CN114513583B - Compression uploading method, device, equipment and medium for image data - Google Patents
Compression uploading method, device, equipment and medium for image data Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
- H04N1/00127—Connection or combination of a still picture apparatus with another apparatus, e.g. for storage, processing or transmission of still picture signals or of information associated with a still picture
- H04N1/00204—Connection or combination of a still picture apparatus with another apparatus, e.g. for storage, processing or transmission of still picture signals or of information associated with a still picture with a digital computer or a digital computer system, e.g. an internet server
- H04N1/00209—Transmitting or receiving image data, e.g. facsimile data, via a computer, e.g. using e-mail, a computer network, the internet, I-fax
- H04N1/00222—Transmitting or receiving image data, e.g. facsimile data, via a computer, e.g. using e-mail, a computer network, the internet, I-fax details of image data generation or reproduction, e.g. scan-to-email or network printing
- H04N1/00228—Image push arrangements, e.g. from an image reading device to a specific network destination
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
- H04N1/00127—Connection or combination of a still picture apparatus with another apparatus, e.g. for storage, processing or transmission of still picture signals or of information associated with a still picture
- H04N1/00204—Connection or combination of a still picture apparatus with another apparatus, e.g. for storage, processing or transmission of still picture signals or of information associated with a still picture with a digital computer or a digital computer system, e.g. an internet server
- H04N1/00244—Connection or combination of a still picture apparatus with another apparatus, e.g. for storage, processing or transmission of still picture signals or of information associated with a still picture with a digital computer or a digital computer system, e.g. an internet server with a server, e.g. an internet server
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- H—ELECTRICITY
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- H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
- H04N1/04—Scanning arrangements, i.e. arrangements for the displacement of active reading or reproducing elements relative to the original or reproducing medium, or vice versa
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- Signal Processing (AREA)
- General Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Information Transfer Between Computers (AREA)
Abstract
The embodiment of the invention discloses a compression uploading method, device, equipment and medium of image data. The method is executed by an application end and comprises the steps that a scanning tool electronically scans target data to obtain image data matched with the target data; determining a target compression algorithm adapted to the image data in the alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end; compressing the image data by adopting a target compression algorithm to obtain target compressed image data; and uploading the target compressed image data to a server corresponding to the application end. The technical scheme of the embodiment of the invention provides a new technology for determining an optimal algorithm in various alternative compression algorithms and ensuring that the performance of the whole compression uploading process is optimal.
Description
Technical Field
Embodiments of the present invention relate to computer technologies, and in particular, to a method, an apparatus, a device, and a medium for compressing and uploading image data.
Background
In various business service fields, image data collection and supplementation are necessary steps not only for verifying the authenticity of information of clients, but also for better ensuring the rights and interests of clients.
Generally, after acquiring a customer data, for example, an identification document of a user or various data filled in by the user, a service personnel needs to scan the customer data, compress the scanned result, and upload the compressed result to a matched back-end server for subsequent core service processing. At present, a compression algorithm is determined by service personnel according to experience or a random selection mode, and a scanning result of customer data is compressed based on the compression algorithm.
The operation terminals and operation systems used by different business personnel are different, the network environments are different, and how to determine the optimal algorithm among the alternative compression algorithms, so that the performance of the whole compression uploading process is guaranteed to achieve the optimal compromise of effectiveness and reliability, is an important problem to be solved at present.
Disclosure of Invention
The embodiment of the invention provides a compression uploading method, device, equipment and medium of image data, and provides a new technology for determining an optimal algorithm in alternative compression algorithms and ensuring the optimal performance of the whole compression uploading process.
In a first aspect, an embodiment of the present invention provides a method for compressing and uploading image data, which is executed by an application end, where the method includes:
electronically scanning target data through a scanning tool to acquire image data matched with the target data;
determining a target compression algorithm adapted to the image data in an alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end;
adopting the target compression algorithm to compress the image data to obtain target compressed image data;
and uploading the target compressed image data to a server corresponding to the application end.
In a second aspect, an embodiment of the present invention further provides a compression uploading device for image data, which is executed by an application end, where the device includes:
the image data acquisition module is used for carrying out electronic scanning on target data through a scanning tool to acquire image data matched with the target data;
the compression algorithm determining module is used for determining a target compression algorithm adapted to the image data in an alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end;
The compressed image data acquisition module is used for compressing the image data by adopting the target compression algorithm to obtain target compressed image data;
and the compressed image data uploading module is used for uploading the target compressed image data to a server corresponding to the application end.
In a third aspect, an embodiment of the present invention further provides an electronic device, including:
one or more processors;
storage means for storing one or more computer programs;
the one or more computer programs, when executed by the one or more processors, cause the one or more processors to implement a method for compressed uploading of image data according to any embodiment of the present invention.
In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, where a computer program is stored, where the computer program when executed by a processor implements a method for uploading compressed image data according to any embodiment of the present invention.
According to the embodiment of the invention, the target data is electronically scanned through the scanning tool, so that the image data matched with the target data is obtained; determining a target compression algorithm adapted to the image data in the alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end; compressing the image data by adopting a target compression algorithm to obtain target compressed image data; the method comprises the steps of uploading target compressed image data to a server corresponding to an application end, solving the problems that in the prior art, different operation terminals and operation systems used by different operators are different, and network environments are different, so that an optimal algorithm is not easy to determine in alternative compression algorithms.
Drawings
Fig. 1 is a flowchart of a method for compressing and uploading image data according to a first embodiment of the present invention;
fig. 2A is a flowchart of another method for compressing and uploading image data according to a second embodiment of the present invention;
fig. 2B is a schematic diagram of a specific application scenario of a method for compressing and uploading image data according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a compression uploading device for image data according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
Example 1
Fig. 1 is a flowchart of a compression uploading method of image data according to an embodiment of the present invention, where the embodiment is applicable to a case of compressing and uploading different image data by different platforms, and the method may be executed by an application end. The method can be executed by a compression uploading device of image data, the device can be realized by a mode of software and/or hardware and can be generally integrated in a client or a server, and the method specifically comprises the following steps:
S110, electronically scanning the target data through a scanning tool to acquire image data matched with the target data.
The application may refer to a service application installed on a terminal device (for example, a mobile phone, a tablet computer, or a desktop computer) used by an operator, where the service application is used to implement a set service function.
Taking the service as an insurance service for example, correspondingly, the application end can be an insurance service application program for providing insurance service functions, such as disease insurance, vehicle insurance or accident insurance, etc. Alternatively, the application end may be a function plug-in installed in the service application program, for implementing the function of compressing and uploading the image data in a centralized manner.
The scanning tool is a hardware scanning tool for forming an electronic image of a paper document, for example, a scanner or a high-definition camera. The application end can convert the target data of the paper edition into image data in the form of electronic images by establishing communication connection with the scanning tool.
The target data may refer to any form of paper data. The image data may refer to data in electronic form for converting paper target data by a scanning tool.
In this embodiment, the target data may be scanned by a scanning tool to obtain image data in electronic form, which matches the target data.
S120, determining a target compression algorithm adapted to the image data in an alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end.
The set of alternative compression algorithms may be a pre-built algorithm set including a plurality of alternative compression algorithms, each of which may implement a different compression result, e.g., different alternative compression algorithms may have different compression rates (an amount of data after image data compression divided by an amount of data before compression).
The target compression algorithm may be a compression algorithm selected from a set of alternative compression algorithms that is adapted to the currently processed image data.
The profile types of the target profile may include: identification cards, driver's licenses, medical bills, various auxiliary documents, and the like. It will be appreciated that the image sharpness requirements required for different material types are different, for example, identification documents such as identification cards or driver's licenses require a sufficiently sharp head print and an ID number, while some auxiliary identification documents may only require a relatively sharp signature portion. Therefore, when determining the target compression algorithm, the data type of the target data needs to be used as a reference factor, so as to select a target compression algorithm with a proper compression rate for the target data.
The data type of the target data can be manually input by a user of the application end, so that the application end can acquire the data, or the application end can recognize the text content in the target data through OCR (Optical Character Recognition ) technology after scanning to obtain the image data matched with the target data, and the data type of the target data can be determined according to the recognition result.
The configuration description information of the application end may include: software configuration information, hardware configuration information, and network environment information.
More specifically, the software configuration information may be information such as a type and a version of the application end, and a type and a version of an operating system adapted to a terminal device for installing the service application end.
The hardware configuration information can be the information such as the model of the scanning tool, the model of the terminal equipment for installing the service application end, the memory, the CPU performance and the like. As described above, the lower the compression rate of a compression algorithm, the higher the configuration requirement on the terminal device or the application end, so when selecting the target compression algorithm, the software configuration information and the hardware configuration information can be used as an important reference at the same time, so as to reasonably determine the target compression algorithm on the basis of reasonably utilizing each configuration information of the terminal device or the application end.
The network environment information may be information such as a network speed, a bandwidth, and a packet loss rate of a network to which the application terminal is currently connected. It can be understood that when the network environment is better, for example, the network speed or the bandwidth is more abundant, an algorithm with higher compression rate can be selected to compress the image data, so as to ensure that the back-end server receives a better electronic image; conversely, when the network environment is poor, an algorithm with lower compression rate can be selected to compress the image data, so as to reduce unnecessary occupation of limited network resources.
Optionally, after the image data of the paper target data is obtained through the scanning tool, a target compression algorithm matched with the image data can be determined from the alternative compression algorithm set according to the data type of the target data and in combination with the configuration description information of the application end.
Generally, in order to ensure image details to the greatest extent, the scanning tool generally adopts high-definition scanning, and then the scanned image data generally has large data volume, which is not beneficial to direct storage and transmission. Therefore, before uploading the image data to the back-end server for core service processing, the image data needs to be first subjected to image compression processing.
Correspondingly, in this embodiment, a new manner of determining a target compression algorithm adapted to the image data according to the data type of the target data and at least one piece of configuration description information of the application end is creatively provided, so that the image data can be transmitted in the minimum data volume on the premise of ensuring the minimum definition requirement of the image data.
In this embodiment, an alternative compression algorithm set may be built in the application end, where the alternative compression algorithm set includes a plurality of alternative compression algorithms, and different alternative compression algorithms have different compression rates.
Wherein each alternative compression algorithm included in the alternative compression algorithm set may include: the present embodiment is not limited to the huffman coding-based compression algorithm, predictive coding-based compression algorithm, string table compression algorithm, algorithmic coding-based compression algorithm, transform coding-based compression algorithm, and the like.
Specifically, when the same electronic image is compressed, the lower the compression rate of a compression algorithm is, the smaller the data size of the compression result obtained after compression is, and accordingly, the higher the compression difficulty of the compression algorithm or the higher the requirements on software and hardware may be.
In this embodiment, different adaptive compression algorithm sets may be set in advance for different data types and different configuration description information, and then, by comparing the adaptive compression algorithm sets corresponding to the data types of the image data and each configuration description information, a compression algorithm with the largest occurrence number may be screened out as the target compression algorithm.
For example, if the data type of the image data is determined to be "identity card", the adaptive compression algorithm set corresponding to "identity card" is: "alternative compression algorithm 1, alternative compression algorithm 2, and alternative compression algorithm 3"; in addition, the adaptive compression algorithm set corresponding to the configuration description information 1 is: "alternative compression algorithm 2, alternative compression algorithm 3, and alternative compression algorithm 4" and the set of adapted compression algorithms corresponding to the configuration description information 2 are: "alternative compression algorithm 1 and alternative compression algorithm 3".
By performing intersection processing on the three adaptive compression algorithm sets described above, the alternative compression algorithm 3 can be determined as the target compression algorithm.
In an optional implementation manner of this embodiment, according to the data type of the target data and at least one piece of configuration description information of the application end, determining, in an alternative compression algorithm set, a target compression algorithm adapted to the image data may include: and determining a target compression algorithm adapted to the image data according to the data type of the target data, at least one piece of configuration description information of the application end and a labeling sample set obtained by pre-labeling.
Wherein, each labeling sample in the labeling sample set comprises: the system comprises a standard data type, at least one piece of standard configuration description information and a matched standard compression algorithm, wherein the standard compression algorithm is one compression algorithm in the alternative compression algorithm set. The set of annotation samples may be a set of target data samples indexed by an adaptive compression algorithm. The standard profile type may refer to a predetermined type of target profile. The standard configuration description information may refer to configuration description information (which may include software configuration information, hardware configuration information, network environment information, etc.) adapted to the target material. The standard compression algorithm may refer to an optimal compression algorithm that adapts to the target material.
And S130, compressing the image data by adopting the target compression algorithm to obtain target compressed image data.
The target compressed image data may be image data obtained by compressing image data by a selected target compression algorithm.
Specifically, according to the selected target compression algorithm, the acquired image data may be compressed, and the compressed image data may be determined as target compressed image data.
And S140, uploading the target compressed image data to a server corresponding to the application end.
The server may refer to a terminal server that is finally stored after the target compressed image data obtained by scanning the initial target data, and the server is generally matched with application ends of a plurality of different service types, and on the server, key processing matched with the actual service types, such as identification, authentication, and the like, may be performed on the target compressed image data.
In this embodiment, the application end may directly upload the target compressed image data to the server in a synchronous uploading manner after generating the target compressed image data, or may upload the target compressed image data to the server by an asynchronous uploading method when the data uploading condition is satisfied, which is not limited in this embodiment.
Accordingly, in an optional implementation manner of this embodiment, uploading the target compressed image data to the server corresponding to the application end may include:
the target compressed image data is locally cached at the application end, and the target compressed image data is asynchronously uploaded to the server when an uploading time interval matched with the application end is met; the server configures different uploading time intervals for application terminals providing different service in advance.
The uploading time interval may be a time interval of uploading compressed image data by application terminals of different service services configured in advance by the server.
Optionally, when the target compressed image data is acquired and uploaded to the server, whether an uploading time interval configured by the server is met or not can be judged; if the uploading time interval is satisfied, the target compressed image data can be uploaded directly, if the uploading time interval is not satisfied, the target compressed image data can be locally cached at the application end, and if the uploading time interval is satisfied, the target compressed image data is uploaded to the server.
Taking insurance service as an example, since the insurance service includes multiple service services, if multiple application ends of each service can upload compressed image data to be transmitted to the server without limitation, there is a high probability that sudden peak bandwidth occupation is caused, and thus a problem of short-time uploading failure or rapid reduction of uploading speed may occur. Based on this, the server may configure different uploading time intervals for different business services, for example, the server may configure the uploading time interval of property insurance business to be 9:00 to 11:00, the uploading time interval of the life insurance business is 13:00 to 15:00, etc.
The method has the advantages that the working pressure of the server can be relieved, so that different types of application ends for providing different service services can be used for uploading compressed target compressed image data to the server in a time-division manner.
According to the technical scheme, the scanning tool is used for carrying out electronic scanning on the target data to obtain image data matched with the target data; determining a target compression algorithm adapted to the image data in the alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end; compressing the image data by adopting a target compression algorithm to obtain target compressed image data; the method comprises the steps of uploading target compressed image data to a server corresponding to an application end, solving the problems that in the prior art, different operation terminals and operation systems used by different operators are different, and network environments are different, so that an optimal algorithm is not easy to determine in alternative compression algorithms.
Optionally, in addition to the data type of the target data and the configuration description information of the application end, a target compression algorithm adapted to the image data may be determined from the candidate compression algorithm set in combination with a pre-labeled labeling sample set.
Correspondingly, on the basis of the above embodiments, determining the target compression algorithm adapted to the image data according to the data type of the target data, at least one piece of configuration description information of the application end and a labeling sample set obtained by pre-labeling may include:
and inputting the data type of the target data and at least one piece of configuration description information of the application end into a pre-trained compression algorithm identification model, and acquiring the target compression algorithm output by the compression algorithm identification model.
The compression algorithm identification model is obtained by training the labeling sample set in advance.
In this embodiment, a compression algorithm recognition model may be trained in advance according to a labeling sample labeled with a relationship between a data type, at least one configuration description information, and a matched compression algorithm, and the target compression algorithm adapted to the image data may be obtained by inputting the data type of the target data and at least one configuration description information of the application end into the compression algorithm recognition model.
In this embodiment, each labeling sample set may be trained in advance to obtain a compression algorithm identification model, and based on the compression algorithm identification model, a target compression algorithm adapted to the image data may be determined.
Or, the labeling samples can be classified according to the standard compression algorithm labeled in each labeling sample, and the labeling samples of the same type correspond to the same standard compression algorithm.
Furthermore, the common characteristics in each standard data type and at least one standard configuration description information in the similar labeling samples can be abstracted to be used as the standard sample characteristics of each class of labeling samples.
Furthermore, by calculating the similarity between the data type of the target data, at least one piece of configuration description information of the application end and the standard sample characteristics of each type of labeling sample, a standard compression algorithm corresponding to the standard sample characteristic with the maximum similarity can be selected as the target compression algorithm.
Example two
Fig. 2A is a flowchart of another method for compressing and uploading image data according to a second embodiment of the present invention. Based on the above embodiments, the present embodiment preferably further refines, in an alternative compression algorithm set, a target compression algorithm operation adapted to the image data according to the data type of the target data and at least one piece of configuration description information of the application end, and specifically includes the following steps:
S210, electronically scanning the target data through a scanning tool to acquire image data matched with the target data.
In an optional implementation manner of this embodiment, the electronic scanning of the target data by the scanning tool to obtain the image data matched with the target data may include:
responding to a compression uploading application request, and acquiring a software environment of a target terminal adapted by an application terminal; acquiring a connection component matched with the software environment in a standardized compatible plug-in, and establishing communication connection with the scanning tool by using the connection component; triggering the scanning tool to electronically scan the target data after the communication connection is completed, and obtaining image data matched with the target data; and in the standardized compatible plug-in, a rendering component matched with the software environment is obtained, and the rendering component is used for rendering the image data to a display screen of the target terminal for display.
The compression uploading application request may refer to a request for uploading the target data to the server after compressing the target data. The target terminal may be a terminal device according to the application end, for example, an electronic device such as a mobile phone or a tablet. The software environment may refer to a software running environment of the target terminal, for example, an operating system (for example, an android operating system, or an iOS operating system, etc.) installed in the target terminal, or when an application end runs on the target terminal, some function plug-ins need to be jointly run, etc. Standardized compatible plug-ins may refer to some of the programs necessary in the process of establishing a communication connection between a scan tool and an application, and may include connection plug-ins and rendering components suitable for use in a variety of software environments (e.g., android systems, ios systems, windows systems, etc.). The connection component may be a program, such as a driver, for enabling communication between the application and the scan tool. The rendering component may refer to a component that generates image data into an image that may be presented in a display screen of a target terminal.
Specifically, when an application terminal receives a compression uploading application request, responding to the request, and acquiring a software environment of a target terminal adapted by the application terminal; from the standardized compatible plug-ins, a connection component is selected that matches the software environment of the target terminal, so that a communication connection can be established between the application end and the scanning tool via the connection component. After the communication connection is established successfully, the target data is scanned through a scanning tool to obtain image data, further, a rendering component matched with the software environment of the target terminal is selected from the standardized compatible plug-in, and the image data is displayed in a display screen of the target terminal by using the rendering component.
For different application ends, when customer data is collected, a plurality of platforms exist, and each insurance system realizes the programming language difference. The compatibility of each platform, how the image is compressed, the minimum bandwidth occupied, and the high availability of the imaging system are important.
S220, according to the data type of the target data, at least one item of key business information is identified in the image data.
The key service information of the image data may refer to information contained in the image data, which may explicitly represent the content of the target data, and taking the data type of the image data as an "identity card" as an example, the key service information that needs to be identified in the image data may include: face image, ID card number, issuing authority, etc.
Optionally, after the image data is obtained by the scanning tool, whether the key business information in the image data is clear and complete can be first identified. Specifically, the identification of key business information is performed on scanned image data according to the data type of the target data.
S230, if all the key business information is determined to be identified, determining a target compression algorithm adapted to the image data in an alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end.
Specifically, if all the key service information can be identified from the image data, the target compression algorithm adapted to the image data can be determined in the alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end, so as to compress the image data.
Correspondingly, if it is determined that all the key service information cannot be identified, service personnel using the application end need to perform electronic scanning on the target data again under the scene more suitable for image scanning, or require a user requiring insurance service to provide clearer target data again.
The arrangement has the advantages that the result after the target data is scanned is checked in time, and the follow-up compression work can be ensured to be carried out smoothly.
S240, compressing the image data by adopting the target compression algorithm to obtain target compressed image data.
S250, uploading the target compressed image data to a server corresponding to the application end.
In an optional implementation manner of this embodiment, uploading the target compressed image data to a server corresponding to the application end may include:
according to the data type of the target data, at least one item of key business information is identified in the target compressed image data; if all the key service information is determined to be identified, uploading the target compressed image data to a server corresponding to the application end; if the fact that all key service information cannot be identified is determined, screening a high-quality compression algorithm set with the compression rate higher than that of the target compression algorithm from an alternative compression algorithm set; sequentially obtaining target high-quality compression algorithms from the high-quality compression algorithm set according to the sequence of the compression rate from low to high; and carrying out compression processing on the image data by adopting the target high-quality compression algorithm, and after updating the compression result into the current target compressed image data, returning to execute the operation of identifying at least one item of key service information in the target compressed image data until the current target compressed image data is successfully uploaded.
The key business information of the target compressed image data may refer to information contained in the target compressed image data, which may explicitly represent the content of the target data, for example, portrait information in the identity card or identity number information in the identity card. The high-quality compression algorithm set may refer to a set of compression algorithms having a compression rate higher than that of the target compression algorithm, compared to the target compression algorithm corresponding to the current target compressed image data. The set of high quality compression algorithms may be a subset of alternative compression algorithms. The target high quality compression algorithm may be an algorithm selected from a set of high quality compressions that again compresses the image data.
Optionally, after the target compressed image data is obtained, it is also necessary to check whether the key information in the compressed initial image data is clear and complete. The key business information in the corresponding target compressed image data can be identified according to the type of the target data; if it is determined that all the pieces of critical information matching the corresponding target materials can be identified from the target compressed image data, the target compressed image data can be uploaded to a server for storage.
Accordingly, if all the key service information is not identified, the compression algorithm can be reselected to compress the image data. Specifically, the compression rate higher than the currently used target compression algorithm can be used as a standard, a high-quality compression algorithm set is obtained by screening from the alternative compression algorithm set, and the algorithms are sequentially obtained from the high-quality compression algorithm set to serve as target high-quality compression algorithms according to the sequence of the compression rate from low to high; and then, according to the target high-quality compression algorithm, carrying out compression processing on the current image data again, updating the compression result into the current target compressed image data, and returning to execute the key business information identification operation again until the current compressed image data is successfully uploaded to the server.
The arrangement has the advantages that the complete definition degree of the compressed target data can be ensured by matching with the key business information identification operation of the image data, the target data information can be saved in higher quality and more real time, and the data of the target data can be more complete.
In this embodiment, the compression algorithm identification model is built in the application end, where the initialized compression algorithm identification model is sent to the application end of the service personnel of different services after being trained by the unified background server.
Correspondingly, after each application end finally completes successful uploading of the target compressed image data, if it is determined that the target compressed image data which is currently uploaded is obtained by compressing a target high-quality compression algorithm, then a new training sample can be built according to the target high-quality compression algorithm, the data type of the target data and at least one piece of configuration description information of the application end, fine adjustment is performed on the compression algorithm identification model in the matched application end, and then each compression algorithm identification model can be enabled to be accurately adapted to the application end, and further compression service for the image data can be accurately and efficiently provided.
According to the technical scheme of the embodiment, the scanning tool is used for carrying out electronic scanning on target data to obtain image data matched with the target data; according to the data type of the target data, at least one item of key business information is identified in the image data; if all the key business information is determined to be identified, determining a target compression algorithm adapted to the image data in an alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of an application end; compressing the image data by adopting a target compression algorithm to obtain target compressed image data; the method comprises the steps of uploading target compressed image data to a server corresponding to an application end, solving the problems that in the prior art, different operation terminals and operation systems used by different operators are different, and network environments are different, so that an optimal algorithm is not easy to determine in alternative compression algorithms.
Fig. 2B is a schematic diagram of a specific application scenario of a method for compressing and uploading image data according to a second embodiment of the present invention.
Scanning an image: business personnel scan the paper target data through a scanning tool to obtain image data;
and (3) data acquisition: the method comprises the steps of collecting the operating system and network bandwidth data of an application terminal in real time in advance, and storing the data into a local cache;
sample data extraction: cleaning the operation system and the network bandwidth data by utilizing a machine learning and feature extraction technology, then performing random sampling analysis to obtain sample data, supporting the support of an intranet environment on a distributed mode, and performing data sharing locally;
modeling a compression algorithm: carrying out algorithm modeling by utilizing machine learning algorithms such as decision trees, random forests and the like to generate a compression algorithm recognition model;
image processing: when a compression algorithm of image data is determined through a compression algorithm identification model, fuzzy verification (namely key service information identification) is carried out on the image data, and if the image data is fuzzy, service personnel are notified in real time and are notified to a user; if all the key business information of the image data is clear and complete, determining a target compression algorithm for compressing the image data according to a compression algorithm identification model, and compressing the image data;
Uploading compressed images: and uploading the compressed image data (i.e. the target compressed image data) to a core system (i.e. a server) in an asynchronous uploading mode.
Example III
Fig. 3 is a schematic structural diagram of a compression uploading device for image data according to a third embodiment of the present invention. Executed by an application end, the device comprises: the image data acquisition module 310, the compression algorithm determination module 320, the compressed image data acquisition module 330, and the compressed image data upload module 340. Wherein:
the image data acquisition module 310 is configured to electronically scan the target data through a scanning tool to acquire image data matched with the target data;
the compression algorithm determining module 320 is configured to determine, in an alternative compression algorithm set, a target compression algorithm adapted to the image data according to the data type of the target data and at least one piece of configuration description information of the application end;
the compressed image data obtaining module 330 is configured to perform compression processing on the image data by using the target compression algorithm to obtain target compressed image data;
and the compressed image data uploading module 340 is configured to upload the target compressed image data to a server corresponding to the application end.
According to the technical scheme, the scanning tool is used for carrying out electronic scanning on the target data to obtain image data matched with the target data; determining a target compression algorithm adapted to the image data in the alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end; compressing the image data by adopting a target compression algorithm to obtain target compressed image data; the method comprises the steps of uploading target compressed image data to a server corresponding to an application end, solving the problems that in the prior art, different operation terminals and operation systems used by different operators are different, and network environments are different, so that an optimal algorithm is not easy to determine in alternative compression algorithms.
In the above apparatus, optionally, the compression algorithm determining module 320 may include:
the compression algorithm determining subunit is used for determining a target compression algorithm adapted to the image data according to the data type of the target data, at least one piece of configuration description information of the application end and a labeling sample set obtained by pre-labeling;
Wherein, each labeling sample in the labeling sample set comprises: the system comprises a standard data type, at least one piece of standard configuration description information and a matched standard compression algorithm, wherein the standard compression algorithm is one compression algorithm in the alternative compression algorithm set.
In the above apparatus, optionally, the compression algorithm determining subunit may be specifically configured to:
inputting the data type of the target data and at least one piece of configuration description information of the application end into a pre-trained compression algorithm identification model, and acquiring the target compression algorithm output by the compression algorithm identification model;
the compression algorithm identification model is obtained by training the labeling sample set in advance.
In the above apparatus, optionally, the compression algorithm determining module 320 may be further specifically configured to:
according to the data type of the target data, at least one item of key business information is identified in the image data;
and if all the key business information is determined to be identified, determining a target compression algorithm adapted to the image data in an alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end.
In the above apparatus, optionally, the compressed image data uploading module 330 may be specifically configured to:
according to the data type of the target data, at least one item of key business information is identified in the target compressed image data;
if all the key service information is determined to be identified, uploading the target compressed image data to a server corresponding to the application end;
if the fact that all key service information cannot be identified is determined, screening a high-quality compression algorithm set with the compression rate higher than that of the target compression algorithm from an alternative compression algorithm set;
sequentially obtaining target high-quality compression algorithms from the high-quality compression algorithm set according to the sequence of the compression rate from low to high;
and carrying out compression processing on the image data by adopting the target high-quality compression algorithm, and after updating the compression result into the current target compressed image data, returning to execute the operation of identifying at least one item of key service information in the target compressed image data until the current target compressed image data is successfully uploaded.
In the above apparatus, optionally, the compressed image data uploading module 330 may be further specifically configured to:
The target compressed image data is locally cached at the application end, and the target compressed image data is asynchronously uploaded to the server when an uploading time interval matched with the application end is met;
the server configures different uploading time intervals for application terminals providing different service in advance.
In the above apparatus, optionally, the image data acquisition module 310 may be specifically configured to:
responding to a compression uploading application request, and acquiring a software environment of a target terminal adapted by an application terminal;
acquiring a connection component matched with the software environment in a standardized compatible plug-in, and establishing communication connection with the scanning tool by using the connection component;
triggering the scanning tool to electronically scan the target data after the communication connection is completed, and obtaining image data matched with the target data;
and in the standardized compatible plug-in, a rendering component matched with the software environment is obtained, and the rendering component is used for rendering the image data to a display screen of the target terminal for display.
The image data compression and uploading device provided by the embodiment of the invention can execute the image data compression and uploading method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example IV
Fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention, where, as shown in fig. 4, the device includes a processor 410, a storage device 420, an input device 430, and an output device 440; the number of processors 410 in the device may be one or more, one processor 410 being taken as an example in fig. 4; the processor 410, the storage 420, the input 430, and the output 440 in the apparatus may be connected by a bus or other means, which is illustrated in fig. 4 as a bus connection.
The storage device 420 is a computer readable storage medium, and can be used to store a software program, a computer executable program, and modules, such as program instructions/modules corresponding to the method for uploading compressed image data in the embodiment of the present invention (for example, the image data acquisition module 310, the compression algorithm determining module 320, the compressed image data acquisition module 330, and the compressed image data uploading module 340 in the device for uploading compressed image data). The processor 410 executes the software programs, instructions and modules stored in the storage 420 to perform various functional applications and data processing of the device, that is, to implement the above-mentioned image data compression uploading method, where the method is executed by the application end, and may include:
Electronically scanning target data through a scanning tool to acquire image data matched with the target data;
determining a target compression algorithm adapted to the image data in an alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end;
adopting the target compression algorithm to compress the image data to obtain target compressed image data;
and uploading the target compressed image data to a server corresponding to the application end.
The storage device 420 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, at least one application program required for functions; the storage data area may store data created according to the use of the terminal, etc. In addition, the storage 420 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some examples, the storage 420 may further include memory remotely located with respect to the processor 410, which may be connected to the appliance via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input means 430 may be used to receive entered numeric or character information and to generate key signal inputs related to user settings and function control of the device. The output 440 may include a display device such as a display screen.
Example five
A fifth embodiment of the present invention further provides a computer readable storage medium having a computer program stored thereon, where the computer program when executed by a processor is configured to perform a method for compressing and uploading image data, where the method is executed by an application side, and the method may include:
electronically scanning target data through a scanning tool to acquire image data matched with the target data;
determining a target compression algorithm adapted to the image data in an alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end;
adopting the target compression algorithm to compress the image data to obtain target compressed image data;
and uploading the target compressed image data to a server corresponding to the application end.
Of course, the computer readable storage medium provided by the embodiments of the present invention is not limited to the above-mentioned method operations, but may also perform the related operations in the image data compression and uploading method provided by any embodiment of the present invention, where the method is performed by the application end, and may include:
Electronically scanning target data through a scanning tool to acquire image data matched with the target data;
determining a target compression algorithm adapted to the image data in an alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end;
adopting the target compression algorithm to compress the image data to obtain target compressed image data;
and uploading the target compressed image data to a server corresponding to the application end.
From the above description of embodiments, it will be clear to a person skilled in the art that the present invention may be implemented by means of software and necessary general purpose hardware, but of course also by means of hardware, although in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, etc., and include several instructions for causing a computer device (which may be a personal computer, an application, or a network device, etc.) to execute the method according to the embodiments of the present invention.
It should be noted that, in the embodiment of the compression uploading device for image data, each unit and module included are only divided according to the functional logic, but not limited to the above-mentioned division, so long as the corresponding functions can be realized; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (9)
1. The compression uploading method of the image data is executed by an application end, wherein the application end is an insurance service application program, and the compression uploading method is characterized by comprising the following steps:
Electronically scanning target data through a scanning tool to acquire image data matched with the target data;
determining a target compression algorithm adapted to the image data in an alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end; the data type of the target data is the certificate type of the insurance service; the configuration description information comprises software configuration information, hardware configuration information and network environment information; the software configuration information is the type and version of the application end and the type and version of the operating system adapted by the terminal equipment for installing the application end; the hardware configuration information is the model of the scanning tool, the model of the terminal equipment of the installation application end, the memory and the CPU performance; the network environment information is the network speed, the bandwidth and the packet loss rate of the network to which the application terminal is connected currently;
adopting the target compression algorithm to compress the image data to obtain target compressed image data;
uploading the target compressed image data to a server corresponding to the application end;
wherein, according to the data type of the target data and at least one piece of configuration description information of the application end, determining the target compression algorithm adapted to the image data in the alternative compression algorithm set comprises the following steps:
Determining a target compression algorithm adapted to the image data according to the data type of the target data, at least one piece of configuration description information of the application end and a labeling sample set obtained by pre-labeling;
wherein, each labeling sample in the labeling sample set comprises: the system comprises a standard data type, at least one piece of standard configuration description information and a matched standard compression algorithm, wherein the standard compression algorithm is one compression algorithm in the alternative compression algorithm set;
classifying the labeling samples according to standard compression algorithms labeled in each labeling sample, wherein the labeling samples of the same class correspond to the same standard compression algorithm; abstracting out common characteristics in each standard data type and at least one standard configuration description information in the similar labeling samples, and taking the common characteristics as standard sample characteristics of each class of labeling samples; and selecting a standard compression algorithm corresponding to the standard sample characteristic with the maximum similarity as the target compression algorithm by calculating the similarity among the data type of the target data, at least one piece of configuration description information of the application end and the standard sample characteristic of each type of marked sample.
2. The method according to claim 1, wherein determining the target compression algorithm adapted to the image data according to the data type of the target data, at least one piece of configuration description information of the application end, and a labeled sample set obtained by labeling in advance, includes:
Inputting the data type of the target data and at least one piece of configuration description information of the application end into a pre-trained compression algorithm identification model, and acquiring the target compression algorithm output by the compression algorithm identification model;
the compression algorithm identification model is obtained by training the labeling sample set in advance.
3. The method of claim 1, wherein determining, in the set of alternative compression algorithms, a target compression algorithm to which the image data is adapted based on the profile type of the target profile and at least one piece of configuration description information of the application side, comprises:
according to the data type of the target data, at least one item of key business information is identified in the image data;
and if all the key business information is determined to be identified, determining a target compression algorithm adapted to the image data in an alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end.
4. A method according to claim 3, wherein uploading the target compressed image data to a server corresponding to the application terminal comprises:
According to the data type of the target data, at least one item of key business information is identified in the target compressed image data;
if all the key service information is determined to be identified, uploading the target compressed image data to a server corresponding to the application end;
if the fact that all key service information cannot be identified is determined, screening a high-quality compression algorithm set with the compression rate higher than that of the target compression algorithm from an alternative compression algorithm set;
sequentially obtaining target high-quality compression algorithms from the high-quality compression algorithm set according to the sequence of the compression rate from low to high;
and carrying out compression processing on the image data by adopting the target high-quality compression algorithm, and after updating the compression result into the current target compressed image data, returning to execute the operation of identifying at least one item of key service information in the target compressed image data until the current target compressed image data is successfully uploaded.
5. The method of claim 1, wherein uploading the target compressed image data to a server corresponding to the application comprises:
the target compressed image data is locally cached at the application end, and the target compressed image data is asynchronously uploaded to the server when an uploading time interval matched with the application end is met;
The server configures different uploading time intervals for application terminals providing different service in advance.
6. The method of claim 1, wherein electronically scanning the target material with a scanning tool to obtain image data matching the target material comprises:
responding to a compression uploading application request, and acquiring a software environment of a target terminal adapted by an application terminal;
acquiring a connection component matched with the software environment in a standardized compatible plug-in, and establishing communication connection with the scanning tool by using the connection component;
triggering the scanning tool to electronically scan the target data after the communication connection is completed, and obtaining image data matched with the target data;
and in the standardized compatible plug-in, a rendering component matched with the software environment is obtained, and the rendering component is used for rendering the image data to a display screen of the target terminal for display.
7. A compression uploading device of image data, executed by an application end, the application end being an insurance service application program, the device comprising:
the image data acquisition module is used for carrying out electronic scanning on target data through a scanning tool to acquire image data matched with the target data;
The compression algorithm determining module is used for determining a target compression algorithm adapted to the image data in an alternative compression algorithm set according to the data type of the target data and at least one piece of configuration description information of the application end; the data type of the target data is the certificate type of the insurance service; the configuration description information comprises software configuration information, hardware configuration information and network environment information; the software configuration information is the type and version of the application end and the type and version of the operating system adapted by the terminal equipment for installing the application end; the hardware configuration information is the model of the scanning tool, the model of the terminal equipment of the installation application end, the memory and the CPU performance; the network environment information is the network speed, the bandwidth and the packet loss rate of the network to which the application terminal is connected currently;
the compressed image data acquisition module is used for compressing the image data by adopting the target compression algorithm to obtain target compressed image data;
the compressed image data uploading module is used for uploading the target compressed image data to a server corresponding to the application end;
the compression algorithm determining module is specifically configured to determine a target compression algorithm adapted to the image data according to the data type of the target data, at least one piece of configuration description information of the application end, and a labeling sample set obtained by pre-labeling;
Wherein, each labeling sample in the labeling sample set comprises: the system comprises a standard data type, at least one piece of standard configuration description information and a matched standard compression algorithm, wherein the standard compression algorithm is one compression algorithm in the alternative compression algorithm set;
classifying the labeling samples according to standard compression algorithms labeled in each labeling sample, wherein the labeling samples of the same class correspond to the same standard compression algorithm; abstracting out common characteristics in each standard data type and at least one standard configuration description information in the similar labeling samples, and taking the common characteristics as standard sample characteristics of each class of labeling samples; and selecting a standard compression algorithm corresponding to the standard sample characteristic with the maximum similarity as the target compression algorithm by calculating the similarity among the data type of the target data, at least one piece of configuration description information of the application end and the standard sample characteristic of each type of marked sample.
8. An electronic device, the electronic device comprising:
one or more processors;
storage means for storing one or more computer programs;
when executed by the one or more processors, the one or more computer programs cause the one or more processors to implement the method of compressed uploading of image data as claimed in any of claims 1-6.
9. A computer readable storage medium having stored thereon a computer program, which when executed by a processor implements a method of compressed uploading of image data according to any of claims 1-6.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1984330A (en) * | 2005-06-25 | 2007-06-20 | 通用电气公司 | Adaptive video compression of graphical user interfaces using application metadata |
| KR20190029800A (en) * | 2017-08-28 | 2019-03-21 | 에스케이텔레콤 주식회사 | Terminal device, server and system for image recognition capable of protecting personal information |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7447365B2 (en) * | 2004-02-06 | 2008-11-04 | Sharp Laboratories Of America, Inc. | Systems and methods for mixed raster conversion in direct printing |
| US10474896B2 (en) * | 2017-07-18 | 2019-11-12 | Facebook, Inc. | Image compression using content categories |
| US11222443B2 (en) * | 2019-04-02 | 2022-01-11 | Dotphoton Ag | Image compression using image acquisition device characteristics |
-
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1984330A (en) * | 2005-06-25 | 2007-06-20 | 通用电气公司 | Adaptive video compression of graphical user interfaces using application metadata |
| KR20190029800A (en) * | 2017-08-28 | 2019-03-21 | 에스케이텔레콤 주식회사 | Terminal device, server and system for image recognition capable of protecting personal information |
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