CN116432152A - Cross-platform collaborative manufacturing system - Google Patents

Cross-platform collaborative manufacturing system Download PDF

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CN116432152A
CN116432152A CN202310409817.3A CN202310409817A CN116432152A CN 116432152 A CN116432152 A CN 116432152A CN 202310409817 A CN202310409817 A CN 202310409817A CN 116432152 A CN116432152 A CN 116432152A
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CN116432152B (en
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赵兵
周雁智
李岩
尹子磊
李正博
崔碧晨
邹连玉
乔金键
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Shandong Radio And Television Communication Network Operation Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q10/10—Office automation; Time management
    • G06Q10/103—Workflow collaboration or project management
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

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Abstract

The invention belongs to the office field, and discloses a cross-platform collaborative manufacturing system which comprises a detection module, an identity recognition module, an editing module and a cloud server; the detection module is used for detecting the type of the equipment currently used by the user and acquiring available hardware of the equipment; the identity recognition module is used for providing identity verification service for the user based on the type of the equipment and available hardware, and the identity verification service is used for determining whether the user has collaborative making authority; the editing module is used for downloading the target document from the cloud server when the user has the collaborative making right, editing or viewing the downloaded target document, and sending the edited target document to the cloud server; the cloud server is used for storing the target document. According to the invention, when the permission identification of cross-platform collaborative production is carried out, the user can carry out permission verification in the most convenient verification mode under the condition of hardware support, and the user experience is improved.

Description

Cross-platform collaborative manufacturing system
Technical Field
The invention relates to the field of office work, in particular to a cross-platform collaborative manufacturing system.
Background
Because the operating systems of the computer, the tablet and the mobile phone are different, when the cross-platform collaborative production of office documents is needed, the cloud server is needed, and the principle is that clients of different platforms download the documents from the cloud server to the local for editing, and upload the documents to the cloud server after the editing is completed, so that the cross-platform collaborative production is realized. In order to ensure the security of the data, the rights of different users to the same document may not be the same. In the prior art, identity recognition is generally performed by adopting an account number and password mode, and then corresponding editing authorities are opened for users participating in editing according to the recognized identity.
However, in different platforms, the convenience of logging in by using the account number and password is not consistent, sometimes, a user may only need to check a document in collaborative production on a mobile phone or a tablet, and if the identity recognition is continuously performed by adopting the account number and password, the convenience of checking is affected, and the user experience is poor.
Disclosure of Invention
The invention aims to disclose a cross-platform collaborative making system, which solves the problem of how to improve the convenience degree of identity recognition when users collaborate with office documents on different platforms.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a cross-platform collaborative manufacturing system comprises a detection module, an identity recognition module, an editing module and a cloud server;
the detection module is used for detecting the type of the equipment currently used by the user and acquiring available hardware of the equipment;
the identity recognition module is used for providing identity verification service for the user based on the type of the equipment and available hardware, and the identity verification service is used for determining whether the user has collaborative making authority;
the editing module is used for downloading the target document from the cloud server when the user has the collaborative making right, editing or viewing the downloaded target document, and sending the edited target document to the cloud server;
the cloud server is used for storing the target document.
Preferably, the device type includes any one of a computer, a tablet, and a cell phone.
Preferably, the available hardware includes one or more of a touch screen, a keyboard, and a front-facing camera.
Preferably, providing authentication services to a user based on the type of device and available hardware includes:
acquiring a corresponding identity verification mode based on the type of the equipment and available hardware;
and authenticating the user based on the authentication mode, and judging whether the user has the authority of collaborative making.
Preferably, the acquiring the corresponding authentication mode based on the type of the device and available hardware includes:
if the type of the equipment is a mobile phone or a tablet or a computer and the available hardware comprises a front camera, the identity authentication mode is face recognition authentication;
if the type of the equipment is a mobile phone or a tablet or a computer and the available hardware does not comprise a front-end camera, the identity authentication mode is account password authentication.
Preferably, the cloud server is further configured to store editing rights of each user to the target document.
Preferably, the editing module comprises an input unit, a downloading unit, an editing unit and an uploading unit;
the input unit is used for inputting document information of the target document by a user with collaborative making authority;
the downloading unit is used for sending the document information and the user information to the cloud server, and receiving a target document sent back by the cloud server according to the document information and editing permission sent back according to the user information;
the editing unit is used for limiting the user to view or edit the target document within the range of the editing authority;
the uploading unit is used for sending the edited target document to the cloud server.
Preferably, the document information includes a document name and a document number.
Preferably, the identity recognition module is further used for acquiring user information of the user when the identity recognition module provides the identity verification service for the user.
Preferably, the user information includes any one of a name, an employee number, a mobile phone number, and an identification card number.
In the step of performing the authority identification of cross-platform collaborative production, the method adopts the mode of determining the authority verification service based on the equipment type and available hardware, so that a user can perform the authority verification in the most convenient verification mode under the condition of hardware support, and the user experience is improved.
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The present disclosure will become more fully understood from the detailed description given herein below and the accompanying drawings, which are given by way of illustration only, and thus are not limiting of the present disclosure, and wherein:
FIG. 1 is a schematic diagram of a cross-platform collaborative fabrication system according to the present invention.
Fig. 2 is a schematic diagram of a process of acquiring a face image of a user according to the present invention.
Description of the embodiments
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
The invention provides a cross-platform collaborative manufacturing system, which is provided with a detection module, an identity recognition module, an editing module and a cloud server, wherein the detection module is used for detecting the identity of a user;
the detection module is used for detecting the type of the equipment currently used by the user and acquiring available hardware of the equipment;
the identity recognition module is used for providing identity verification service for the user based on the type of the equipment and available hardware, and the identity verification service is used for determining whether the user has collaborative making authority;
the editing module is used for downloading the target document from the cloud server when the user has the collaborative making right, editing or viewing the downloaded target document, and sending the edited target document to the cloud server;
the cloud server is used for storing the target document.
In the step of performing the authority identification of cross-platform collaborative production, the method adopts the mode of determining the authority verification service based on the equipment type and available hardware, so that a user can perform the authority verification in the most convenient verification mode under the condition of hardware support, and the user experience is improved.
The face recognition can be completed by shooting the equipment against the face, more characters are required to be input in the account password mode, and obviously the face recognition is inconvenient on smaller equipment such as a mobile phone, so that the face recognition mode is more convenient and faster under the condition.
Preferably, the device type includes any one of a computer, a tablet, and a cell phone.
Specifically, the types of devices may also include other devices capable of editing documents, such as smart televisions, television boxes, and the like.
Preferably, the available hardware includes one or more of a touch screen, a keyboard, and a front-facing camera.
In particular, the available hardware is the hardware that is present on the device. The available hardware for different devices may not be the same. For example, some computers have front-facing cameras, while some computers do not. In addition to the types of hardware listed above, the available hardware may also include fingerprint recognition devices, iris recognition devices, and the like.
Preferably, providing authentication services to a user based on the type of device and available hardware includes:
acquiring a corresponding identity verification mode based on the type of the equipment and available hardware;
and authenticating the user based on the authentication mode, and judging whether the user has the authority of collaborative making.
Specifically, the identity verification mode is obtained by selecting based on comprehensive consideration of the type of the equipment and available hardware, and the most convenient identity verification mode is obtained.
Preferably, the acquiring the corresponding authentication mode based on the type of the device and available hardware includes:
if the type of the equipment is a mobile phone or a tablet or a computer and the available hardware comprises a front camera, the identity authentication mode is face recognition authentication;
if the type of the equipment is a mobile phone or a tablet or a computer and the available hardware does not comprise a front-end camera, the identity authentication mode is account password authentication.
In particular, compared with the verification mode of the account password, the verification mode of the face recognition is higher in convenience, so that when the front-facing camera is detected to be arranged on equipment used by a user, the face recognition is adopted for recognition.
Preferably, the identity recognition module comprises a storage unit and a face recognition unit;
the storage unit is used for storing the identity verification information of all users with collaborative making authority, wherein the identity verification information comprises an account number, a password, a face image and user information;
the face recognition unit is used for carrying out identity authentication on the user in a face recognition authentication mode.
Preferably, the authentication of the user by adopting a face recognition authentication mode comprises the following steps:
and acquiring a face image of the user, and comparing the face image with the face image in the storage unit, so as to determine whether the user has the collaborative making authority.
Preferably, acquiring a face image of a user includes:
continuously shooting the face of the user to obtain a face image set Q;
and calculating the face image set Q to obtain a face image of the user.
Specifically, continuous shooting can obtain face images of a plurality of users in a short time. The image most conforming to the set condition can be selected as the final face image by calculating the set Q. Compared with a single shooting mode, the method and the device can improve the probability of obtaining the face image with high quality, so that the probability of obtaining a correct verification result by a user for single identity verification is improved, and the user experience is improved.
Preferably, shooting the face of the user continuously to obtain a face image set Q includes:
calculating the offset coefficient of the face image once every fixed number of sheets;
if the offset coefficient of the face image is larger than the set coefficient threshold or the accumulated duration of continuous shooting reaches the set duration threshold, stopping shooting to obtain a face image set Q.
Specifically, there are two end conditions for continuous shooting in the present invention, and any trigger stops shooting. The first end condition is that the accumulated time length reaches a set time length threshold value, which is a condition for ending continuous shooting in a relatively conventional way. The second end is that the offset coefficient is larger than the set coefficient threshold, and because the head of the user may move slightly in the continuous shooting process, the continuous shooting can be stopped when the moving amplitude is larger by using the offset coefficient, and the invention further needs to calculate the images in the set Q, if the amplitude is too large, the acquisition of the detection area in the process of calculating the set Q cannot be smoothly performed, so that the face image of the user is not beneficial to being obtained from the set Q quickly.
Preferably, the offset coefficient of the face image is calculated once every fixed number of sheets, including:
by using
Figure SMS_1
Representing the first face image, the offset coefficient of the t-th face image is:
Figure SMS_2
in the formula (i),
Figure SMS_3
for the offset coefficient of the t-th face image, < >>
Figure SMS_4
The center coordinates of the detection area of the t-th face image; />
Figure SMS_5
Is the center coordinates of the detection area of the first face image.
Specifically, the fixed number of sheets may be 3 sheets, 4 sheets, 5 sheets, etc., and specific numerical values may be set according to actual situations. The offset coefficient is mainly obtained by calculating the change between the center coordinates of the detection areas of the two face images, and the larger the offset coefficient is, the larger the amplitude of the head movement of the user is, and the larger the shooting ending probability is. The offset coefficient is calculated after the fixed number of sheets is set, so that the offset coefficient has enough calculation time to calculate, the calculation pressure is reduced, and the offset of the head of the user is generally smaller between two adjacent face images, so that the continuous shooting can be stopped in time by the fixed number of sheets.
Preferably, the method for acquiring the detection area of the first face image includes:
for the first face image
Figure SMS_6
Partitioning is performed, will->
Figure SMS_7
Dividing the space into K rectangular areas with the same area;
calculating a representative coefficient of each region belonging to the face part of the user;
wherein, the calculation function of the representative coefficient is:
Figure SMS_8
Figure SMS_9
representing coefficient of region d represented in human face part of user, < ->
Figure SMS_12
Representing the ratio value->
Figure SMS_15
，
Figure SMS_11
For the set of other regions adjacent to region d, +.>
Figure SMS_14
Variance of gray value for pixel in region k +.>
Figure SMS_16
Is the variance of the gray value of the pixel in region d +.>
Figure SMS_17
Variance of gradient value for pixel point in region k +.>
Figure SMS_10
Variance of gradient values for pixel points in region d; n is->
Figure SMS_13
The number of regions in (a);
and taking the area with the largest representative coefficient as a detection area of the first face image.
Since the face region needs to be identified later, the present aspect only calculates the representative coefficient for the region belonging to the face portion of the user, thereby improving the efficiency of acquiring the detection region. Specifically, if a region includes pixels of a skin portion of a face, the region is a region belonging to the face portion of the user. The detection region is obtained for calculating the offset coefficient, so that the invention respectively carries out comprehensive calculation from the variance of the gray value and the variance of the gradient value to obtain the representative coefficient, and if the difference between one region and the surrounding region in terms of the gray value variance and the gradient value variance is larger, the representativeness of the region is better. And after the area with the best representativeness is selected, the detection area can be obtained quickly and accurately when the detection area is extracted from other face images. Because if the representativeness is small, the detection area of other face images is difficult to obtain, that is, a plurality of windows to be screened with very high similarity may exist in a plurality of windows to be screened obtained by taking the window to be screened as the center of the sliding window, so that the offset coefficient cannot be accurately and rapidly calculated.
Preferably, the method for acquiring the detection area of the t-th face image includes:
for the t-th face image
Figure SMS_18
Performing image difference processing to obtain the t-th face image and +.>
Figure SMS_19
Total number of pixels with different gray values +.>
Figure SMS_20
；
Calculating a variation coefficient:
Figure SMS_21
calculating the radius:
Figure SMS_22
wherein,,
Figure SMS_23
for the radius used when the acquisition of the detection area is performed in the t-th face image,
Figure SMS_24
the maximum value of the side length of the detection area of the first face image; />
Figure SMS_25
The total number of pixel points in the t-th face image;
using pairs of windows of the same size as the detection area of the first face image
Figure SMS_26
Is the center of a circle>
Figure SMS_27
Sliding window detection is carried out for the pixel points within the radius range, so that a plurality of windows to be screened are obtained;
and respectively calculating the similarity between each window to be screened and the detection area of the first face image, wherein the pixel point corresponding to the window to be screened with the highest similarity is used as the pixel point of the detection area of the t-th face image.
For the t-th face image, the change range of the central pixel point of the window to be screened is obtained through the change coefficient and the radius, and the radius can be increased along with the increase of the change coefficient by the arrangement mode, so that the situation that too many windows to be screened are obtained when the change coefficient is smaller is avoided, and the calculation pressure is reduced. The radius can be changed along with the change, so that the method does not need to set the change range of the central pixel point of the window to be screened in advance, thereby reducing the implementation difficulty of the method and improving the adaptability of the method.
Preferably, as shown in fig. 2, the face image set Q is calculated to obtain a face image of a user, including:
based on the first face image
Figure SMS_28
Acquiring a calculation region;
calculating the competitiveness coefficient of each face image in the face image set Q based on the calculation region respectively;
and taking the face image with the largest competitive coefficient as the face image of the user.
Specifically, the competitiveness is not calculated according to the attributes of all the pixels, but calculated according to the calculation region. The efficiency of obtaining the face image of the user from the set Q can be improved.
Preferably based on the first face image
Figure SMS_29
Acquiring a calculation region, including:
by using
Figure SMS_30
Representing the first face image +.>
Figure SMS_31
Represents the region with the largest coefficient;
acquiring distances in all areas with representative coefficients
Figure SMS_32
Furthest region->
Figure SMS_33
；
Acquiring the distance between the region with the representative coefficient and the region
Figure SMS_34
And->
Figure SMS_35
The sum of the distances between is the largestZone->
Figure SMS_36
；
Will be
Figure SMS_37
、/>
Figure SMS_38
And->
Figure SMS_39
As a calculation region.
Specifically, the calculated area is obtained by calculating the distance between the representative coefficient and the area, firstly obtaining the most representative area by the representative coefficient, and then selecting the distance
Figure SMS_40
The furthest area with the representative coefficient and finally the area with the largest distance between the two areas selected before are selected, and the selection mode ensures that the calculation area comprises representative pixel points and range pixel points, so that the competitiveness of the face part of the face image is comprehensively represented from two different aspects.
Preferably, the calculation function of the competitiveness coefficient is:
Figure SMS_41
in the function of the method,
Figure SMS_44
is the competitive coefficient of the face image q, < +.>
Figure SMS_45
Is->
Figure SMS_49
、/>
Figure SMS_43
And->
Figure SMS_47
Set of->
Figure SMS_48
And->
Figure SMS_50
Respectively calculating the minimum and maximum values of the gray values in region j, +.>
Figure SMS_42
Is the total number of pixel points with gray value of i, < >>
Figure SMS_46
To calculate the total number of pixels in region j.
The competition coefficient is calculated by the accumulated sum of the probabilities of different gray values of the pixel points in the three areas, and the larger the accumulated sum of the probabilities of different gray values is, the larger the competition coefficient is, the more abundant the image details in the face image are, so that the face image with the most abundant image details in the set Q is selected as the face image of the user.
Preferably, the identity recognition module further comprises an account password recognition unit;
the account password identification unit is used for carrying out authentication on the user in an account password authentication mode.
Specifically, the account password identification unit is used for acquiring an account and a password input by a user, and comparing the account and the password input by the user with the account and the password stored in the storage unit, so as to determine whether the user has collaborative making permission.
Preferably, the cloud server is further configured to store editing rights of each user to the target document.
Specifically, for the same target document, different editing authorities can be set for different users, for example, a certain user can be limited to only view the target document and not edit the target document; the range of pages that the user can edit may be limited.
Preferably, the editing module comprises an input unit, a downloading unit, an editing unit and an uploading unit;
the input unit is used for inputting document information of the target document by a user with collaborative making authority;
the downloading unit is used for sending the document information and the user information to the cloud server, and receiving a target document sent back by the cloud server according to the document information and editing permission sent back according to the user information;
the editing unit is used for limiting the user to view or edit the target document within the range of the editing authority;
the uploading unit is used for sending the edited target document to the cloud server.
Specifically, the cloud service performs database retrieval based on the document information after receiving the document information, so as to obtain a target document, then retrieves editing rights of a user according to the user information, and finally sends the editing rights and the target document to the downloading unit.
Preferably, the document information includes a document name and a document number.
Preferably, the identity recognition module is further used for acquiring user information of the user when the identity recognition module provides the identity verification service for the user.
Specifically, the identity recognition module stores the identity verification information of all users with collaborative making authority, wherein the identity verification information comprises an account number password, a face image and user information. And when the account password verification passes or the face recognition verification passes, the corresponding user information is sent to the editing module.
Preferably, the user information includes any one of a name, an employee number, a mobile phone number, and an identification card number.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (10)

1. The cross-platform collaborative manufacturing system is characterized by comprising a detection module, an identity recognition module, an editing module and a cloud server;
the detection module is used for detecting the type of the equipment currently used by the user and acquiring available hardware of the equipment;
the identity recognition module is used for providing identity verification service for the user based on the type of the equipment and available hardware, and the identity verification service is used for determining whether the user has collaborative making authority;
the editing module is used for downloading the target document from the cloud server when the user has the collaborative making right, editing or viewing the downloaded target document, and sending the edited target document to the cloud server;
the cloud server is used for storing the target document.
2. The cross-platform co-production system of claim 1, wherein the device type comprises any one of a computer, a tablet, and a cell phone.
3. The cross-platform co-production system of claim 2, wherein the available hardware comprises one or more of a touch screen, a keyboard, and a front-facing camera.
4. A cross-platform co-production system according to claim 3, wherein providing authentication services to users based on the type of device and available hardware comprises:
acquiring a corresponding identity verification mode based on the type of the equipment and available hardware;
and authenticating the user based on the authentication mode, and judging whether the user has the authority of collaborative making.
5. The cross-platform collaborative fabrication system according to claim 4, wherein obtaining a corresponding authentication mode based on a type of device and available hardware comprises:
if the type of the equipment is a mobile phone or a tablet or a computer and the available hardware comprises a front camera, the identity authentication mode is face recognition authentication;
if the type of the equipment is a mobile phone or a tablet or a computer and the available hardware does not comprise a front-end camera, the identity authentication mode is account password authentication.
6. The cross-platform collaborative production system of claim 1, wherein the cloud server is further configured to store editing rights for each user to a target document.
7. The cross-platform collaborative fabrication system according to claim 6, wherein the editing module includes an input unit, a download unit, an editing unit, and an upload unit;
the input unit is used for inputting document information of the target document by a user with collaborative making authority;
the downloading unit is used for sending the document information and the user information to the cloud server, and receiving a target document sent back by the cloud server according to the document information and editing permission sent back according to the user information;
the editing unit is used for limiting the user to view or edit the target document within the range of the editing authority;
the uploading unit is used for sending the edited target document to the cloud server.
8. The cross-platform collaborative production system of claim 7, wherein the document information includes a document name and a document number.
9. The cross-platform collaborative manufacturing system according to claim 7, wherein the identity module is further configured to obtain user information of a user while providing authentication services to the user.
10. The cross-platform collaborative manufacturing system according to claim 9, wherein the user information includes any one of a name, employee number, cell phone number, and identification number.
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