CN106778645A - A kind of image processing method and device - Google Patents
A kind of image processing method and device Download PDFInfo
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- CN106778645A CN106778645A CN201611210672.0A CN201611210672A CN106778645A CN 106778645 A CN106778645 A CN 106778645A CN 201611210672 A CN201611210672 A CN 201611210672A CN 106778645 A CN106778645 A CN 106778645A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
Abstract
A kind of image processing method and device are the embodiment of the invention provides, methods described includes：Obtain pending image；Face datection is carried out to the pending image, M facial image is obtained, the M is positive integer；The M facial image is screened, N facial image is obtained, the N is less than or equal to the integer of the M；The N facial image is uploaded onto the server.Intelligent upload image can be realized by the embodiment of the present invention.
Description
Technical field
The present invention relates to computer vision calculating field, and in particular in cluster computing system, a kind of image processing method
Method and device.
Background technology
With economic, society, the fast development of culture, growing day by day, more and more population from other places of impact at home and abroad power
City is flowed to, these populations increase while urbanization process is accelerated, also for city management brings bigger challenge, although,
The calculating analysis of video monitoring and the machine vision based on video provides technical support to urban safety, but, at present,
Camera is laid out in city and comes, and the function of each camera is more independent, when need search for certain personage when, it is necessary to
The video image that each camera shoots is checked frame by frame, in this way, can not preferably by whole section, or even whole city
Camera resource is fully utilized.In the prior art, at present, machine vision calculate relate generally to concentrate formula calculate in
The heart to data such as video images, it is necessary to carry out collecting treatment.If being uploaded in video monitoring system when deploying to ensure effective monitoring and control of illegal activities object, such as using regarding
Certain face in frequency image as deploy to ensure effective monitoring and control of illegal activities object when, it is necessary to artificially intercepted to the face, then, then after uploading interception
Facial image, in this way, during object is deployed to ensure effective monitoring and control of illegal activities in upload, it is impossible to intelligently upload image；And in the gatherer process of image,
To many quality evaluation and analysis that carry out of image, and it is also one from satisfactory high-quality picture source data is uploaded
Individual critically important one side, this is also that can not meet requirement in existing system, also without accomplishing intelligent upload
Image.
The content of the invention
The embodiment of the invention provides a kind of image processing method and device, can during object is deployed to ensure effective monitoring and control of illegal activities in upload,
Intelligently upload image.
Embodiment of the present invention first aspect provides a kind of image processing method, including：
Obtain pending image；
Face datection is carried out to the pending image, M facial image is obtained, the M is positive integer；
The M facial image is screened, N facial image is obtained, the N is whole less than or equal to the M
Number；
The N facial image is uploaded onto the server.
It is described to the M with reference to the embodiment of the present invention in a first aspect, in the first possible embodiment of first aspect
Facial image is opened to be screened, including：
The angle information of facial image i is obtained, the angle information is following at least one：Horizontally rotate angle, pitching
Angle and gradient, the facial image i are any facial image in the M facial image；
The angle information of the facial image i and predetermined angle information are compared, in the angle of the facial image i
When information is compared successfully with the predetermined angle information, retain the facial image i.
It is described to the M with reference to the embodiment of the present invention in a first aspect, in second possible embodiment of first aspect
Open facial image to be screened, obtain N facial image, including：
The image that human face region in the M facial images is not blocked is filtered out, K facial image is obtained, the K is
Positive integer；
Image quality evaluation is carried out to the K facial image, the K image quality evaluation values are obtained；
The image quality evaluation values more than predetermined threshold value are chosen from the K image quality evaluation values, obtains described N number of
Image quality evaluation values, obtain the corresponding N facial image of the N number of image quality evaluation values.
With reference to the first or second possible embodiment of embodiment of the present invention first aspect or first aspect, first
It is described that the N facial image is uploaded onto the server in the third possible embodiment of aspect, including：
The N facial image is compressed, the N first object facial image is obtained；
The N first object facial image and its corresponding attribute information are uploaded into the server.
With reference to the first or second possible embodiment of embodiment of the present invention first aspect or first aspect, first
In the third possible embodiment of aspect, the M facial images are screened described, obtain N facial image it
Afterwards, methods described also includes：
Image enhancement processing is carried out to the N facial image；
It is described that the N facial image uploads onto the server, including：
The N facial image after by image enhaucament is uploaded to the server.
Embodiment of the present invention second aspect provides a kind of image processing apparatus, including：
Acquiring unit, for obtaining pending image；
Detection unit, for carrying out Face datection to the pending image, obtains M facial image, and the M is just whole
Number；
Screening unit, for being screened to the M facial images, obtains N facial image, the N be less than or
Equal to the integer of the M；
Uploading unit, for the N facial image to be uploaded onto the server.
With reference to embodiment of the present invention second aspect, in the first possible embodiment of second aspect, the screening is single
Unit includes：
Acquisition module, the angle information for obtaining facial image i, the angle information is following at least one：Level
Rotational angle, the angle of pitch and gradient, the facial image i are any facial image in the M facial image；
Comparing module, for the angle information of the facial image i and predetermined angle information to be compared, in the people
When the angle information of face image i is compared successfully with the predetermined angle information, retain the facial image i.
With reference to embodiment of the present invention second aspect, in the first possible embodiment of second aspect, the screening is single
Unit includes：
Screening module, for filtering out the image that human face region in the M facial images is not blocked, obtains K people
Face image, the K is positive integer；
Evaluation module, for carrying out image quality evaluation to the K facial image, obtains the K picture quality and comments
Value；
Module is chosen, for choosing the image quality evaluation more than predetermined threshold value from the K image quality evaluation values
Value, obtains N number of image quality evaluation values, obtains the corresponding N facial image of the N number of image quality evaluation values.
With reference to the first or second possible embodiment of embodiment of the present invention second aspect or second aspect, second
In the third possible embodiment of aspect, the uploading unit includes：
Compression module, for the N facial image to be compressed, obtains the N first object facial image；
Uploading module, for the N first object facial image and its corresponding attribute information to be uploaded into the clothes
Business device.
With reference to the first or second possible embodiment of embodiment of the present invention second aspect or second aspect, second
In 4th kind of possible embodiment of aspect, described image processing unit also includes：
Processing unit, for being screened to the M facial image in the screening unit, obtains N facial image
Afterwards, image enhancement processing is carried out to the N facial image；
The uploading unit specifically for：
The N facial image after by image enhaucament is uploaded to the server.Implement the embodiment of the present invention, with such as
Lower beneficial effect：
As can be seen that by the embodiment of the present invention, obtaining pending image, Face datection is carried out to pending image, obtained
To M facial image, M is positive integer, and M facial image is screened, and obtains N facial image, and N is less than or equal to M
Integer, N facial images are uploaded onto the server, in this way, can realize intelligent uploading image.
Brief description of the drawings
Technical scheme in order to illustrate more clearly the embodiments of the present invention, below will be to that will make needed for embodiment description
Accompanying drawing is briefly described, it should be apparent that, drawings in the following description are some embodiments of the present invention, for ability
For the those of ordinary skill of domain, on the premise of not paying creative work, can also obtain other attached according to these accompanying drawings
Figure.
Fig. 1 is a kind of first embodiment schematic flow sheet of image processing method provided in an embodiment of the present invention；
Fig. 2 is a kind of second embodiment schematic flow sheet of image processing method provided in an embodiment of the present invention；
Fig. 3 a are a kind of first embodiment structural representations of image processing apparatus provided in an embodiment of the present invention；
Fig. 3 b are the structural representations of the screening unit of the image processing apparatus described by Fig. 3 a provided in an embodiment of the present invention
Figure；
Fig. 3 c are the another structures of the screening unit of the image processing apparatus described by Fig. 3 a provided in an embodiment of the present invention
Schematic diagram；
Fig. 3 d are the structural representations of the uploading unit of the image processing apparatus described by Fig. 3 a provided in an embodiment of the present invention
Figure；
Fig. 3 e are the another structural representations of the image processing apparatus described by Fig. 3 a provided in an embodiment of the present invention；
Fig. 4 is a kind of second embodiment structural representation of image processing apparatus provided in an embodiment of the present invention.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is a part of embodiment of the invention, rather than whole embodiments.Based on this hair
Embodiment in bright, the every other implementation that those of ordinary skill in the art are obtained under the premise of creative work is not made
Example, belongs to the scope of protection of the invention.
Term " first ", " second ", " the 3rd " in description and claims of this specification and the accompanying drawing and "
Four " it is etc. for distinguishing different objects, rather than for describing particular order.Additionally, term " comprising " and " having " and it
Any deformation, it is intended that covering non-exclusive is included.For example contain the process of series of steps or unit, method, be
System, product or equipment are not limited to the step of having listed or unit, but alternatively also include the step of not listing or list
Unit, or alternatively also include for these processes, method, product or other intrinsic steps of equipment or unit.
Referenced herein " embodiment " is it is meant that the special characteristic, structure or the characteristic that describe can be wrapped in conjunction with the embodiments
Containing at least one embodiment of the present invention.It is identical that each position in the description shows that the phrase might not each mean
Embodiment, nor the independent or alternative embodiment with other embodiments mutual exclusion.Those skilled in the art explicitly and
Implicitly understand, embodiment described herein can be combined with other embodiments.
Image processing apparatus described by the embodiment of the present invention can include smart mobile phone (such as Android phone, iOS mobile phones,
Windows Phone mobile phones etc.), panel computer, palm PC, notebook computer, mobile internet device (MID, Mobile
Internet Devices) or Wearable etc., above-mentioned is only citing, and non exhaustive, including but not limited to said apparatus.Example
Such as, when above-mentioned image processing apparatus are mobile phone, the application software of the application implementation embodiment of the present invention can be installed in mobile phone, in this way,
Image can be uploaded in mobile phone terminal, for example, Security Personnel is captured to someone, then it can taken pictures, its facial image is uploaded to
Server, the monitoring to the people can be completed by server.
It should be noted that the image processing apparatus in the embodiment of the present invention can be connected with multiple cameras, each shooting
Head is used equally to capture video image, and each camera can have a corresponding position mark, or, can have one with
Corresponding numbering.Under normal circumstances, camera may be provided at public place, for example, school, museum, crossroad, walking
Street, office building, garage, airport, hospital, subway station, station, bus platform, supermarket, hotel, public place of entertainment etc..Camera exists
After photographing video image, the video image can be saved in the memory of system where image processing apparatus.Can in memory
The multiple images that are stored with storehouse, each image library can include the different video image of same people, and certainly, each image library can also be used
The video image that video image or certain specified camera in one region of storage shoot.
Still optionally further, in the embodiment of the present invention, each frame video image that camera shoots corresponds to an attribute
Information, attribute information is following at least one：The shooting time of video image, the position of video image, the attribute of video image
Character features attribute in parameter (form, size, resolution ratio etc.), the numbering and video image of video image.Above-mentioned video figure
Character features attribute as in may include but be not limited only to：Personage's number, character positions, personage's angle in video image etc.
Deng.
Explanation is needed further exist for, the video image of each camera collection is usually dynamic human face image, thus, this
The angle information of facial image can be planned in inventive embodiments, above-mentioned angle information may include but be not limited only to：Water
Flat rotational angle, the angle of pitch or gradient.For example, definable dynamic human face view data two spacing of requirement are not less than 30 pictures
Element, it is proposed that more than 60 pixels.Horizontally rotate angle no more than ± 30 °, the angle of pitch no more than ± 20 °, inclination angle no more than ±
45°.Recommended levels rotational angle is no more than ± 15 ° no more than ± 15 °, the angle of pitch no more than ± 10 °, inclination angle.For example, may be used also
Screened to whether facial image is blocked by other objects, it is generally the case that jewelry should not block face's main region, jewelry
Such as dark sunglasses, mouth mask and exaggeration jewellery, it is of course also possible to be covered with dust all over above camera, cause facial image to be hidden
Gear.The picture format of the video image in the embodiment of the present invention may include but be not limited only to：BMP, JPEG, JPEG2000, PNG etc.
Deng its size can be between 10-30KB, and each video image can also correspond to a shooting time and shoot the video
The camera Unified number big figure of panorama corresponding with facial image of image such as links at information (facial image and the global image
Set up feature correspondence relational file).
Fig. 1 is referred to, is a kind of first embodiment schematic flow sheet of image processing method provided in an embodiment of the present invention.
Image processing method described in the present embodiment, comprises the following steps：
101st, pending image is obtained.
Wherein, any image that pending image can be shot by camera.Certainly, pending image is likely to as multiple figures
Picture.Certainly, above-mentioned pending image can be the image comprising certain personage, and certain personage can voluntarily be specified by user.Wait to locate
One or more facial image can be included in reason image.
Still optionally further, other targets that can also be specified comprising user in image to be checked, for example, automobile, car plate,
Etc..
Alternatively, in above-mentioned steps 101, pending image is obtained, it may include following steps：
102nd, Face datection is carried out to the pending image, obtains M facial image, the M is positive integer.
Wherein, for any pending image, image processing apparatus are required to carry out Face datection to the pending image,
In this way, can extract the facial image in the pending image, when in pending image comprising multiple faces, can obtain more personal
Face image, when including 1 facial image in pending image, can obtain 1 facial image, not include in pending image
During facial image, then after Face datection, 0 facial image is obtained.Above-mentioned Face datection can be using following at least one people
Face detection algorithm is realized：Several frequently seen Face datection algorithm is set forth below.
Boosting graders, boosting may be considered a kind of Feature Selection algorithm, due to its simple and extensive energy
The features such as power is strong, very wide application is suffered from many fields.Specifically, boosting is by the spy of original weave in
Space is levied, the wrong point of weight of sample is selected and strengthened by feature progressively to separate sample space.
HAAR human-face detectors, HAAR human-face detectors be earliest by Face datection be promoted to application level algorithm it
One.Algorithm is broadly divided into three parts, and Weak Classifier feature is selected in feature generation, boosting and strong classifier builds.It is special
Levy generation and mainly build many chequered with black and white rectangular blocks, spy is generated by comparing the difference of pixel sum of black and white rectangle
Levy, be named and be also due to that its calculating process is similar with the calculating process of HAAR small echos, the pixel of rectangular block and can be based on integration
Figure is calculated, calculating speed and considerable overhead；Feature is selected to be carried out by boosting algorithms；Finally will be singled out
The Weak Classifier feature come generates many strong classifiers by combinations of features.
Rigid or nonrigid object is divided into many by DPM (Deformable Part Model) human-face detector, DPM
Subassembly, by being described to each subassembly come the final object for expressing wanted recognition detection, each part and subassembly pass through
HOG carries out feature description.The response filter of each part is solved by optimized algorithm.Because its calculating is relatively multiple
It is miscellaneous, limit its application in many fields.
ACF (Aggregated Channel Feature) human-face detector, ACF is ICF (Integral Channel
Feature a kind of extension), equivalent to a sub-sampling has been done on the basis of ICF, advantage of this is that on the one hand reducing
The dimension of feature, two one side can increase the defensive ability/resistance ability to deformation.ACF is applied to pedestrian detection field, Zhi Houyou earliest
People is applied also to achieve good effect with Face datection field.But because its computing cost is still than larger, feature
There is larger redundancy, room for improvement is also very big.
PICO (Pixel Intensity Comparison Object Detector) human-face detector, PICO is a kind of
Feature based on statistical property describes algorithm, the description of its feature with Ferns than relatively similar, the simplicity that is calculated due to it and stronger
Descriptive power, be used in many computer vision fields such as field such as object detection, target identification, target following.Recently
Someone is applied in Face datection field, and ratio of precision is more general, but calculating speed is very fast.Trace it to its cause or mark sheet
Up to excessively simple, have than larger room for promotion.
103rd, the M facial image is screened, obtains N facial image, the N is less than or equal to the M
Integer.
Alternatively, user can choose N facial image from M facial images, it is of course also possible to by M facial image
It is ranked up to bad by good according to picture quality, so that, can preferentially choose picture quality preferably N number of facial image.
Alternatively, in above-mentioned steps 103, the M facial image is screened, it may include following steps：
A1 the angle information of facial image i), is obtained, the angle information is following at least one：Horizontally rotate angle,
The angle of pitch and gradient, the facial image i are any facial image in the M facial image；
A2), the angle information and predetermined angle information of the facial image i are compared, the facial image i's
When angle information is compared successfully with the predetermined angle information, retain the facial image i.
Wherein, due to there is a certain distance between camera and face, and, it is generally the case that people be also it is dynamic, because
And, the angle of the facial image that camera is captured also is being continually changing, if user movement is obtained comparatively fast, then possible camera is caught
The fogging image grasped, or, only half of face, or, only one of which silhouette, in this way, at this stage, then cannot be to such figure
As being identified.Thus, it is necessary to the angle of angular image during image is uploaded, if angle is not in the range of certain,
Then it is not easy to subsequently deploy to ensure effective monitoring and control of illegal activities, predetermined angle information is then to upload image for specification, only meets the upper of the predetermined angle information
Blit picture can just upload onto the server.Predetermined angle information can include following at least one：Horizontally rotate angular range, pitching
Angular region and inclination range.For example, horizontally rotate angle for ± 30 °, the angle of pitch be ± 20 °, inclination angle be ± 45 °.
Alternatively, in above-mentioned steps 103, the M facial image is screened, the M facial image is carried out
Screening, obtains N facial image, it may include following steps：
B1 the image that human face region in the M facial images is not blocked), is filtered out, K facial image, institute is obtained
K is stated for positive integer；
B2 image quality evaluation), is carried out to the K facial image, the K image quality evaluation values are obtained；
B3 the image quality evaluation values more than predetermined threshold value), are chosen from the K image quality evaluation values, institute is obtained
N number of image quality evaluation values are stated, the corresponding N facial image of the N number of image quality evaluation values is obtained.
Wherein, in step 41, continuous shooting mode can be used, obtains corresponding multiple images of targets preview parameter.It is above-mentioned such as
What chooses best one of picture quality from multiple images.Can be using at least one image quality evaluation index respectively to image
Image quality evaluation is carried out, image quality evaluation values are obtained, wherein, image quality evaluation index may include but be not limited only to：It is flat
Equal gray scale, mean square deviation, entropy, edge conservation degree, signal to noise ratio etc..The image quality evaluation values that may be defined as obtaining are bigger, then scheme
As quality is better.
It should be noted that due to when use single evaluation index is evaluated picture quality, with certain limitation
Property, therefore, picture quality can be evaluated using multiple images quality evaluation index, certainly, picture quality is evaluated
When, not image quality evaluation index is The more the better, because image quality evaluation index is more, the meter of image quality assessment process
Calculate complexity higher, it is better also to may not be certain image quality evaluation effect, therefore, in the situation higher to image quality evaluation requirement
Under, picture quality can be evaluated using 2~10 image quality evaluation indexs.Specifically, image quality evaluation is chosen to refer to
Target number and which index, depending on the situation that implements.Certainly, specifically scene selection picture quality must be also combined to comment
Valency index, carries out carrying out the image quality index of image quality evaluation selection under image quality evaluation and bright ring border under dark situation
Can be different.
Alternatively, in the case of not high to image quality evaluation required precision, an image quality evaluation index can be used
Evaluated, for example, carrying out image quality evaluation values to pending image with entropy, it is believed that entropy is bigger, then illustrate picture quality
It is better, on the contrary, entropy is smaller, then illustrate that picture quality is poorer.
Alternatively, in the case of higher to image quality evaluation required precision, multiple images quality evaluation can be used
Index is evaluated pending image, and image quality evaluation is carried out to pending image in multiple images quality evaluation index
When, the weight of each image quality evaluation index in the plurality of image quality evaluation index can be set, can obtain multiple images matter
Amount evaluation of estimate, final image quality evaluation values, example are can obtain according to the plurality of image quality evaluation values and its corresponding weight
Such as, three image quality evaluation indexs are respectively：A indexs, B indexs and C indexs, the weight of A is a1, and the weight of B is a2, C's
Weight is a3, and when carrying out image quality evaluation to a certain image using A, B and C, the corresponding image quality evaluation values of A are b1, B couples
The image quality evaluation values answered are b2, and the corresponding image quality evaluation values of C are b3, then, last image quality evaluation values=
a1b1+a2b2+a3b3.Under normal circumstances, image quality evaluation values are bigger, illustrate that picture quality is better.
104th, the N facial image is uploaded onto the server.
Alternatively, in above-mentioned steps 104, the N facial image is uploaded onto the server, including：
41), the N facial image is compressed, the N first object facial image is obtained；
42) N first object facial image and its corresponding attribute information, are uploaded into the server.
Wherein, N facial image can be compressed, lossy compression method mode or Lossless Compression mode may be selected to the N
Facial image is opened to be compressed.In this way, uploading speed can be accelerated during the N facial image is uploaded.Certainly, press
The memory size of N facial image after contracting can be in a certain scope, for example, 10kb~30kb.
Certainly, before step 41, it is also possible to perform the following steps：
The size of above-mentioned N facial image is adjusted to consistent, then the N facial image is carried out in step 41 again
Compression.It is not of uniform size due to the facial image that is detected in pending image, it is relevant mainly due to camera imaging, from
Camera is nearer, and facial image is bigger, from camera more away from, then facial image is smaller.Thus, can be by all people's face image
Size is adjusted to consistent, in this way, follow-up management can be facilitated.
As can be seen that by the embodiment of the present invention, obtaining pending image, Face datection is carried out to pending image, obtained
To M facial image, M is positive integer, and M facial image is screened, and obtains N facial image, and N is less than or equal to M
Integer, N facial images are uploaded onto the server, in this way, can realize intelligent uploading image.
Consistent with the abovely, Fig. 2 is referred to, is a kind of the second implementation of image processing method provided in an embodiment of the present invention
Example schematic flow sheet.Image processing method described in the present embodiment, comprises the following steps：
201st, pending image is obtained.
202nd, Face datection is carried out to the pending image, obtains M facial image, the M is positive integer.
203rd, the M facial image is screened, obtains N facial image, the N is less than or equal to the M
Integer.
Alternatively, the specific descriptions of above-mentioned steps 201- steps 203 can refer to the step of the image processing method described by Fig. 1
Rapid 101- steps 103.
204th, image enhancement processing is carried out to the N facial image.
Wherein, image enhancement processing is to lift the N picture quality of facial image, the mode of image enhancement processing
May include but be not limited only to：Contrast stretching, histogram equalization, image restoration, wavelet transformation, certainly, due to the N face
Image is different images, thus, contrast, the average gray of each image are different, thus, different images can be used
Enhancing processing mode carries out image enhancement processing to the N facial image.After image enhancement processing is carried out to facial image, people
The better quality of face image, more convenient subsequent user carries out image retrieval, or, it is managed and safeguards.
Alternatively, above-mentioned steps 204, image enhancement processing is carried out to the N facial image, also can be comprising following step
Suddenly：
Image quality evaluation is carried out to the N facial image, N number of image quality evaluation values are obtained；
Choose the X image quality evaluation values less than pre-set image quality threshold in N number of image quality evaluation values；
Image enhancement processing is carried out to the corresponding facial image of X image quality evaluation values, is removed in the N facial image
The corresponding facial image of X image quality evaluation values does not make image enhancement processing then.
Wherein, above-mentioned pre-set image quality threshold can voluntarily be set or system default by user.
205th, by image enhaucament after the N facial images be uploaded to the server.
Wherein, the N after image enhaucament facial image can be uploaded onto the server, certainly, server can also be to the N
Facial image is identified, if in any image storehouse in a certain image in the N facial image and image processing apparatus
Image mismatch, then can set up new storehouse for preserving the facial image, if a certain image in the N facial image with
, then can be stored in the facial image in the image library by the images match in a certain image library in image processing apparatus.
As can be seen that by the image processing apparatus described by the embodiment of the present invention, pending image can be obtained, place is treated
Reason image carries out Face datection, obtains M facial image, and M is positive integer, and M facial image is screened, and obtains N people
Face image, N is the integer less than or equal to M, and image enhancement processing is carried out to N facial image, and by the N after image enhaucament
Facial image uploads onto the server, in this way, intelligent upload image can be realized.
Consistent with the abovely, it is below the device of the above-mentioned image processing method of implementation, it is specific as follows：
Fig. 3 a are referred to, is a kind of first embodiment structural representation of image processing apparatus provided in an embodiment of the present invention
Figure.Image processing apparatus described in the present embodiment, including：Acquiring unit 301, detection unit 302, the and of screening unit 303
Uploading unit 304, it is specific as follows：
Acquiring unit 301, for obtaining pending image；
Detection unit 302, for carrying out Face datection to the pending image, obtains M facial image, and the M is
Positive integer；
Screening unit 303, for being screened to the M facial images, obtains N facial image, the N be less than
Or equal to the integer of the M；
Uploading unit 304, for the N facial image to be uploaded onto the server.
Alternatively, the specific refinement of the screening unit 303 of the image processing apparatus such as Fig. 3 b, Fig. 3 b described in Fig. 3 a
Structure, the screening unit 303 may include：Acquisition module 3031 and comparing module 3032, it is specific as follows：
Acquisition module 3031, the angle information for obtaining facial image i, the angle information is following at least one：
Horizontally rotate angle, the angle of pitch and gradient, the facial image i is any facial image in the M facial image；
Comparing module 3032, for the angle information of the facial image i and predetermined angle information to be compared, in institute
When the angle information for stating facial image i is compared successfully with the predetermined angle information, retain the facial image i.
Alternatively, the specific refinement of the screening unit 303 of the image processing apparatus such as Fig. 3 c, Fig. 3 c described in Fig. 3 a
Structure, the screening unit 303 may include：Screening module 3033, evaluation module 3034 and selection module 3035, it is specific as follows：
Screening module 3033, for filtering out the image that human face region in the M facial images is not blocked, obtains K
Facial image is opened, the K is positive integer；
Evaluation module 3034, for carrying out image quality evaluation to the K facial image, obtains the K image matter
Amount evaluation of estimate；
Module 3035 is chosen, for choosing the picture quality more than predetermined threshold value from the K image quality evaluation values
Evaluation of estimate, obtains N number of image quality evaluation values, obtains the corresponding N facial image of the N number of image quality evaluation values.
Alternatively, the specific refinement of the uploading unit 304 of the image processing apparatus such as Fig. 3 d, Fig. 3 d described in Fig. 3 a
Structure, the uploading unit 304 may include：Compression module 3041 and uploading module 3042, it is specific as follows；
Compression module 3041, for the N facial image to be compressed, obtains the N first object face figure
Picture；
Uploading module 3042, for the N first object facial image and its corresponding attribute information to be uploaded into institute
State server.
Alternatively, such as the another modification structures that Fig. 3 e, Fig. 3 e are the image processing apparatus described in Fig. 3 a, it can also be wrapped
Include：Processing unit 305, it is specific as follows：
Processing unit 305, for being screened in 303 couples of M of the screening unit facial images, obtains N people
After face image, image enhancement processing is carried out to the N facial image；
The uploading unit 304 specifically for：
The N facial image after by image enhaucament is uploaded to the server.
As can be seen that by the image processing apparatus described by the embodiment of the present invention, pending image can be obtained, place is treated
Reason image carries out Face datection, obtains M facial image, and M is positive integer, and M facial image is screened, and obtains N people
Face image, N is the integer less than or equal to M, N facial image is uploaded onto the server, in this way, blit in intellectuality can be realized
Picture.
Consistent with the abovely, Fig. 4 is referred to, is a kind of the second implementation of image processing apparatus provided in an embodiment of the present invention
Example structural representation.Image processing apparatus described in the present embodiment, including：At least one input equipment 1000；At least one
Individual output equipment 2000；At least one processor 3000, such as CPU；With memory 4000, above-mentioned input equipment 1000, output
Equipment 2000, processor 3000 and memory 4000 are connected by bus 5000.
Wherein, above-mentioned input equipment 1000 concretely contact panel, physical button or mouse.
The concretely display screen of above-mentioned output equipment 2000.
Above-mentioned memory 4000 can be high-speed RAM memory, or nonvolatile storage (non-volatile
Memory), such as magnetic disk storage.Above-mentioned memory 4000 is used to store batch processing code, above-mentioned input equipment 1000, defeated
Going out equipment 2000 and processor 3000 is used to call the program code stored in memory 4000, performs following operation：
Above-mentioned processor 3000, is used for：
Obtain pending image；
Face datection is carried out to the pending image, M facial image is obtained, the M is positive integer；
The M facial image is screened, N facial image is obtained, the N is whole less than or equal to the M
Number；
The N facial image is uploaded onto the server.
Alternatively, 3000 couples of M of above-mentioned processor facial images are screened, including：
The angle information of facial image i is obtained, the angle information is following at least one：Horizontally rotate angle, pitching
Angle and gradient, the facial image i are any facial image in the M facial image；
The angle information of the facial image i and predetermined angle information are compared, in the angle of the facial image i
When information is compared successfully with the predetermined angle information, retain the facial image i.
Alternatively, 3000 couples of M of above-mentioned processor facial images are screened, and obtain N facial image, including：
The image that human face region in the M facial images is not blocked is filtered out, K facial image is obtained, the K is
Positive integer；
Image quality evaluation is carried out to the K facial image, the K image quality evaluation values are obtained；
The image quality evaluation values more than predetermined threshold value are chosen from the K image quality evaluation values, obtains described N number of
Image quality evaluation values, obtain the corresponding N facial image of the N number of image quality evaluation values.
Alternatively, above-mentioned processor 3000 uploads onto the server the N facial image, including：
The N facial image is compressed, the N first object facial image is obtained；
The N first object facial image and its corresponding attribute information are uploaded into the server.
Alternatively, above-mentioned processor 3000, screens described to the M facial image, obtains N facial image
Afterwards, also particularly useful for：
Image enhancement processing is carried out to the N facial image；
It is described that the N facial image uploads onto the server, including：
The N facial image after by image enhaucament is uploaded to the server.
The embodiment of the present invention also provides a kind of computer-readable storage medium, wherein, the computer-readable storage medium can be stored with journey
Sequence, the part or all of step including any image processing method described in the above method embodiment when program is performed
Suddenly.
Although invention has been described to combine each embodiment herein, however, implementing the present invention for required protection
During, those skilled in the art are by checking the accompanying drawing, disclosure and appended claims, it will be appreciated that and it is real
Other changes of the existing open embodiment.In the claims, " including " (comprising) one word be not excluded for other composition
Part or step, "a" or "an" are not excluded for the situation of multiple.Single processor or other units can realize claim
In some functions enumerating.Mutually different has been recited in mutually different dependent some measures, it is not intended that these are arranged
Apply to combine and produce good effect.
It will be understood by those skilled in the art that embodiments of the invention can be provided as method, device (equipment) or computer journey
Sequence product.Therefore, in terms of the present invention can be using complete hardware embodiment, complete software embodiment or combination software and hardware
The form of embodiment.And, the present invention can be used and wherein include the calculating of computer usable program code at one or more
The computer program implemented in machine usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.Computer program is stored/distributed in suitable medium, is provided together with other hardware or as the one of hardware
Part, it would however also be possible to employ other distribution forms, such as passes through Internet or other wired or wireless telecommunication systems.
The present invention be with reference to the embodiment of the present invention method, device (equipment) and computer program product flow chart with/
Or block diagram is described.It should be understood that each flow during flow chart and/or block diagram can be realized by computer program instructions and/
Or the combination of the flow and/or square frame in square frame and flow chart and/or block diagram.These computer program instructions can be provided
To the processor of all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing devices producing one
Individual machine so that produced for realizing by the instruction of computer or the computing device of other programmable data processing devices
The device of the function of being specified in one flow of flow chart or multiple one square frame of flow and/or block diagram or multiple square frames.
These computer program instructions may be alternatively stored in can guide computer or other programmable data processing devices with spy
In determining the computer-readable memory that mode works so that instruction of the storage in the computer-readable memory is produced and include finger
Make the manufacture of device, the command device realize in one flow of flow chart or multiple one square frame of flow and/or block diagram or
The function of being specified in multiple square frames.
These computer program instructions can be also loaded into computer or other programmable data processing devices so that in meter
Series of operation steps is performed on calculation machine or other programmable devices to produce computer implemented treatment, so as in computer or
The instruction performed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in individual square frame or multiple square frames.
Although with reference to specific features and embodiment, invention has been described, it is clear that, do not departing from this hair
In the case of bright spirit and scope, various modifications and combinations can be carried out to it.Correspondingly, the specification and drawings are only institute
The exemplary illustration of the invention that attached claim is defined, and be considered as covered in the scope of the invention any and all and repair
Change, change, combining or equivalent.Obviously, those skilled in the art the present invention can be carried out it is various change and modification without
Depart from the spirit and scope of the present invention.So, if it is of the invention these modification and modification belong to the claims in the present invention and its
Within the scope of equivalent technologies, then the present invention is also intended to comprising these changes and modification.
Claims (10)
1. a kind of image processing method, it is characterised in that including：
Obtain pending image；
Face datection is carried out to the pending image, M facial image is obtained, the M is positive integer；
The M facial image is screened, N facial image is obtained, the N is less than or equal to the integer of the M；
The N facial image is uploaded onto the server.
2. method according to claim 1, it is characterised in that described to be screened to the M facial image, including：
The angle information of facial image i is obtained, the angle information is following at least one：Horizontally rotate angle, the angle of pitch and
Gradient, the facial image i is any facial image in the M facial image；
The angle information of the facial image i and predetermined angle information are compared, in the angle information of the facial image i
When being compared successfully with the predetermined angle information, retain the facial image i.
3. method according to claim 1, it is characterised in that described to be screened to the M facial image, obtains N
Facial image is opened, including：
The image that human face region in the M facial images is not blocked is filtered out, K facial image is obtained, the K is just whole
Number；
Image quality evaluation is carried out to the K facial image, the K image quality evaluation values are obtained；
The image quality evaluation values more than predetermined threshold value are chosen from the K image quality evaluation values, N number of image is obtained
Quality evaluation value, obtains the corresponding N facial image of the N number of image quality evaluation values.
4. the method according to any one of claims 1 to 3, it is characterised in that described to upload to the N facial image
Server, including：
The N facial image is compressed, the N first object facial image is obtained；
The N first object facial image and its corresponding attribute information are uploaded into the server.
5. the method according to any one of claims 1 to 3, it is characterised in that carried out to the M facial image described
Screening, obtains after N facial image, and methods described also includes：
Image enhancement processing is carried out to the N facial image；
It is described that the N facial image uploads onto the server, including：
The N facial image after by image enhaucament is uploaded to the server.
6. a kind of image processing apparatus, it is characterised in that including:
Acquiring unit, for obtaining pending image；
Detection unit, for carrying out Face datection to the pending image, obtains M facial image, and the M is positive integer；
Screening unit, for being screened to the M facial images, obtains N facial image, the N be less than or equal to
The integer of the M；
Uploading unit, for the N facial image to be uploaded onto the server.
7. image processing apparatus according to claim 6, it is characterised in that the screening unit includes：
Acquisition module, the angle information for obtaining facial image i, the angle information is following at least one：Horizontally rotate
Angle, the angle of pitch and gradient, the facial image i are any facial image in the M facial image；
Comparing module, for the angle information of the facial image i and predetermined angle information to be compared, in the face figure
When being compared successfully with the predetermined angle information as the angle information of i, retain the facial image i.
8. image processing apparatus according to claim 6, it is characterised in that the screening unit includes：
Screening module, for filtering out the image that human face region in the M facial images is not blocked, obtains K face figure
Picture, the K is positive integer；
Evaluation module, for carrying out image quality evaluation to the K facial image, obtains the K image quality evaluation values；
Module is chosen, for choosing the image quality evaluation values more than predetermined threshold value from the K image quality evaluation values, is obtained
To N number of image quality evaluation values, the corresponding N facial image of the N number of image quality evaluation values is obtained.
9. image processing apparatus according to any one of claim 6 to 8, it is characterised in that the uploading unit includes：
Compression module, for the N facial image to be compressed, obtains the N first object facial image；
Uploading module, for the N first object facial image and its corresponding attribute information to be uploaded into the server.
10. image processing apparatus according to any one of claim 6 to 8, it is characterised in that described image processing unit is also
Including：
Processing unit, for being screened to the M facial images in the screening unit, after obtaining N facial image,
Image enhancement processing is carried out to the N facial image；
The uploading unit specifically for：
The N facial image after by image enhaucament is uploaded to the server.
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| CN201611210672.0A CN106778645B (en) | 2016-12-24 | 2016-12-24 | A kind of image processing method and device |
| PCT/CN2017/114856 WO2018113523A1 (en) | 2016-12-24 | 2017-12-06 | Image processing method and device, and storage medium |
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| CN106778645B (en) | 2018-05-18 |
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