CN110231960A - A kind of target screen determines method, apparatus and storage medium - Google Patents

A kind of target screen determines method, apparatus and storage medium Download PDF

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Publication number
CN110231960A
CN110231960A CN201810181679.7A CN201810181679A CN110231960A CN 110231960 A CN110231960 A CN 110231960A CN 201810181679 A CN201810181679 A CN 201810181679A CN 110231960 A CN110231960 A CN 110231960A
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image
screen
target screen
classification
target
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孙延宾
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ZTE Corp
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ZTE Corp
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Priority to CN201810181679.7A priority Critical patent/CN110231960A/en
Priority to PCT/CN2019/076694 priority patent/WO2019170038A1/en
Publication of CN110231960A publication Critical patent/CN110231960A/en
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for program control, e.g. control units
    • G06F9/06Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44Arrangements for executing specific programs
    • G06F9/4401Bootstrapping
    • G06F9/4418Suspend and resume; Hibernate and awake
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/24Classification techniques
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for program control, e.g. control units
    • G06F9/06Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44Arrangements for executing specific programs
    • G06F9/4401Bootstrapping

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  • Software Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
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  • Computer Security & Cryptography (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Evolutionary Computation (AREA)
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  • Computer Vision & Pattern Recognition (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Artificial Intelligence (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Image Analysis (AREA)
  • Collating Specific Patterns (AREA)
  • User Interface Of Digital Computer (AREA)

Abstract

The embodiment of the invention discloses a kind of target screens to determine method, apparatus and storage medium, belongs to communication technique field.The method is suitable for the terminal equipped at least two screens, comprising: obtains the image of the image collecting device shooting of at least one screen;The image classification that classification processing obtains described image is carried out to described image;It is corresponding with target screen to judge whether described image classification is marked as;Target screen is determined according to judging result.Using the embodiment of the present invention, image classification is carried out by the image that the camera to different screens acquires, target screen is determined from multiple screens according to classification results and target screen corresponding relationship, compared with the prior art relies on merely face or fingerprint to determine target screen, not only increase accuracy rate, and whole process is participated in without user, improves user experience.

Description

A kind of target screen determines method, apparatus and storage medium
Technical field
The present embodiments relate to communication technique fields more particularly to a kind of target screen to determine method, apparatus and storage Medium.
Background technique
In recent years, intelligent terminal (such as mobile phone) is pursuing always the development trend of large screen, and still, the increase of screen is inevitable The portability that will affect terminal carrying, when screen increases to a certain extent, people pursued large screen vision and to intelligent ends Just there is contradiction in the portability requirements at end, in this case, double screen terminal occur.Double screen terminal is set there are two screen, When user's wake-up device, it is thus necessary to determine which screen waken up.
Therefore, it is necessary to which providing a kind of target screen determines method, apparatus and storage medium, make the end with multiple screens End can accurately wake up the screen close to user side.
Summary of the invention
In view of this, a kind of target screen of being designed to provide of the embodiment of the present invention determines that method, apparatus and storage are situated between Matter needs user to participate in solve the terminal with multiple screens in the prior art when waking up screen, and accuracy rate is not high Problem.
It is as follows that the embodiment of the present invention solves technical solution used by above-mentioned technical problem:
First aspect according to an embodiment of the present invention provides a kind of target screen and determines method, is suitable for being equipped at least The terminal of two screens, which comprises
Obtain the image of the image collecting device shooting of at least one screen;
The image classification that classification processing obtains described image is carried out to described image;
It is corresponding with target screen to judge whether described image classification is marked as;
Target screen is determined according to judging result.
The second aspect according to an embodiment of the present invention provides a kind of target screen determining device, is suitable for being equipped at least The terminal of two screens, described device include:
Module is obtained, the image that the image collecting device for obtaining at least one screen is shot;
Categorization module, for carrying out the image classification that classification processing obtains described image to described image;
Judgment module for judging it is corresponding with target screen whether described image classification is marked as, and is tied according to judgement Fruit determines target screen.
In terms of third according to an embodiment of the present invention, a kind of storage medium is provided, the storage medium is stored with one Or multiple programs, one or more of programs can be executed by one or more processor, to realize such as first aspect The step.
The target screen of the embodiment of the present invention determines method, apparatus and storage medium, passes through the camera shooting to different screens The image of head acquisition carries out image classification, and target screen is determined from multiple screens according to classification results and target screen corresponding relationship Curtain, compared with the prior art relies on merely face or fingerprint to determine target screen, not only increases accuracy rate, and whole process It is participated in without user, improves user experience.
Detailed description of the invention
Fig. 1 is the flow chart that a kind of target screen that the embodiment of the present invention one provides determines method;
Fig. 2 is that second embodiment of the present invention provides the flow charts that another target screen determines method;
Fig. 3 is a kind of modular structure schematic diagram for target screen determining device that the embodiment of the present invention three provides.
Realization, functional characteristics and the advantage of purpose of the embodiment of the present invention will be done furtherly referring to attached drawing in conjunction with the embodiments It is bright.
Specific embodiment
In order to be clearer and more clear technical problem to be solved of the embodiment of the present invention, technical solution and beneficial effect, Below in conjunction with drawings and examples, the embodiment of the present invention is further elaborated.It should be appreciated that tool described herein Body embodiment is only used to explain the embodiment of the present invention, is not intended to limit the present invention embodiment.
In subsequent description, it is only using the suffix for indicating such as " module ", " component " or " unit " of element The explanation for being conducive to the embodiment of the present invention, itself does not have a specific meaning.Therefore, " module ", " component " or " unit " can Mixedly to use.
Inventor has found that the mode that the double screen terminal of the prior art wakes up screen is usually in the implementation of the present invention Fixed screen is waken up by fixed mode or is dynamically determined target screen.Due to two screen diversity ratios of Dual-band Handy Phone Smaller, discrimination is little, and therefore, when wake-up device is dynamically determined target screen, it is possible to reduce since target screen is back to user And perplex to user's bring.
The method for being dynamically determined target screen at present is more, and more commonly used has the following two kinds:
One, using fingerprint identification technology, when user adds finger print information, it is desirable that user setting finger print information, often A fingerprint can bind a screen, and when with some fingerprint wake-up device, system is according to the information being previously saved come some The bright screen bound therewith.But the flexibility of this method is inadequate.For example some fingerprint of user's right hand binds screen one, is shielding Also there is a strong possibility when curtain two faces oneself will use right hand progress fingerprint wake-up, and screen one is lighted at this time, target screen Determine mistake and.The method needs user to be manually operated, and needs to keep firmly in mind to remember fingerprint binding information, and user experience is not It is good.
Two, using face recognition technology, recognition of face is carried out when user wakes up mobile phone, is imaged if recognizing face A face screen where head is lighted, and otherwise another screen is lighted.But this method discrimination is relatively low, because many times Although camera is with user in the same side, face is determined not in camera viewfinder range so as to cause target screen Mistake accuracy is relatively low.
The embodiment of the present invention one provides a kind of target screen and determines method, suitable for being equipped with the end of at least two screens End, referring to Fig. 1, this method comprises:
The image that S101, the image collecting device for obtaining at least one screen are shot;
S102, the image classification that classification processing obtains the image is carried out to the image;
S103, to judge whether the image classification is marked as corresponding with target screen;
S104, target screen is determined according to judging result.
In practical application, when user's wake-up device, system is waken up from dormant state, and image collecting device is got started Work opens camera and takes pictures, obtains image.
It should be noted that the image feature information mentioned in the embodiment of the present invention includes extracting from image data Characteristic value, such as color space information, figure information, brightness information, neural network weight etc..
In a feasible scheme, the image classification that classification processing obtains the image step S102, is carried out to the image, Include:
The image data of the image calculate and obtains image feature information;
The image feature information is matched with the preset features information in preset features library, and will be matching pre- Set image classification of the corresponding image classification of characteristic information as described image.
In a feasible scheme, the image classification that classification processing obtains the image is carried out to the image, comprising:
Classification processing is carried out to the image using machine learning algorithm, comprising:
According to the machine learning algorithm to the degree of dependence of historical data, selectively read in image feature base pre- Characteristic information is set to be matched, and learns new feature;
Wherein, which includes K- nearest neighbor algorithm algorithm of support vector machine or deep learning algorithm.
In practical application, the mode for carrying out classification processing to image includes but is not limited to conventional machine learning algorithm, such as K- nearest neighbor algorithm, algorithm of support vector machine and deep learning algorithm (such as convolutional neural networks algorithm).
It during processing can be selective in characteristics of image number according to algorithms of different to the degree of dependence of historical data It is matched according to historical data information is read in library, if this calculated image feature information is not included in preset features library In, new image feature information can be saved in preset features library.
In a feasible scheme, when the terminal is set there are two when screen, this determines target screen according to judging result, Include:
If obtaining the image of the image collecting device shooting of two screens, determine that image classification is marked as and target Screen corresponding to the corresponding image of screen is target screen;
If only obtaining the image of image collecting device shooting, it is marked as and mesh in the image classification of the image Mark screen is to determining that the corresponding screen of the image collecting device is target screen when corresponding to, otherwise, it determines another screen is target Screen.
In practical application, if the screen more than two of terminal, and the screen of image collecting device would be not configured less than two It is a, target screen directly can also be determined according to the result of image classification.
In a feasible scheme, after step S104, determining target screen according to judging result, this method is also wrapped It includes:
Whether the screen that verification user is operated is consistent with determining target screen;
The preset features information is marked or revised according to check results.
In practical application, after target screen is lighted, if target screen determines that accurately user can be directly in the target It is inputted, is operated, otherwise, user may be switched to other screens and operate, and user inputs screen on screen Operation, the input mode of operation include but is not limited to the screen operators such as to click, double-click, slide.
In practical application, after lighting target screen, can also be asked the user whether by way of dialog box using Current screen, then the selection for the user that follows up determine the screen that user is operated, and shortcut key or other quick behaviour also can be set Make mode, user is helped to realize the quick switching between screen.
If the screen that user is operated is consistent with the target screen determined, check results are correct, otherwise verification knot Fruit mistake.When check results correctly then add to the corresponding image classification of relevant preset features information in image feature base Add correct labeling, otherwise adds error flag.Alternatively, it is corresponding to correct corresponding preset features information according to the operation to user Image classification, whether correct and image classification is corresponding with target screen for the image classification including the prediction picture characteristic information Whether relationship is correct.It can be further improved the accuracy of subsequent classification by verification classification correctness.
In practical application, image classification, prediction picture characteristic information and corresponding relationship such as 1 institute of table with target screen Show, it should be noted that be only a simple citing in table 1, actual corresponding relationship can be different according to the actual situation:
Table 1
Preset features information Image classification Whether target screen
Nose, eyes, eyebrow, mouth Face It is
Ground, metope, railing Building It is no
Trees, flower, desk Environment It is no
In practical application, corresponding corresponding relationship, example can also be marked by way of to different image classification assignment Such as, being assigned a value of 1 indicates that the image classification is corresponding with target screen, if the image that the camera of some screen is shot is corresponding Image classification is assigned a value of 1, then the screen is target screen, lights the screen at this time;It is assigned a value of zero, then it represents that the image point Class does not correspond to target screen, if the corresponding image classification of image that the camera of some screen is shot is assigned a value of 0, does not need Light the screen.
The matched preset features information pair of image feature information with the image of camera shooting can also be seen that by upper table The image classification answered is exactly the corresponding image classification of the image.
In a feasible scheme, after step S104, determining target screen according to judging result, this method is also wrapped It includes:
Light determining target screen.
The target screen of the present embodiment determines method, carries out image by the image that the camera to different screens acquires Classification determines target screen according to classification results and target screen corresponding relationship from multiple screens, with the prior art merely according to It determines that target screen is compared by face or fingerprint, not only increases accuracy rate, and whole process is participated in without user, is improved User experience.
On the basis of previous embodiment, second embodiment of the present invention provides another target screens to determine method, the party Method is illustrated so that the screen of Dual-band Handy Phone wakes up as an example, it is assumed that two screens of the Dual-band Handy Phone are equipped with and can work normally Camera.Referring to Fig. 2, method flow includes:
S201, when cell phone system is waken up from dormant state, target screen determining device obtain image collecting device adopt The image of collection.
In practical application, when cell phone system is waken up from dormant state, process quilt of the image collector setting in backstage It wakes up, open camera and takes pictures, obtain image data.
S202, the predicted value that image is calculated using convolutional neural networks.
Wherein, predicted value is that is, image feature information.
In practical application, which includes:
1, image is pre-processed.
In practical application, which includes the resolution ratio that compression reduces image.
The resolution ratio of taking pictures of existing mobile phone is generally relatively high, and high-resolution will increase calculating cost, and simultaneously to image recognition Without too many significant information, it is possible to reduce resolution ratio.In addition, picture size requirement of the convolutional neural networks to input It is unified, it can use preparatory trained characteristic value information in this way.
2, pretreated image is calculated using convolutional neural networks.
Convolutional neural networks can be used in this step to calculate pretreated image.
In practical application, can only it calculate without being trained.
The network parameter needs of convolutional network are trained to obtain to a large amount of picture, and the similar devices such as mobile phone are can not be into The such large-scale calculations of row, therefore preparatory trained characteristic value information on computers can be used, the instruction on computer Practicing data can be used image library disclosed in ImageNet etc..Only need the extremely short time that can calculate figure in this way on mobile phone The predicted value of picture.
S203, calculated predicted value is matched with the preset features information in preset features library.
Need to predefine a feature database (preset features library) on mobile phone, each preset features letter in the preset features library Breath has corresponding image classification, and whether each image classification marks out it corresponding with target screen.
S204, target screen is determined according to matching result.
In this step, the predicted value of the image of the camera shooting of the first screen of the mobile phone is defined as with image classification The preset features information matches of [face], [picture material is simple] (such as number of modes is simple less than 3), it is assumed that [face] The target screen of image classification relevant be assigned a value of 1;And the prediction of the image of the camera shooting of the second screen of the mobile phone Value and image classification are defined as the preset features information matches of [building], [trees], [figure viewed from behind] etc., it is assumed that these image classifications Target screen it is relevant be assigned a value of 0, then being assigned a value of 1 according to table 1 and illustrating that corresponding screen (i.e. screen one) can determine For target screen.
S205: determining target screen is lighted.
According to step S204's as a result, screen one should be lighted.
S206: whether the screen that verification user is operated is consistent with determining target screen, and according to check results mark Note.
If the screen that user is operated is consistent with the target screen determined, check results are correct, otherwise verification knot Fruit mistake.When check results correctly then add to the corresponding image classification of relevant preset features information in image feature base Add correct labeling, otherwise adds error flag.
The target screen of the present embodiment determines method, carries out image by the image that the camera to different screens acquires Classification determines target screen according to classification results and target screen corresponding relationship from multiple screens, with the prior art merely according to It determines that target screen is compared by face or fingerprint, not only increases accuracy rate, and whole process is participated in without user, is improved User experience.
On the basis of previous embodiment, the embodiment of the present invention three provides a kind of target screen determining device, is suitable for Terminal equipped at least two screens, referring to Fig. 3, the device includes:
Module 301 is obtained, the image that the image collecting device for obtaining at least one screen is shot;
Categorization module 302, for carrying out the image classification that classification processing obtains the image to the image;
Judgment module 303 is tied for judging it is corresponding with target screen whether the image classification is marked as, and according to judgement Fruit determines target screen.
In practical application, when user's wake-up device, system is waken up from dormant state, and image collecting device is got started Work opens camera and takes pictures, obtains image.
In a feasible scheme, the categorization module 302, comprising:
Computational submodule carries out calculating acquisition image feature information for the image data to the image;
Matching module, for the image feature information to be matched with the preset features information in preset features library, and Using the matching corresponding image classification of preset features information as the image classification of described image.
In a feasible scheme, which is also used to classify to the image using machine learning algorithm Processing, comprising: according to the machine learning algorithm to the degree of dependence of historical data, selectively read in image feature base Preset features information learns new feature to be matched;
Wherein, which includes K- nearest neighbor algorithm, algorithm of support vector machine or deep learning algorithm.
In practical application, the mode for carrying out classification processing to image includes but is not limited to conventional machine learning algorithm, such as K- nearest neighbor algorithm, algorithm of support vector machine and deep learning algorithm (such as convolutional neural networks algorithm).
It during processing can be selective in characteristics of image number according to algorithms of different to the degree of dependence of historical data It is matched according to historical data information is read in library, if this calculated image feature information is not included in preset features library In, new image feature information can be saved in preset features library.
In a feasible scheme, when the terminal is set there are two when screen, which is also used to obtaining When the image of the image collecting device shooting of two screens, determine that image classification is marked as figure corresponding with target screen As corresponding screen be target screen, or be also used to only obtain an image collecting device shooting image when, When the image classification of the image is marked as corresponding with target screen, determine that the corresponding screen of the image collecting device is target screen Curtain, otherwise, it determines another screen is target screen.
In practical application, if the screen more than two of terminal, and the screen of image collecting device would be not configured less than two It is a, target screen directly can also be determined according to the result of image classification.
In a feasible scheme, the device further include:
Correction verification module, for after determining target screen, screen that verification user is operated whether with determining mesh It is consistent to mark screen, and marks or revise the corresponding image classification of preset features information according to check results.
In practical application, after target screen is lighted, if target screen determines that accurately user can be directly in the target It is inputted, is operated, otherwise, user may be switched to other screens and operate, and user inputs screen on screen Operation, the input mode of operation include but is not limited to the screen operators such as to click, double-click, slide.
In practical application, after lighting target screen, can also be asked the user whether by way of dialog box using Current screen, then the selection for the user that follows up determine the screen that user is operated, and shortcut key or other quick behaviour also can be set Make mode, user is helped to realize the quick switching between screen.
If the screen that user is operated is consistent with the target screen determined, check results are correct, otherwise verification knot Fruit mistake.When check results correctly then add to the corresponding image classification of relevant preset features information in image feature base Add correct labeling, otherwise adds error flag.Alternatively, it is corresponding to correct corresponding preset features information according to the operation to user Image classification, whether correct and image classification is corresponding with target screen for the image classification including the prediction picture characteristic information Whether relationship is correct.It can be further improved the accuracy of subsequent classification by verification classification correctness.
In practical application, image classification, prediction picture characteristic information and corresponding relationship such as 1 institute of table with target screen Show.Corresponding corresponding relationship can also be marked by way of to different image classification assignment, for example, being assigned a value of 1 indicates The image classification is corresponding with target screen, if the corresponding image classification of image that the camera of some screen is shot is assigned a value of 1, then the screen is target screen, lights the screen at this time;It is assigned a value of zero, then it represents that the image classification does not correspond to target screen Curtain, if the corresponding image classification of image that the camera of some screen is shot is assigned a value of 0, does not need to light the screen.
In an optional scheme, the device further include:
Screen lights module, for lighting determining target screen.
The target screen determining device of the present embodiment carries out image by the image that the camera to different screens acquires Classification determines target screen according to classification results and target screen corresponding relationship from multiple screens, with the prior art merely according to It determines that target screen is compared by face or fingerprint, not only increases accuracy rate, and whole process is participated in without user, is improved User experience.
On the basis of previous embodiment, the embodiment of the present invention three provides a kind of storage medium, which includes The program of storage, equipment where controlling the storage medium in program operation execute the operation being somebody's turn to do such as embodiment one.
Above by reference to the preferred embodiment of the Detailed description of the invention embodiment of the present invention, not thereby limit to the embodiment of the present invention Interest field.Those skilled in the art do not depart from made any modification in the scope and spirit of the embodiment of the present invention, equally replace It changes and improves, it should all be within the interest field of the embodiment of the present invention.

Claims (11)

1. a kind of target screen determines method, suitable for being equipped with the terminal of at least two screens, which is characterized in that the method packet It includes:
Obtain the image of the image collecting device shooting of at least one screen;
The image classification that classification processing obtains described image is carried out to described image;
It is corresponding with target screen to judge whether described image classification is marked as;
Target screen is determined according to judging result.
2. the method as described in claim 1, which is characterized in that described to carry out classification processing acquisition described image to described image Image classification, comprising:
The image data of described image calculate and obtains image feature information;
Described image characteristic information is matched with the preset features information in preset features library, and will be matching preset Image classification of the corresponding image classification of characteristic information as described image.
3. the method as described in claim 1, which is characterized in that described according to judgement when the terminal is set there are two screen As a result target screen is determined, comprising:
If obtaining the image of the image collecting device shooting of described two screens, determine that image classification is marked as and target screen Screen corresponding to the corresponding image of curtain is target screen;
If only obtaining the image of image collecting device shooting, it is marked as and target in the image classification of described image Screen is to determining that the corresponding screen of described image acquisition device is target screen when corresponding to, otherwise, it determines another screen is target Screen.
4. method as described in any one of claims 1 to 3, which is characterized in that described to determine target screen according to judging result Later, the method also includes:
Whether the screen that verification user is operated is consistent with determining target screen;
The corresponding image classification of the preset features information is marked or revised according to check results.
5. method as described in any one of claims 1 to 3, which is characterized in that described to be obtained to described image progress classification processing Take the image classification of the image, comprising:
Classification processing is carried out to described image using machine learning algorithm, comprising:
According to the machine learning algorithm to the degree of dependence of historical data, selectively read in image feature base preset Characteristic information learns new feature to be matched;
Wherein, the machine learning algorithm includes K- nearest neighbor algorithm, algorithm of support vector machine or deep learning algorithm.
6. a kind of target screen determining device, suitable for being equipped with the terminal of at least two screens, which is characterized in that described device packet It includes:
Module is obtained, the image that the image collecting device for obtaining at least one screen is shot;
Categorization module, for carrying out the image classification that classification processing obtains described image to described image;
Judgment module, for judging it is corresponding with target screen and true according to judging result whether described image classification is marked as Set the goal screen.
7. device as claimed in claim 6, which is characterized in that the categorization module, comprising:
Computational submodule carries out calculating acquisition image feature information for the image data to described image;
Matching module, for described image characteristic information to be matched with the preset features information in preset features library, and will Image classification of the matching corresponding image classification of preset features information as described image.
8. device as claimed in claim 7, which is characterized in that when the terminal is set there are two screen, the judgment module, It is also used to determine that image classification is marked as and mesh in the image for the image collecting device shooting for obtaining described two screens Marking screen corresponding to the corresponding image of screen is target screen, or is also used to only obtaining an image collecting device bat When the image taken the photograph, when the image classification of described image is marked as corresponding with target screen, described image acquisition device is determined Corresponding screen is target screen, otherwise, it determines another screen is target screen.
9. such as the described in any item devices of claim 6 to 7, which is characterized in that described device further include:
Correction verification module, for after determining target screen, screen that verification user is operated whether with determining target screen Curtain is consistent, and marks or revise the corresponding image classification of the preset features information according to check results.
10. such as the described in any item devices of claim 6 to 7, which is characterized in that the categorization module is also used to using machine Learning algorithm carries out classification processing to described image, comprising: according to the machine learning algorithm to the degree of dependence of historical data, It reads preset features information selectively in image feature base to be matched, and learns new feature;
Wherein, the machine learning algorithm includes K- nearest neighbor algorithm, algorithm of support vector machine or deep learning algorithm;
Screen lights module, for lighting determining target screen.
11. a kind of storage medium, which is characterized in that the storage medium is stored with one or more program, it is one or The multiple programs of person can be executed by one or more processor, to realize step as described in any one in claim 1-5.
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