CN110610164A - Face image processing method, system, server and readable storage medium - Google Patents
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Abstract
The invention discloses a face image processing method, a system, a server and a readable storage medium, wherein the face image processing method comprises the following steps: receiving image information uploaded by a first terminal, and preprocessing the image information; extracting a face image from the image information according to the preprocessed image information; and clustering the face images, and storing clustering results in a database. The image information is preprocessed, the face images of the users are extracted, the face images matched with the users are correspondingly clustered, clustering results are obtained and stored in the database, similar or identical face images can be rapidly clustered through the clustering processing, if the users need to download, the corresponding face images can be rapidly obtained through the clustering results, and therefore the efficiency of processing the image information by the server is improved.
Description
Technical Field
The invention relates to the technical field of image recognition, in particular to a face image processing method, a face image processing system, a server and a readable storage medium.
Background
With the development of society, many large and medium-sized events and other events appear on the market. For example, in marathon events, hundreds of thousands of people are gathered in the event, in order to better monitor the contestants, a live photographer or a roadside monitoring camera needs to take face images of the contestants, a large number of face images taken are uploaded to a server, and a user can download corresponding target face images to the server by uploading the face images of the user.
Since current image processing systems take a significant amount of time to process a large number of photographs in a large activity. When the server receives a large number of photos, the face images corresponding to the users need to be searched from the large number of photos and distributed to the users, and the problem that the face image information processing efficiency of the users is low is caused.
Disclosure of Invention
The invention mainly aims to provide a face image processing method, a face image processing system, a server and a readable storage medium, and aims to solve the technical problem of low face image processing efficiency in a large-scale event.
In order to achieve the above object, the present invention provides a face image processing method, including:
receiving image information uploaded by a first terminal, and preprocessing the image information;
extracting a face image from the image information according to the preprocessed image information;
and clustering the face images, and storing clustering results in a database.
Further, the step of receiving the image information uploaded by the first terminal and preprocessing the image information includes:
judging whether the image information contains a face area meeting a preset condition or not according to the received image information;
if the image information meets the preset condition, intercepting partial image information including the face in a preset size frame;
and compressing the partial image information.
Further, the step of determining whether the image information includes a face region meeting a preset condition according to the received image information includes:
extracting the human face features in the image information;
calculating the face characteristic value according to the face characteristic, and judging whether the face characteristic value is greater than or equal to a preset definition threshold value;
and if the face characteristic value is greater than or equal to a preset definition threshold value, judging that the image information contains a face region meeting the preset condition.
Further, the step of extracting a face image from the image information according to the preprocessed image information includes:
and traversing the image information, and extracting one or more face images in the image information.
Further, the step of clustering the face images and storing the clustering result in a database includes:
dividing the plurality of face images into a plurality of data blocks, clustering the face images of each data block, and acquiring a plurality of clustering sub-results;
calculating the clustering result corresponding to the face image according to the plurality of clustering sub-results;
and storing the clustering result in the database.
Further, after the step of storing the clustering result in the database, the method comprises:
receiving a user face image uploaded by a second terminal;
judging whether the face image of the user is matched with the face image in the clustering result;
and if the user face image is matched with the face image of the clustering result, sending a target face image matched with the user face image to the second terminal.
Further, before the step of receiving the image information uploaded by the first terminal and preprocessing the image information, the method includes:
establishing communication connection with the searched first terminal;
acquiring a user account uploaded by the first terminal and judging whether account information of the user exists in a preset authority list or not;
and if the user account exists in the preset authority list, allowing the user account to upload the image information.
The invention also provides a face image processing system, which comprises:
the receiving module is used for receiving the image information uploaded by the first terminal and preprocessing the image information;
the extraction module is used for extracting a face image from the image information according to the preprocessed image information;
and the clustering module is used for clustering the face images and storing clustering results in a database.
The present invention also provides a server, comprising: the human face image processing method comprises a memory, a processor and a program stored on the memory and capable of running on the processor, wherein the human face image processing program realizes the steps of the human face image processing method when being executed by the processor.
The invention also provides a readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps of the face image processing method as described above.
The face image processing method provided by the embodiment of the invention receives the image information uploaded by the first terminal and preprocesses the image information; extracting a face image from the image information according to the preprocessed image information; and clustering the face images, and storing clustering results in a database. The image information is preprocessed, the face images of the users are extracted, the face images matched with the users are correspondingly clustered, clustering results are obtained and stored in the database, similar or identical face images can be rapidly clustered through the clustering processing, if the users need to download, the corresponding face images can be rapidly obtained through the clustering results, and therefore the efficiency of processing the image information by the server is improved.
Drawings
FIG. 1 is a schematic diagram of a hardware-operating server according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a first embodiment of a face image processing method according to the present invention;
fig. 3 is a schematic diagram of a framework structure of an embodiment of a face image processing system according to the invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, fig. 1 is a schematic diagram of a server structure of a hardware operating environment according to an embodiment of the present invention.
The server can be a computer or a smart phone.
As shown in fig. 1, the server may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the server architecture shown in FIG. 1 is not meant to be limiting, and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a face image processing program.
In the server shown in fig. 1, the network interface 1004 is mainly used for connecting to a backend server and performing data communication with the backend server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and the processor 1001 may be configured to call the face image processing program stored in the memory 1005, and perform the following operations:
receiving image information uploaded by a first terminal, and preprocessing the image information;
extracting a face image from the image information according to the preprocessed image information;
and clustering the face images, and storing clustering results in a database.
Further, the step of receiving the image information uploaded by the first terminal and preprocessing the image information includes:
judging whether the image information contains a face area meeting a preset condition or not according to the received image information;
if the image information meets the preset condition, intercepting partial image information including the face in a preset size frame;
and compressing the partial image information.
Further, the step of determining whether the image information includes a face region meeting a preset condition according to the received image information includes:
extracting the human face features in the image information;
calculating the face characteristic value according to the face characteristic, and judging whether the face characteristic value is greater than or equal to a preset definition threshold value;
and if the face characteristic value is greater than or equal to a preset definition threshold value, judging the face region of which the image information meets the preset condition.
Further, the step of extracting a face image from the image information according to the preprocessed image information includes:
and traversing the image information, and extracting one or more face images in the image information.
Further, the step of clustering the face images and storing the clustering result in a database includes:
dividing the plurality of face images into a plurality of data blocks, clustering the face images of each data block, and acquiring a plurality of clustering sub-results;
calculating the clustering result corresponding to the face image according to the plurality of clustering sub-results;
and storing the clustering result in the database.
Further, the processor 1001 may call the face image processing program stored in the memory 1005, and also perform the following operations:
receiving a user face image uploaded by a second terminal;
judging whether the face image of the user is matched with the face image in the clustering result;
and if the user face image is matched with the face image of the clustering result, sending a target face image matched with the user face image to the second terminal.
Further, the processor 1001 may call the face image processing program stored in the memory 1005, and also perform the following operations: establishing communication connection with the searched first terminal;
acquiring a user account uploaded by the first terminal and judging whether account information of the user exists in a preset authority list or not;
and if the user account exists in the preset authority list, allowing the user account to upload the image information.
Based on the hardware structure, the invention provides various embodiments of the task scheduling method.
Referring to fig. 2, in a first embodiment of the face image processing method of the present invention, the face image processing method includes:
step S10, receiving the image information uploaded by the first terminal and preprocessing the image information;
the server can receive the image information uploaded by one or more first terminals and preprocess the image information, wherein the preprocessing is to compress the image information. The first terminal may be a PC, or may be a mobile terminal device having a display function, such as a smart phone, a tablet computer, an e-book reader, an MP3 player, an MP4 player, or a portable computer. Specifically, the image information includes a face image. In this embodiment, the server may receive the image information uploaded by the first terminal in real time and preprocess the image information in real time, and the server may also receive the image information uploaded by the first terminal within a preset time and preprocess the image information within the preset time, where the preset time may be set to 5 seconds.
Step S20, extracting a face image from the image information according to the preprocessed image information;
and the server extracts the face image from the image information according to the preprocessed image information. Specifically, the image information includes images of one or more users, and facial images of the one or more users can be extracted according to the image information.
And step S30, clustering the face images, and storing the clustering result in a database.
The server may cluster one or more facial images and store the clustering results in a database. In this embodiment, the server may cluster a plurality of similar or identical facial images together, and store the plurality of similar or identical facial images together in the database. For example, the server acquires a plurality of facial images of the same user, clusters the plurality of facial images of the user to obtain a clustering result of the plurality of facial images of the user, and stores the clustering result in the database.
The face image processing method provided by the embodiment of the invention receives the image information uploaded by the first terminal and preprocesses the image information; extracting a face image from the image information according to the preprocessed image information; and clustering the face images, and storing clustering results in a database. The image information is preprocessed, the face images of the users are extracted, the face images matched with the users are correspondingly clustered, clustering results are obtained and stored in the database, similar or identical face images can be rapidly clustered through the clustering processing, if the users need to download, the corresponding face images can be rapidly obtained through the clustering results, and therefore the efficiency of processing the image information by the server is improved.
Further, in step S10 of the first embodiment, the step of receiving the image information uploaded by the first terminal and preprocessing the image information includes:
step S11, judging whether the image information accords with the human face with the preset condition according to the received image information;
step S12, if the image information meets the preset condition, intercepting partial image information including human face in a preset size frame;
in step S13, the partial image information is compressed.
The server judges whether the image information contains a face area meeting preset conditions or not according to the received image information, can discard the non-meeting image information and process the meeting image information. If the image information contains a face area meeting the preset condition, capturing partial image information containing the face in a preset size frame, and if the image information does not meet the face area meeting the preset condition, discarding the image information. Therefore, the server is prevented from processing the fuzzy or half face image shot by the first terminal when receiving the fuzzy or half face image, the server can discard the unqualified face image, and the processing efficiency of the server is improved.
In this embodiment, for image information that meets a preset condition, the outline of a human face is used to intercept partial image information of the human face, the obtained partial image is compressed, and other partial image information is discarded. For example, the server acquires the image information of the whole user, wherein the server only intercepts the face in the face contour range of the user, compresses the face, and discards the image information of other parts, so that a clear face image of the user can be quickly acquired.
Further, step S11 includes:
step S111, extracting the face features in the image information;
step S112, calculating a face characteristic value according to the face characteristics, and judging whether the face characteristic value is greater than or equal to a preset definition threshold value or not;
in step S112, if the face feature value is greater than or equal to the preset sharpness threshold, it is determined that the image information includes a face region meeting the preset condition.
The server extracts the face features in the image information, calculates a face feature value according to the face features, judges whether the face feature value is larger than or equal to a preset definition threshold value or not, and judges that the image information contains a face area meeting preset conditions if the face feature value is larger than or equal to the preset definition threshold value; and if the face characteristic value is smaller than the preset definition threshold value, judging that the image information contains a face region which does not accord with the preset condition. For example, when the face image of the user is blurred, it indicates that the sharpness of the face image does not meet the preset condition. Wherein, the definition threshold is a definition for indicating a face feature, and the preset definition threshold may be 80%. Therefore, the server can screen out fuzzy or non-face image photos, the processing of the server on image information can be reduced, and the efficiency of the server for processing the face images is improved.
Further, in step S20 of the first embodiment, the step of extracting a face image from the image information based on the image information after the preprocessing includes:
step S21, the image information is traversed, and one or more face images located in the image information are extracted.
The server receives image information shot by the first terminal, wherein the image information can comprise one or more face images, traverses the image information, obtains one face image or a plurality of face images according to the traversed image information, and extracts one or more face images in the image information.
Further, in step S30 of the first embodiment, the clustering the face images and storing the clustering result in the database includes:
step S31, dividing a plurality of face images into a plurality of data blocks, clustering the face images of each data block, and acquiring a plurality of clustering sub-results;
step S32, calculating a clustering result corresponding to the face image according to the plurality of clustering sub-results;
step S33, the clustering result is stored in the database.
The server divides the plurality of face images into a plurality of data blocks, carries out face image clustering on each data block, obtains a plurality of clustering sub-results, calculates the clustering result corresponding to the face images according to the plurality of clustering sub-results, and stores the clustering result in a database. Wherein, the clustering result is to cluster a plurality of similar or same face images together. In this embodiment, the server includes a plurality of threads, each thread may process a plurality of data blocks in parallel, cluster face images similar or identical to each data block together to obtain a plurality of cluster sub-results, calculate a cluster result corresponding to a face image according to a plurality of cluster sub-result, and store the cluster result in the database. For example, the first thread processes a first data block, the second thread processes a second data block, the third thread processes a third data block, each data block is subjected to face image clustering to obtain a first clustering result, a second clustering result and a third clustering result respectively, the first clustering result, the second clustering result and the third clustering result are clustered to obtain a clustering result, and the clustering result is stored in the database. Therefore, the information of the plurality of facial images is divided into the plurality of data blocks and distributed to the plurality of threads of the server for clustering, and the efficiency of the server for processing the plurality of facial images can be improved.
Further, in the second embodiment of the facial image processing method of the present invention, after the step of storing the clustering result in the database, the method includes:
step S311, receiving a user face image uploaded by a second terminal;
judging whether the face image of the user is matched with the face image in the clustering result;
and if the face image of the user is matched with the face image of the clustering result, sending a target face image matched with the face image of the user to the second terminal.
The server receives a user face image uploaded by the second terminal, judges whether the user face image is matched with a face image in the clustering result or not, and sends a target face image matched with the user face image to the second terminal if the user face image is matched with the face image in the clustering result; and if the facial image of the user is not matched with the facial image of the clustering result, the server sends a failure message to the second terminal. The second terminal may be a PC, or may be a mobile terminal device having a display function, such as a smart phone, a tablet computer, an e-book reader, an MP3 player, an MP4 player, or a portable computer. For example, taking marathon as an example, a photographer or a monitoring camera uploads image information of all players participating in a game, which is shot by a first terminal, to a server, after the game is finished, players can shoot the image information of their faces through a second terminal and upload the image information to the server, the server calls a face image in a database through the face to perform matching, and if the matching is successful, a target face image matched with the face is sent to the second terminal. Therefore, the server can be matched with the clustering result according to the user face image, the target face image corresponding to the user face image can be quickly matched and sent to the second terminal, and therefore the efficiency of distributing the target face image by the server can be improved.
Further, in a third embodiment of the method for processing a face image according to the present invention, before the step of receiving image information uploaded by a first terminal and preprocessing the image information, the method includes:
step A, establishing communication connection with a searched first terminal;
step B, acquiring a user account uploaded by the first terminal and judging whether account information of the user exists in a preset authority list or not;
and C, if the user account exists in the preset authority list, allowing the user account to upload the image information.
The server establishes communication connection with the searched first terminal, acquires a user account uploaded by the first terminal and judges whether account information of a user exists in a preset authority list or not, if the user account exists in the preset authority list, the user account is allowed to upload image information to the server, and if the user account does not exist in the preset authority list, the user account is refused to log in. In this embodiment, the server establishes a wireless communication connection with the searched first terminal, and the user may register an account on a login page on the first terminal in advance and store the account in the permission list. When a user logs in through the registered account information, whether the user account exists in a preset authority list or not is judged, and if the user account exists in the preset authority list, the user account is allowed to upload image information to a server. Therefore, the server can shield the image information uploaded by other strange users and only accept the image information uploaded by the corresponding user, so that the server can avoid receiving and processing unnecessary image information, and further improve the processing of the server on the image information.
In an embodiment, as shown in fig. 3, fig. 3 is a schematic diagram of a framework structure of an embodiment of a face image processing system 40 of the present invention, including: the receiving module 41, the extracting module 42 and the clustering module 43 are configured to:
a receiving module 41, configured to receive image information uploaded by a first terminal, and perform preprocessing on the image information;
an extracting module 42, configured to extract a face image from the image information according to the preprocessed image information;
and the clustering module 43 is configured to cluster the face images and store the clustering result in a database.
For the specific limitation of the face image processing system, reference may be made to the above limitation on the face image processing method, and details are not described here. All or part of the modules in the face image processing system can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
Furthermore, an embodiment of the present invention further provides a readable storage medium (i.e., a computer readable memory), where a face image processing program is stored on the readable storage medium, and when executed by a processor, the face image processing program implements the following operations:
receiving image information uploaded by a first terminal, and preprocessing the image information;
extracting a face image from the image information according to the preprocessed image information;
and clustering the face images, and storing clustering results in a database.
Further, the step of receiving the image information uploaded by the first terminal and preprocessing the image information includes:
judging whether the image information contains a face area meeting a preset condition or not according to the received image information;
if the image information meets the preset condition, intercepting partial image information including the face in a preset size frame;
and compressing the partial image information.
Further, the step of determining whether the image information includes a face region meeting a preset condition according to the received image information includes:
extracting the human face features in the image information;
calculating the face characteristic value according to the face characteristic, and judging whether the face characteristic value is greater than or equal to a preset definition threshold value;
and if the face characteristic value is greater than or equal to a preset definition threshold value, judging the face region of which the image information meets the preset condition.
Further, the step of extracting a face image from the image information according to the preprocessed image information includes:
and traversing the image information, and extracting one or more face images in the image information.
Further, the step of clustering the face images and storing the clustering result in a database includes:
dividing the plurality of face images into a plurality of data blocks, clustering the face images of each data block, and acquiring a plurality of clustering sub-results;
calculating the clustering result corresponding to the face image according to the plurality of clustering sub-results;
and storing the clustering result in the database.
Further, the face image processing program, when executed by the processor, further implements the following operations: receiving a user face image uploaded by a second terminal;
judging whether the face image of the user is matched with the face image in the clustering result;
and if the user face image is matched with the face image of the clustering result, sending a target face image matched with the user face image to the second terminal.
Further, the face image processing program, when executed by the processor, further implements the following operations:
establishing communication connection with the searched first terminal;
acquiring a user account uploaded by the first terminal and judging whether account information of the user exists in a preset authority list or not;
and if the user account exists in the preset authority list, allowing the user account to upload the image information.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a server device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A face image processing method is characterized by comprising the following steps:
receiving image information uploaded by a first terminal, and preprocessing the image information;
extracting a face image from the image information according to the preprocessed image information;
and clustering the face images, and storing clustering results in a database.
2. The method for processing the human face image according to claim 1, wherein the step of receiving the image information uploaded by the first terminal and preprocessing the image information comprises the steps of:
judging whether the image information contains a face area meeting a preset condition or not according to the received image information;
if the image information meets the preset condition, intercepting partial image information comprising the face by using a preset size frame;
and compressing the partial image information.
3. The method for processing a human face image according to claim 2, wherein the step of determining whether the image information contains a human face region meeting a preset condition according to the received image information comprises:
extracting the human face features in the image information;
calculating the face characteristic value according to the face characteristic, and judging whether the face characteristic value is greater than or equal to a preset definition threshold value;
and if the face characteristic value is greater than or equal to a preset definition threshold value, judging that the image information contains a face region meeting the preset condition.
4. The method for processing human face image according to claim 1, wherein said step of extracting human face image from said image information after said preprocessing comprises:
and traversing the image information, and extracting one or more face images in the image information.
5. The method of claim 4, wherein the step of clustering the face images and storing the clustering results in a database comprises:
dividing the plurality of face images into a plurality of data blocks, clustering the face images of each data block, and acquiring a plurality of clustering sub-results;
calculating the clustering result corresponding to the face image according to the plurality of clustering sub-results;
and storing the clustering result in the database.
6. The method of processing a face image according to claim 5, wherein the step of storing the clustering result in the database is followed by:
receiving a user face image uploaded by a second terminal;
judging whether the face image of the user is matched with the face image in the clustering result;
and if the user face image is matched with the face image of the clustering result, sending a target face image matched with the user face image to the second terminal.
7. The method for processing the human face image according to claim 1, wherein before the step of receiving the image information uploaded by the first terminal and preprocessing the image information, the method comprises:
establishing communication connection with the searched first terminal;
acquiring a user account uploaded by the first terminal and judging whether account information of the user exists in a preset authority list or not;
and if the user account exists in the preset authority list, allowing the user account to upload the image information.
8. A face image processing system, characterized in that the face image processing system comprises:
the receiving module is used for receiving the image information uploaded by the first terminal and preprocessing the image information;
the extraction module is used for extracting a face image from the image information according to the preprocessed image information;
and the clustering module is used for clustering the face images and storing clustering results in a database.
9. A server, characterized in that the server comprises: a memory, a processor and a program stored on the memory and executable on the processor, the facial image processing program when executed by the processor implementing the steps of the facial image processing method of any one of claims 1 to 7.
10. A readable storage medium, characterized in that the readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the face image processing method according to any one of claims 1 to 7.
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