodule is determined, for determining the credit rating of each photo to be processed in every group according to the mass parameter.
Optionally, the detection module further include:
Second detection sub-module, for detecting in the photo to be processed when the mass parameter includes face parameter
It whether include face；
The determining submodule, for determining the photo to be processed when in the photo to be processed including face
Photo grade is higher than the photo grade of the photo to be processed not comprising face.
Optionally, the detection module further include:
Acquisition submodule, for obtaining the image information of facial image in the photo to be processed, described image packet
Include at least one of following information: position of the facial image in the photo to be processed, the facial image it is described to
Handle proportion and the clarity of the facial image in photo；
The determining submodule, for determining the quality of the photo to be processed according to the image information of the facial image
Grade；Wherein, position of the facial image in the photo to be processed is that the credit rating of predeterminated position is higher than the people
Position of the face image in the photo to be processed is not the photo of predeterminated position；The facial image is in the photo to be processed
Middle proportion is higher, and the credit rating of the photo to be processed is higher；The clarity of the facial image is higher, described wait locate
The credit rating for managing photo is higher.
Optionally, the memory module includes at least one following submodule:
First sub-module stored is used for according to the corresponding default compression ratio of the credit rating to the photo pressure to be processed
It is stored after contracting；
Second sub-module stored, for deleting or storing the photo to be processed according to the credit rating；
Third sub-module stored, for the photo to be processed to be stored in the corresponding storage location of the credit rating.
Optionally, the acquisition submodule, for obtaining the exchangeable image file of the photo to be processed；It is obtained from described
It is extracted in the exchangeable image file for taking submodule to obtain at least one in the shooting time and shooting location of the photo to be processed
Item information.
According to the third aspect of an embodiment of the present disclosure, a kind of picture processing device is provided, comprising:
Processor；
Memory for storage processor executable instruction；
Wherein, the processor is configured to:
Photo to be processed is grouped by preset rules；
Quality testing is carried out to every group of photo to be processed, obtains the credit rating of every group of photo to be processed；
The photo to be processed is stored according to the credit rating.
The technical scheme provided by this disclosed embodiment can include the following benefits:
In the present embodiment, by being grouped to photo to be processed, that is, the photo shot under Same Scene is picked out, it is right
The photo shot under Same Scene uses different storage modes according to photographic quality grade, in this way, saving terminal or server
Memory space, reduce its store pressure.Meanwhile the preferable photo of shooting quality is accurately filtered out for user, so that shooting
Preferable photo accurately can be saved completely.
In another embodiment, by being grouped according to photo property information and photo similarity to photo to be processed,
The photo shot under Same Scene can be accurately picked out, to the photo shot under Same Scene, according to photographic quality etc.
Grade uses different storage modes, in this way, saving the memory space of terminal or server, reduces it and stores pressure.Meanwhile for
Family accurately filters out the preferable photo of shooting quality, enables and shoots preferable photo and accurately completely save.
It, can be accurately right by according at least one information in shooting time and shooting location in another embodiment
Photo is grouped, so that the subsequent division to similar photo group is more acurrate, and effectively reduces the photograph for needing to calculate similarity
The quantity of piece saves the processing capacity of terminal or server.
The photo shot under Same Scene can accurately be found out by the similar photo group of division in another embodiment,
Accurately these photos are screened so as to subsequent.
In another embodiment, can determine photographic quality grade according to a variety of mass parameters, so as to it is subsequent can be accurately
Photo is handled according to photographic quality grade.
In another embodiment, different storage modes is used to photo according to photographic quality grade, can effectively be saved
The about memory space of terminal or server reduces it and stores pressure.Meanwhile accurately to filter out shooting quality preferable for user
Photo enables and shoots preferable photo and accurately completely save.
It should be understood that above general description and following detailed description be only it is exemplary and explanatory, not
The disclosure can be limited.
Detailed description of the invention
The drawings herein are incorporated into the specification and forms part of this specification, and shows the implementation for meeting the disclosure
Example, and together with specification for explaining the principles of this disclosure.
Fig. 1 is a kind of flow chart of photo processing method shown according to an exemplary embodiment.
Fig. 2 is a kind of flow chart of the photo processing method shown according to another exemplary embodiment.
Fig. 3 is a kind of flow chart of the photo processing method shown according to another exemplary embodiment.
Fig. 4 is a kind of flow chart of the photo processing method shown according to another exemplary embodiment.
Fig. 5 is a kind of flow chart of the photo processing method shown according to another exemplary embodiment.
Fig. 6 is a kind of block diagram of picture processing device shown according to an exemplary embodiment.
Fig. 7 is the block diagram of grouping module shown according to an exemplary embodiment.
Fig. 8 a is the block diagram of detection module shown according to an exemplary embodiment.
Fig. 8 b is the block diagram of the detection module shown according to another exemplary embodiment.
Fig. 8 c is the block diagram of the detection module shown according to another exemplary embodiment.
Fig. 9 is the block diagram of memory module shown according to an exemplary embodiment.
Figure 10 is a kind of block diagram of device for photo processing shown according to an exemplary embodiment.
Figure 11 is a kind of block diagram of device for photo processing shown according to an exemplary embodiment.
Specific embodiment
Example embodiments are described in detail here, and the example is illustrated in the accompanying drawings.Following description is related to
When attached drawing, unless otherwise indicated, the same numbers in different drawings indicate the same or similar elements.Following exemplary embodiment
Described in embodiment do not represent all implementations consistent with this disclosure.On the contrary, they be only with it is such as appended
The example of the consistent device and method of some aspects be described in detail in claims, the disclosure.
The technical solution that the embodiment of the present disclosure provides, is related to server or terminal.The terminal can be mobile phone, calculate
Machine, digital camera, digital broadcasting terminal, messaging device, game console, tablet device, Medical Devices, body-building equipment,
Any equipment with image processing function such as personal digital assistant.
Fig. 1 is a kind of flow chart of photo processing method shown according to an exemplary embodiment, as shown in Figure 1, photo
Processing method is in terminal or server, comprising the following steps:
In step s 11, photo to be processed is grouped by preset rules；
In step s 12, quality testing is carried out to every group of photo to be processed, obtains the quality etc. of every group of photo to be processed
Grade；
In step s 13, photo to be processed is stored according to credit rating.
In the present embodiment, by being grouped to photo to be processed, that is, the photo shot under Same Scene is picked out, it is right
The photo shot under Same Scene uses different storage modes according to photographic quality grade, in this way, saving terminal or server
Memory space, reduce its store pressure.Meanwhile the preferable photo of shooting quality is accurately filtered out for user, so that shooting
Preferable photo accurately can be saved completely.
Fig. 2 is a kind of flow chart of the photo processing method shown according to another exemplary embodiment, as shown in Fig. 2,
In another embodiment, photo to be processed is grouped by preset rules, comprising:
In the step s 21, the attribute information of photo to be processed is obtained, attribute information includes shooting time and the shooting of photo
At least one of place information；
In step S22, photo to be processed is grouped in advance according to attribute information；
In step S23, similarity calculation is carried out between the photo to be processed in pre- grouping；
In step s 24, similar photo to be processed in pre- grouping is divided into according to the similarity being calculated same
Group obtains the grouping to photo to be processed.
It, can be with by being grouped according to photo property information and photo similarity to photo to be processed in the present embodiment
The photo shot under Same Scene is accurately picked out, to the photo shot under Same Scene, is adopted according to photographic quality grade
It is reduced it in this way, being saved the memory space of terminal or server with different storage modes and stores pressure.Meanwhile it is quasi- for user
The preferable photo of shooting quality really is filtered out, is enabled and is shot preferable photo and accurately completely save.
In another embodiment, can by the exchangeable image file of photo (Exchangeable Image File,
Abbreviation exif) extract user grouping photographic intelligence.Photographic intelligence is obtained in step S11, comprising:
The exif of photo to be processed is obtained, the photo exclusively for digital camera is contained in exif and the metadata that customizes,
Include at least the information of following a few class record digital photographs:
Shooting time, shooting equipment (fuselage, camera lens, flash lamp etc.), acquisition parameters (shutter speed, aperture F value, ISO speed
Degree, focal length, metering mode etc.), Image Processing parameter (sharpening, contrast, saturation degree, white balance etc.), iamge description and copyright
Information, shooting location (GPS positioning data etc.), thumbnail etc..
At least one of shooting time and the shooting location of photo to be processed information is extracted from exif.
In another embodiment, it in step S12, is compareed only on the basis of the shooting time of photo to be processed or shooting location
Piece is grouped, and can also be grouped according to shooting time and shooting location to photo to be processed.When below to according to shooting
Between and shooting location to photo to be processed grouping be illustrated.
For example, user may be selected to be photo on the same day by shooting time, it is grouped according to shooting location.
The photo that shooting time is on October 1st, 2015 is obtained, these photos are respectively provided with three shooting locations: the Forbidden City,
The Tian'anmen Square and front door.
Three groups can be divided into according to shooting time and these photos of shooting location:
First group: 2,015 1, on October, the Forbidden City；
Second group: 2,015 1, on October, the Tian'anmen Square；
Third group: on October 1st, 2015, front door.
It, can be accurately to photo by according at least one information in shooting time and shooting location in the present embodiment
It is grouped, so that the subsequent division to similar photo group is more acurrate, and effectively reduces the photo for needing to calculate similarity
Quantity saves the processing capacity of terminal or server.
In another embodiment, the photo in every group is divided into similar photo group according to similarity by step S13.It can benefit
Similarity mutual in this group of photo is calculated with the technology of similar diagram search comparison, and similarity is selected to be greater than or equal to 95%
Photo as similar photo group.
For example, by similarity calculation, the similarity between photo E001-E010 is higher than in above-mentioned second group of photo
95%, then can determine that this ten photos are the photo that shoots under Same Scene, i.e., be all to the photo of same building object shooting or
It is the photo etc. shot to same people in same place.
In the present embodiment, by the similar photo group of division, the photo shot under Same Scene can be accurately found out, so as to
It is subsequent that accurately these photos are screened.
In another embodiment, in step S14, quality judging is carried out to the photo in each similar photo group, with right
The photo of different quality is stored using different storage modes.
Fig. 3 is a kind of flow chart of the photo processing method shown according to another exemplary embodiment, as shown in figure 3, right
Every group of photo to be processed carries out quality testing, obtains the credit rating of every group of photo to be processed, comprising:
In step S31, the mass parameter of each photo to be processed in every group is detected, mass parameter includes following at least one
Item parameter: clarity, color saturation and face；
In step s 32, the credit rating of each photo to be processed in every group is determined according to mass parameter.
Fig. 4 is a kind of flow chart of the photo processing method shown according to another exemplary embodiment, as shown in figure 4, working as
When order parameter includes face parameter, step S32 includes:
Whether in step S41, detecting in photo to be processed includes face；
In step S42, when in photo including face, determines that the credit rating of photo to be processed is higher than and do not include face
Photo to be processed credit rating.
Fig. 5 is a kind of flow chart of the photo processing method shown according to another exemplary embodiment, as shown in figure 5, working as
When including face in photo, step S32 includes:
In step s 51, the image information of facial image in photo to be processed is obtained, image information includes following at least one
Information: position of the facial image in photo, facial image proportion and clarity of facial image in photo；
In step S52, the credit rating of photo to be processed is determined according to the image information of facial image, wherein face
Image is the credit rating of predeterminated position higher than position of the facial image in photo to be processed in the position in photo to be processed
It is not the photo of predeterminated position；Facial image proportion in photo to be processed is higher, and the credit rating of photo to be processed is got over
It is high；The clarity of facial image is higher, and the credit rating of photo to be processed is higher.
The acquisition modes to the mass parameter of photo and the influence to credit rating are specifically described below.
One, clarity
The clarity of photo can adopt greyscale transformation function, gradient function, image grayscale entropy function, frequency domain class function, statistics
The Image Definitions such as mathematic(al) function are calculated.The shade of gray value of each photo is calculated for example, by using gradient function,
The bigger photo of gradient value, clarity are higher.
The higher photo of clarity, quality are higher.
Two, color saturation
The color saturation of photo refers to the bright-coloured degree of photographic quality.The more higher photo of color saturation and color
More bright-coloured photographic quality higher grade.
Color saturation depends on the ratio of ingredient containing color and colour killing ingredient (grey) in the color.Ingredient containing color is bigger, satisfies
It is bigger with spending；Colour killing ingredient is bigger, and saturation degree is smaller.
The color of photo can be determined according to the value of S (saturation degree) parameter in HSV the or HSL color attribute parameter of photo
Color saturation degree.Wherein, HSL, that is, form and aspect, saturation degree, brightness (Hue, Saturation, Lightness).HSV, that is, form and aspect, saturation
Degree, lightness (Hue, Saturation, Value).
Alternatively, can also determine the color saturation of photo, Ji Congzhao according to the histogram of the RGB color of photo
Ratio shared by each color is obtained in the histogram of piece, the color number that proportion is greater than preset ratio value is more, explanation
The color saturation of the photo is bigger, and photographic quality is more bright-coloured.
Three, face
Facial image in photo is identified by face recognition technology.If in photo including face, it is believed that the photo
Credit rating is higher than the photo not comprising face.
For the multiple pictures comprising face, the facial image recognized can also be further analyzed, be obtained
The image information of facial image, to determine the quality of these photos.
Photographic quality grade can be determined according to position of the face in photo, as face is located at the photograph in photo middle position
Tablet quality is higher ranked.
Ratio-dependent photographic quality grade can also be accounted for according to face is more in photo, for example, facial image is in photo
Proportion is higher, credit rating is higher or facial image in photo proportion within a preset range, such as 30%~
90%, credit rating is relatively high.
The clarity of facial image can also be detected, the credit rating that the clarity of facial image is higher is higher.
Mass parameter is not limited to above-mentioned three kinds of parameters, and photographic quality grade can also be determined according to other factors.Such as, feel
Luminosity, exposure, contrast, color range, color curve etc..The piece identity of face in photo, root can also further be analyzed
Photographic quality grade is determined according to piece identity.If including household, friend, colleague etc. in photo, photographic quality grade is higher than
Photo including stranger's face.
It can be using above at least one parameter to photo to the judgement of photographic quality grade.If using multiple parameters pair
Photographic quality grade is evaluated, then can the weight different to each parameter setting according to actual needs, using weighting algorithm
Credit rating is calculated, by quantifying to credit rating, photo is located accordingly according to credit rating convenient for subsequent
Reason.
The determination of credit rating is illustrated by taking ten photos of above-mentioned similar photo group E001-E010 as an example below.
For example, the mass parameter of above-mentioned similar photo group E001-E010 is as shown in table 1 below,
Table 1
The corresponding weight of each mass parameter is as shown in table 2 below,
Table 2
The mass value for the photo that E001-E010 can be calculated according to table 1, table 2 is as shown in table 3 below,
Table 3
| Photo | Mass value |
| E001 | 40 |
| E002 | 33.2 |
| E003 | 38.7 |
| E004 | 68.7 |
| E005 | 81.2 |
| E006 | 72.7 |
| E007 | 87.45 |
| E008 | 66.55 |
| E009 | 68.45 |
| E010 | 36 |
According to table 3 as can be seen that the mass value of this several photos of photo E007, E005, E006, E004, E009, E008 is equal
It is relatively high more than 60%.
For example, can set mass value be more than 60% credit rating as A；Credit rating of the mass value lower than 60% is B.
To sum up, can determine credit rating according to a variety of mass parameters, so as to it is subsequent can be accurately according to credit rating pair
Photo is handled.
In another embodiment, according to the difference of credit rating, different storage modes can be used to photo, it can be with
Using following at least one mode:
(1) according to the corresponding default compression ratio of credit rating to being stored after picture compression
For example, using 80% pressure for photo E007, E005, E006, E004, E009 and E008 that credit rating is A
Contracting ratio is compressed, and the photo E001-E003 and E010 that credit rating is B are compressed using 25% compression ratio.
Alternatively, photo is divided into three grades by mass value: the highest photo E007 of mass value is credit rating A,
E005, E006, E004, E009 and E008 credit rating are B, E001-E003 and E010 credit rating is C.
The photo that credit rating is A is compressed using 100% compression ratio, guarantee photographic quality is carried out, for matter
Photo E005, E006, E004, E009 and E008 of amount grade B is compressed using 50% compression ratio, the photograph of credit rating C
Piece E001-E003 and E010 are compressed using 25% compression ratio.
(2) photo is deleted or stored according to credit rating
For example, photo E007, E005, E006, E004, E009 and E008 that only storage credit rating is A, delete quality etc.
Grade is the photo E001-E003 and E010 of B.
(3) photo is stored in the corresponding storage location of credit rating
Photo E007, E005, E006, E004, E009 and E008 that credit rating is A are stored in terminal, credit rating
Server end is stored in for B photo E001-E003 and E010.
Alternatively, three kinds of modes can be combined: photo being divided into three grades by mass value: the highest photo of mass value
E007 is credit rating A, and E005, E006, E004, E009 and E008 credit rating are B, E001-E003 and E010 credit rating
For C.
In terminal, photo E007, E005, E006, E004, E009 and E008 that credit rating is A, B are stored, quality is deleted
Grade is the photo E001-E003 and E010 of C.Meanwhile to credit rating be A photo E007 using 100% compression ratio into
Row compression, carries out guarantee photographic quality, and photo E005, E006, E004, E009 and E008 that credit rating is B are used
50% compression ratio is compressed.
After server compresses the photo E001-E003 and E010 that credit rating is C using 25% compression ratio
Storage.
In the present embodiment, according to credit rating to photo use different storage modes, can effectively save terminal or
The memory space of server reduces it and stores pressure.Meanwhile the preferable photo of shooting quality is accurately filtered out for user, make
Preferable photo, which must be shot, accurately completely to be saved.
Following is embodiment of the present disclosure, can be used for executing embodiments of the present disclosure.
Fig. 6 is a kind of block diagram of picture processing device shown according to an exemplary embodiment, which can be by soft
Part, hardware or both are implemented in combination with as some or all of of electronic equipment.As shown in fig. 6, the picture processing device
Include:
Grouping module 61, for being grouped to photo to be processed by preset rules；
Detection module 62 obtains every group of photo to be processed for carrying out quality testing to every group of photo to be processed
Credit rating；
Memory module 63, for being stored according to the credit rating to the photo to be processed.
In the present embodiment, grouping module 61 is grouped photo, and detection module 62 carries out matter to every group of photo to be processed
Amount detection, obtains the credit rating of every group of photo to be processed, and memory module 65 is used according to photographic quality grade reference substance
Different storage modes are stored.In this way, saving the memory space of terminal or server, reduces it and store pressure.Meanwhile being
User accurately filters out the preferable photo of shooting quality, enables and shoots preferable photo and accurately completely save.
Fig. 7 is the block diagram of grouping module shown according to an exemplary embodiment, as shown in fig. 7, grouping module 61 includes:
Acquisition submodule 71, for obtaining the attribute information of photo to be processed, the attribute information includes the shooting of photo
At least one of time and shooting location information；
First grouping submodule 72, for being grouped in advance according to the attribute information to the photo to be processed；
Computational submodule 73, for carrying out similarity calculation between the photo to be processed in the pre- grouping；
Second packet submodule 74, for according to the similarity that is calculated by photograph to be processed similar in the pre- grouping
Piece is divided into same group, obtains the grouping to the photo to be processed.
It, can be with by being grouped according to photo property information and photo similarity to photo to be processed in the present embodiment
The photo shot under Same Scene is accurately picked out, to the photo shot under Same Scene, is adopted according to photographic quality grade
It is reduced it in this way, being saved the memory space of terminal or server with different storage modes and stores pressure.Meanwhile it is quasi- for user
The preferable photo of shooting quality really is filtered out, is enabled and is shot preferable photo and accurately completely save.
In another embodiment, can by the exchangeable image file of photo (Exchangeable Image File,
Abbreviation exif) extract user grouping photographic intelligence.Acquisition submodule 71 is configured as obtaining the commutative figure of photo to be processed
As file；At least one of shooting time and the shooting location of photo information is extracted from exchangeable image file.
The metadata for containing the photo exclusively for digital camera in the exif that acquisition submodule 71 obtains and customizing, at least
Contain the information of following a few class record digital photographs:
Shooting time, shooting equipment (fuselage, camera lens, flash lamp etc.), acquisition parameters (shutter speed, aperture F value, ISO speed
Degree, focal length, metering mode etc.), Image Processing parameter (sharpening, contrast, saturation degree, white balance etc.), iamge description and copyright
Information, shooting location (GPS positioning data etc.), thumbnail etc..
In another embodiment, grouping module 61 carries out photo only on the basis of the shooting time of photo or shooting location
Grouping, can also be grouped photo according to shooting time and shooting location.Below to according to shooting time and shooting location
Photo grouping is illustrated.
For example, user may be selected to be photo on the same day by shooting time, it is grouped according to shooting location.
The photo that shooting time is on October 1st, 2015 is obtained, these photos are respectively provided with three shooting locations: the Forbidden City,
The Tian'anmen Square and front door.
Three groups can be divided into according to shooting time and these photos of shooting location:
First group: 2,015 1, on October, the Forbidden City；
Second group: 2,015 1, on October, the Tian'anmen Square；
Third group: on October 1st, 2015, front door.
It, can be accurately to photo by according at least one information in shooting time and shooting location in the present embodiment
It is grouped, so that the subsequent division to similar photo group is more acurrate, and effectively reduces the photo for needing to calculate similarity
Quantity saves the processing capacity of terminal or server.
In another embodiment, the photo in every group is divided into similar photo according to similarity by second packet submodule 74
Group.The technology that can use similar diagram search comparison calculates similarity mutual in this group of photo, and similarity is selected to be greater than
Or equal to 95% photo as similar photo group.
For example, by similarity calculation, the similarity between photo E001-E010 is higher than in above-mentioned second group of photo
95%, then can determine that this ten photos are the photo that shoots under Same Scene, i.e., be all to the photo of same building object shooting or
It is the photo etc. shot to same people in same place.
In the present embodiment, by the similar photo group of division, the photo shot under Same Scene can be accurately found out, so as to
It is subsequent that accurately these photos are screened.
Fig. 8 a is the block diagram of detection module shown according to an exemplary embodiment, as shown in Figure 8 a, optionally, detects mould
Block 62 includes:
First detection sub-module 81 is configured as detecting the mass parameter of each photo to be processed in every group, mass parameter
Including at least one of following parameter: clarity, color saturation and face；
It determines submodule 82, is configured as determining the quality etc. of each photo to be processed in every group according to the mass parameter
Grade.
Fig. 8 b is the block diagram of the detection module shown according to another exemplary embodiment, as shown in Figure 8 b, optionally, detection
Module 62 includes:
Second detection sub-module 83, for detecting the photo to be processed when the mass parameter includes face parameter
In whether include face；
The determining submodule 82, for determining the photo to be processed when in the photo to be processed including face
Photo grade be higher than not comprising face photo to be processed photo grade.
Fig. 8 c is the block diagram of the detection module shown according to another exemplary embodiment, as shown in Figure 8 c, optionally, detection
Module 62 further include:
Acquisition submodule 84, for obtaining the image information of facial image in the photo to be processed, described image information
Including at least one of following information: position of the facial image in the photo to be processed, the facial image are described
Proportion and the clarity of the facial image in photo to be processed；
The determining submodule 82, for determining the matter of the photo to be processed according to the image information of the facial image
Measure grade；Wherein, position of the facial image in the photo to be processed is the credit rating of predeterminated position higher than described
Position of the facial image in the photo to be processed is not the photo of predeterminated position；The facial image is in the photograph to be processed
Proportion is higher in piece, and the credit rating of the photo to be processed is higher；The clarity of the facial image is higher, it is described to
The credit rating for handling photo is higher.
The acquisition modes to the mass parameter of photo and the influence to photographic quality grade are specifically described below.
One, clarity
The clarity of photo can adopt greyscale transformation function, gradient function, image grayscale entropy function, frequency domain class function, statistics
The Image Definitions such as mathematic(al) function are calculated.The shade of gray value of each photo is calculated for example, by using gradient function,
The bigger photo of gradient value, clarity are higher.
The higher photo of clarity, quality are higher.
Two, color saturation
The color saturation of photo refers to the bright-coloured degree of photographic quality.The more higher photo of color saturation and color
More bright-coloured photographic quality higher grade.
Color saturation depends on the ratio of ingredient containing color and colour killing ingredient (grey) in the color.Ingredient containing color is bigger, satisfies
It is bigger with spending；Colour killing ingredient is bigger, and saturation degree is smaller.
The color of photo can be determined according to the value of S (saturation degree) parameter in HSV the or HSL color attribute parameter of photo
Color saturation degree.Wherein, HSL, that is, form and aspect, saturation degree, brightness (Hue, Saturation, Lightness).HSV, that is, form and aspect, saturation
Degree, lightness (Hue, Saturation, Value).
Alternatively, can also determine the color saturation of photo, Ji Congzhao according to the histogram of the RGB color of photo
Ratio shared by each color is obtained in the histogram of piece, the color number that proportion is greater than preset ratio value is more, explanation
The color saturation of the photo is bigger, and photographic quality is more bright-coloured.
Three, face
Facial image in photo is identified by face recognition technology.If in photo including face, it is believed that the photo
Credit rating is higher than the photo not comprising face.
For the multiple pictures comprising face, the facial image recognized can also be further analyzed, be obtained
The image information of facial image, to determine the quality of these photos.
Photographic quality grade can be determined according to position of the face in photo, as face is located at the photograph in photo middle position
Tablet quality is higher ranked.
Ratio-dependent photographic quality grade can also be accounted for according to face is more in photo, for example, facial image is in photo
Proportion is higher, photographic quality higher grade or facial image in photo proportion within a preset range, such as 30%
~90%, photographic quality grade is relatively high.
The clarity of facial image can also be detected, the higher photographic quality better grade of the clarity of facial image.
Mass parameter is not limited to above-mentioned three kinds of parameters, and photographic quality grade can also be determined according to other factors.Such as, feel
Luminosity, exposure, contrast, color range, color curve etc..The piece identity of face in photo, root can also further be analyzed
Photographic quality grade is determined according to piece identity.If including household, friend, colleague etc. in photo, photographic quality grade is higher than
Photo including stranger's face.
It can be using above at least one parameter to photo to the judgement of photographic quality grade.If using multiple parameters pair
Photographic quality grade is evaluated, then can the weight different to each parameter setting according to actual needs, using weighting algorithm
Credit rating is calculated, by quantifying to credit rating, photo is located accordingly according to credit rating convenient for subsequent
Reason.
The determination of credit rating is illustrated by taking ten photos of above-mentioned similar photo group E001-E010 as an example below.
The mass parameter of above-mentioned similar photo group E001-E010 is as listed in Table 1, the corresponding weight of each mass parameter table as above
Shown in 2, the photographic quality value of E001-E010 can be calculated according to table 1, table 2.Shown in table 3 as above, it can be seen that according to table 3
The mass value of this several photos of photo E007, E005, E006, E004, E009, E008 is relatively high more than 60%.
For example, can set mass value be more than 60% credit rating as A；Credit rating of the mass value lower than 60% is B.
To sum up, can determine credit rating according to a variety of mass parameters, so as to it is subsequent can be accurately according to credit rating pair
Photo is handled.
Fig. 9 is the block diagram of memory module shown according to an exemplary embodiment, as shown in figure 9, optionally, memory module
63 include at least one following submodule:
First sub-module stored 91 is configured as according to the corresponding default compression ratio of credit rating to picture compression to be processed
After stored.
For example, the first sub-module stored 91 for credit rating more than or equal to 60% photo E007, E005, E006,
E004, E009 and E008 are compressed using 80% compression ratio, photo E001-E003 of the photographic quality grade less than 60% and
E010 is compressed using 25% compression ratio.
Alternatively, 91 credit rating of the first sub-module stored is photo E007, E005, E006, E004, E009 and E008 of A
It is compressed using 80% compression ratio, the photo E001-E003 and E010 that credit rating is B are carried out using 25% compression ratio
Compression.
Alternatively, photo is divided into three grades by mass value: the highest photo E007 of mass value is credit rating A,
E005, E006, E004, E009 and E008 credit rating are B, E001-E003 and E010 credit rating is C.
The photo that credit rating is A is compressed using 100% compression ratio, guarantee photographic quality is carried out, for matter
Photo E005, E006, E004, E009 and E008 of amount grade B is compressed using 50% compression ratio, the photograph of credit rating C
Piece E001-E003 and E010 are compressed using 25% compression ratio.
Second sub-module stored 92 is configured as deleting or storing photo to be processed according to credit rating.
For example, the second sub-module stored 92 only stores photo E007, E005, E006, E004, E009 that credit rating is A
And E008, delete the photo E001-E003 and E010 that credit rating is B.
Third sub-module stored 93 is configured as photo to be processed being stored in the corresponding storage location of credit rating.
Third sub-module stored 93 stores photo E007, E005, E006, E004, E009 and E008 that credit rating is A
In terminal, credit rating is that B photo E001-E003 and E010 is stored in server end.
Furthermore it is possible to which three modules are combined:
In terminal,
Photo is divided into three grades by mass value: the highest photo E007 of mass value be credit rating A, E005,
E006, E004, E009 and E008 credit rating are B, E001-E003 and E010 credit rating is C.
In terminal, photo E007, E005, E006, E004, E009 and E008 that credit rating is A, B are stored, quality is deleted
Grade is the photo E001-E003 and E010 of C.Meanwhile to credit rating be A photo E007 using 100% compression ratio into
Row compression, carries out guarantee photographic quality, and photo E005, E006, E004, E009 and E008 that credit rating is B are used
50% compression ratio is compressed.
After server compresses the photo E001-E003 and E010 that credit rating is C using 25% compression ratio
Storage.
In the present embodiment, according to credit rating to photo use different storage modes, can effectively save terminal or
The memory space of server reduces it and stores pressure.Meanwhile the preferable photo of shooting quality is accurately filtered out for user, make
Preferable photo, which must be shot, accurately completely to be saved.
According to the third aspect of an embodiment of the present disclosure, a kind of picture processing device is provided, comprising:
Processor；
Memory for storage processor executable instruction；
Wherein, the processor is configured to:
Photo to be processed is grouped by preset rules；
Quality testing is carried out to every group of photo to be processed, obtains the credit rating of every group of photo to be processed；
The photo to be processed is stored according to the credit rating.
Figure 10 is a kind of block diagram of device for photo processing shown according to an exemplary embodiment, which is applicable in
In terminal device.For example, device 1700 can be video camera, sound pick-up outfit, mobile phone, computer, digital broadcast terminal disappears
Cease transceiver, game console, tablet device, Medical Devices, body-building equipment, personal digital assistant etc..
Device 1700 may include following one or more components: processing component 1702, memory 1704, power supply module
1706, multimedia component 1708, audio component 1710, the interface 1712 of input/output (I/O), sensor module 1714, and
Communication component 1716.
The integrated operation of the usual control device 1700 of processing component 1702, such as with display, telephone call, data communication,
Camera operation and record operate associated operation.Processing element 1702 may include one or more processors 1720 to execute
Instruction, to perform all or part of the steps of the methods described above.In addition, processing component 1702 may include one or more moulds
Block, convenient for the interaction between processing component 1702 and other assemblies.For example, processing component 1702 may include multi-media module,
To facilitate the interaction between multimedia component 1708 and processing component 1702.
Memory 1704 is configured as storing various types of data to support the operation in equipment 1700.These data
Example includes the instruction of any application or method for operating on device 1700, contact data, telephone book data,
Message, picture, video etc..Memory 1704 can by any kind of volatibility or non-volatile memory device or they
Combination is realized, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), it is erasable can
Program read-only memory (EPROM), programmable read only memory (PROM), read-only memory (ROM), magnetic memory, flash memory
Reservoir, disk or CD.
Power supply module 1706 provides electric power for the various assemblies of device 1700.Power supply module 1706 may include power management
System, one or more power supplys and other with for device 1700 generate, manage, and distribute the associated component of electric power.
Multimedia component 1708 includes the screen of one output interface of offer between described device 1700 and user.?
In some embodiments, screen may include liquid crystal display (LCD) and touch panel (TP).If screen includes touch panel,
Screen may be implemented as touch screen, to receive input signal from the user.Touch panel includes that one or more touch passes
Sensor is to sense the gesture on touch, slide, and touch panel.The touch sensor can not only sense touch or sliding is dynamic
The boundary of work, but also detect duration and pressure associated with the touch or slide operation.In some embodiments, more
Media component 1708 includes a front camera and/or rear camera.When equipment 1700 is in operation mode, as shot mould
When formula or video mode, front camera and/or rear camera can receive external multi-medium data.Each preposition camera shooting
Head and rear camera can be a fixed optical lens system or have focusing and optical zoom capabilities.
Audio component 1710 is configured as output and/or input audio signal.For example, audio component 1710 includes a wheat
Gram wind (MIC), when device 1700 is in operation mode, when such as call mode, recording mode, and voice recognition mode, microphone quilt
It is configured to receive external audio signal.The received audio signal can be further stored in memory 1704 or via communication
Component 1716 is sent.In some embodiments, audio component 1710 further includes a loudspeaker, is used for output audio signal.
I/O interface 1712 provides interface, above-mentioned peripheral interface module between processing component 1702 and peripheral interface module
It can be keyboard, click wheel, button etc..These buttons may include, but are not limited to: home button, volume button, start button and
Locking press button.
Sensor module 1714 includes one or more sensors, and the state for providing various aspects for device 1700 is commented
Estimate.For example, sensor module 1714 can detecte the state that opens/closes of equipment 1700, the relative positioning of component, such as institute
The display and keypad that component is device 1700 are stated, sensor module 1714 can be with detection device 1700 or device 1,700 1
The position change of a component, the existence or non-existence that user contacts with device 1700,1700 orientation of device or acceleration/deceleration and dress
Set 1700 temperature change.Sensor module 1714 may include proximity sensor, be configured in not any physics
It is detected the presence of nearby objects when contact.Sensor module 1714 can also include optical sensor, as CMOS or ccd image are sensed
Device, for being used in imaging applications.In some embodiments, which can also include acceleration sensing
Device, gyro sensor, Magnetic Sensor, pressure sensor or temperature sensor.
Communication component 1716 is configured to facilitate the communication of wired or wireless way between device 1700 and other equipment.Dress
The wireless network based on communication standard, such as WiFi can be accessed by setting 1700,2G or 3G or their combination.It is exemplary at one
In embodiment, communication component 1716 receives broadcast singal or broadcast correlation from external broadcasting management system via broadcast channel
Information.In one exemplary embodiment, the communication component 1716 further includes near-field communication (NFC) module, to promote short distance
Communication.For example, radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra wide band can be based in NFC module
(UWB) technology, bluetooth (BT) technology and other technologies are realized.
In the exemplary embodiment, device 1700 can be by one or more application specific integrated circuit (ASIC), number
Signal processor (DSP), digital signal processing appts (DSPD), programmable logic device (PLD), field programmable gate array
(FPGA), controller, microcontroller, microprocessor or other electronic components are realized, for executing the above method.
In the exemplary embodiment, a kind of non-transitorycomputer readable storage medium including instruction, example are additionally provided
It such as include the memory 1704 of instruction, above-metioned instruction can be executed by the processor 1720 of device 1700 to complete the above method.Example
Such as, the non-transitorycomputer readable storage medium can be ROM, random access memory (RAM), CD-ROM, tape, soft
Disk and optical data storage devices etc..
Figure 11 is a kind of block diagram of device for photo processing shown according to an exemplary embodiment.For example, device
1900 may be provided as a server.Device 1900 includes processing component 1922, further comprises one or more processing
Device and memory resource represented by a memory 1932, can be by the instruction of the execution of processing component 1922, example for storing
Such as application program.The application program stored in memory 1932 may include it is one or more each correspond to one group
The module of instruction.In addition, processing component 1922 is configured as executing instruction, to execute the above method.
Device 1900 can also include that a power supply module 1926 be configured as the power management of executive device 1900, and one
Wired or wireless network interface 1950 is configured as device 1900 being connected to network and input and output (I/O) interface
1958.Device 1900 can be operated based on the operating system for being stored in memory 1932, such as Windows ServerTM, Mac
OS XTM, UnixTM, LinuxTM, FreeBSDTM or similar.
A kind of non-transitorycomputer readable storage medium, when the instruction in the storage medium is by device 1700 or device
When 1900 processor executes, so that the method that device 1700 or device 1900 are able to carry out above-mentioned photo processing, the method
Include:
Photo to be processed is grouped by preset rules；
Quality testing is carried out to every group of photo to be processed, obtains the credit rating of every group of photo to be processed；
The photo to be processed is stored according to the credit rating.
It is optionally, described that photo to be processed is grouped by preset rules, comprising:
Obtain the attribute information of photo to be processed, the attribute information include in the shooting time and shooting location of photo extremely
One item missing information；
The photo to be processed is grouped in advance according to the attribute information；
Similarity calculation is carried out between the photo to be processed in the pre- grouping；
Photo to be processed similar in the pre- grouping is divided into same group according to the similarity being calculated, is obtained pair
The grouping of the photo to be processed.
Optionally, described that quality testing is carried out to every group of photo to be processed, obtain the quality of every group of photo to be processed
Grade, comprising:
The mass parameter of each photo to be processed in every group is detected, the mass parameter includes at least one of following parameter:
Clarity, color saturation and face；
The credit rating of each photo to be processed in every group is determined according to the mass parameter.
It is optionally, described that quality testing is carried out to every group of photo to be processed when the mass parameter includes face parameter,
Obtain the credit rating of every group of photo to be processed, comprising:
Whether detect in the photo to be processed includes face；
When in the photo to be processed including face, determines that the credit rating of the photo to be processed is higher than and do not include people
The credit rating of the photo to be processed of face.
Optionally, described that quality testing is carried out to every group of photo to be processed when in the photo including face, obtain institute
State the credit rating of every group of photo to be processed, further includes:
The image information of facial image in the photo to be processed is obtained, described image information includes at least one of following letter
Breath: the facial image is in the position in the photo to be processed, facial image institute's accounting in the photo to be processed
The clarity of example and the facial image；
The credit rating of the photo to be processed is determined according to the image information of the facial image；Wherein, the face
Position of the image in the photo to be processed is that the credit rating of predeterminated position is higher than the facial image described to be processed
Position in photo is not the photo of predeterminated position；Facial image proportion in the photo to be processed is higher, institute
The credit rating for stating photo to be processed is higher；The clarity of the facial image is higher, the credit rating of the photo to be processed
It is higher.
Optionally, at least one of described that the photo to be processed is stored according to the credit rating including following
Operation:
According to the corresponding default compression ratio of the credit rating to being stored after the picture compression to be processed；
The photo to be processed is deleted or stored according to the credit rating；
The photo to be processed is stored in the corresponding storage location of the credit rating.
Optionally, the attribute information for obtaining photo to be processed, comprising:
Obtain the exchangeable image file of the photo to be processed；
At least one from the shooting time and shooting location for extracting the photo to be processed in the exchangeable image file
Item information.
Those skilled in the art will readily occur to its of the disclosure after considering specification and practicing disclosure disclosed herein
Its embodiment.This application is intended to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes or
Person's adaptive change follows the general principles of this disclosure and including the undocumented common knowledge in the art of the disclosure
Or conventional techniques.The description and examples are only to be considered as illustrative, and the true scope and spirit of the disclosure are by following
Claim is pointed out.
It should be understood that the present disclosure is not limited to the precise structures that have been described above and shown in the drawings, and
And various modifications and changes may be made without departing from the scope thereof.The scope of the present disclosure is only limited by the accompanying claims.
Claims (12)
1. a kind of photo processing method characterized by comprising
Photo to be processed is grouped by preset rules；
Quality testing is carried out to every group of photo to be processed, obtains the credit rating of every group of photo to be processed；
The photo to be processed is stored according to the credit rating；
At least one of described that the photo to be processed is stored according to the credit rating including following operation:
According to the corresponding default compression ratio of the credit rating to being stored after the picture compression to be processed；
The photo to be processed is deleted or stored according to the credit rating；
The photo to be processed is stored in the corresponding storage location of the credit rating；
The mass parameter includes at least one of following parameter: clarity, color saturation and face；
It is described that quality testing is carried out to every group of photo to be processed when in the photo including face, it obtains described every group and waits locating
Manage the credit rating of photo, further includes:
The image information of facial image in the photo to be processed is obtained, described image information includes at least one of following information:
The facial image in the photo to be processed position, the facial image in the photo to be processed proportion and
The clarity of the facial image；
The credit rating of the photo to be processed is determined according to the image information of the facial image；Wherein, the facial image
Position in the photo to be processed is that the credit rating of predeterminated position is higher than the facial image in the photo to be processed
In position be not predeterminated position photo；Facial image proportion in the photo to be processed is higher, it is described to
The credit rating for handling photo is higher；The clarity of the facial image is higher, and the credit rating of the photo to be processed is higher.
2. the method according to claim 1, wherein described be grouped photo to be processed by preset rules,
Include:
The attribute information of photo to be processed is obtained, the attribute information includes at least one in the shooting time and shooting location of photo
Item information；
The photo to be processed is grouped in advance according to the attribute information；
Similarity calculation is carried out between the photo to be processed in the pre- grouping；
Photo to be processed similar in the pre- grouping is divided into same group according to the similarity being calculated, is obtained to described
The grouping of photo to be processed.
3. being obtained the method according to claim 1, wherein described carry out quality testing to every group of photo to be processed
To the credit rating of every group of photo to be processed, comprising:
Detect the mass parameter of each photo to be processed in every group；
The credit rating of each photo to be processed in every group is determined according to the mass parameter.
4. described right according to the method described in claim 3, it is characterized in that, when the mass parameter includes face parameter
Every group of photo to be processed carries out quality testing, obtains the credit rating of every group of photo to be processed, comprising:
Whether detect in the photo to be processed includes face；
When in the photo to be processed including face, determine that the credit rating of the photo to be processed is higher than not comprising face
The credit rating of photo to be processed.
5. according to the method described in claim 2, it is characterized in that, the attribute information for obtaining photo to be processed, comprising:
Obtain the exchangeable image file of the photo to be processed；
At least one of shooting time and shooting location of the photo to be processed letter is extracted from the exchangeable image file
Breath.
6. a kind of picture processing device characterized by comprising
Grouping module, for being grouped to photo to be processed by preset rules；
Detection module obtains the quality etc. of every group of photo to be processed for carrying out quality testing to every group of photo to be processed
Grade；
Memory module, for being stored according to the credit rating to the photo to be processed；
The memory module includes at least one following submodule:
First sub-module stored, for according to the corresponding default compression ratio of the credit rating to the picture compression to be processed after
It is stored；
Second sub-module stored, for deleting or storing the photo to be processed according to the credit rating；
Third sub-module stored, for the photo to be processed to be stored in the corresponding storage location of the credit rating；
The mass parameter includes at least one of following parameter: clarity, color saturation and face；
The detection module further include:
Acquisition submodule, for obtaining the image information of facial image in the photo to be processed, described image information include with
At least one of lower information: position of the facial image in the photo to be processed, the facial image are described to be processed
Proportion and the clarity of the facial image in photo；
Submodule is determined, for determining the credit rating of the photo to be processed according to the image information of the facial image；Its
In, position of the facial image in the photo to be processed is that the credit rating of predeterminated position exists higher than the facial image
Position in the photo to be processed is not the photo of predeterminated position；Facial image institute's accounting in the photo to be processed
Example is higher, and the credit rating of the photo to be processed is higher；The clarity of the facial image is higher, the photo to be processed
Credit rating is higher.
7. device according to claim 6, which is characterized in that the grouping module includes:
Acquisition submodule, for obtaining the attribute information of photo to be processed, the attribute information include photo shooting time and
At least one of shooting location information；
First grouping submodule, for being grouped in advance according to the attribute information to the photo to be processed；
Computational submodule, for carrying out similarity calculation between the photo to be processed in the pre- grouping；
Second packet submodule, for being divided photo to be processed similar in the pre- grouping according to the similarity being calculated
It is same group, obtains the grouping to the photo to be processed.
8. device according to claim 6, which is characterized in that the detection module includes:
First detection sub-module, for detecting the mass parameter of each photo to be processed in every group；
Submodule is determined, for determining the credit rating of each photo to be processed in every group according to the mass parameter.
9. device according to claim 8, which is characterized in that the detection module further include:
Second detection sub-module, for when the mass parameter includes face parameter, detect in the photo to be processed whether
Including face；
The determining submodule, for determining the photo of the photo to be processed when in the photo to be processed including face
Grade is higher than the photo grade of the photo to be processed not comprising face.
10. device according to claim 7, which is characterized in that the acquisition submodule, for obtaining the photograph to be processed
The exchangeable image file of piece；The photo to be processed is extracted from the exchangeable image file that the acquisition submodule obtains
At least one of shooting time and shooting location information.
11. a kind of picture processing device characterized by comprising
Processor；
Memory for storage processor executable instruction；
Wherein, the processor is configured to:
Photo to be processed is grouped by preset rules；
Quality testing is carried out to every group of photo to be processed, obtains the credit rating of every group of photo to be processed；
The photo to be processed is stored according to the credit rating；
At least one of described that the photo to be processed is stored according to the credit rating including following operation:
According to the corresponding default compression ratio of the credit rating to being stored after the picture compression to be processed；
The photo to be processed is deleted or stored according to the credit rating；
The photo to be processed is stored in the corresponding storage location of the credit rating；
The mass parameter includes at least one of following parameter: clarity, color saturation and face；
It is described that quality testing is carried out to every group of photo to be processed when in the photo including face, it obtains described every group and waits locating
Manage the credit rating of photo, further includes:
The image information of facial image in the photo to be processed is obtained, described image information includes at least one of following information:
The facial image in the photo to be processed position, the facial image in the photo to be processed proportion and
The clarity of the facial image；
The credit rating of the photo to be processed is determined according to the image information of the facial image；Wherein, the facial image
Position in the photo to be processed is that the credit rating of predeterminated position is higher than the facial image in the photo to be processed
In position be not predeterminated position photo；Facial image proportion in the photo to be processed is higher, it is described to
The credit rating for handling photo is higher；The clarity of the facial image is higher, and the credit rating of the photo to be processed is higher.
12. a kind of non-transitorycomputer readable storage medium, is stored thereon with computer program, which is characterized in that the journey
The step of any one of claims 1 to 5 the method is realized when sequence is executed by processor.
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| CN107291781A (en) * | 2016-04-12 | 2017-10-24 | 中兴通讯股份有限公司 | A kind of image management method and device |
| CN106056138A (en) * | 2016-05-25 | 2016-10-26 | 努比亚技术有限公司 | Picture processing device and method |
| CN106155592A (en) * | 2016-07-26 | 2016-11-23 | 深圳天珑无线科技有限公司 | A kind of photo processing method and terminal |
| CN106339496A (en) * | 2016-08-31 | 2017-01-18 | 百度在线网络技术（北京）有限公司 | Method and device for clearing photos |
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