CN116129457A - Intelligent digital conversion method and system for paper document - Google Patents
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- CN116129457A CN116129457A CN202310162207.8A CN202310162207A CN116129457A CN 116129457 A CN116129457 A CN 116129457A CN 202310162207 A CN202310162207 A CN 202310162207A CN 116129457 A CN116129457 A CN 116129457A
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Abstract
The invention provides an intelligent digital conversion method and system for paper documents. Wherein the method comprises the following steps: s10, task attribute information digitally converted from a paper document is received; s20, determining target content of the paper document based on the task attribute information; s30, identifying and extracting the target content to finish digital conversion; according to the scheme provided by the invention, different types of contents in the converted paper document can be selected based on various requirements of the user, namely, the conventional printed contents can be included, the annotation contents handwritten by the user can be also included, and the better digital conversion experience of the paper document can be provided for the user.
Description
Technical Field
The invention relates to the technical field of image recognition and document processing, in particular to an intelligent digital conversion method and system for paper documents.
Background
With the rapid development of information technology, most of current document realization forms are electronic and digital, namely, documents can be conveniently checked and operated on computers and mobile devices by means of various types of document processing software. However, at present, a huge amount of old documents are in paper form, and the documents face the threat of aging and damage, are inconvenient for users to use, and especially cannot be quickly searched and positioned.
After searching the prior art, some related schemes for digitally converting paper documents already exist in the prior art, for example:
patent document 1 (CN 112819724 a) discloses a CNN-based scanned document image enhancement method, comprising the steps of: step 1, performing color space conversion and normalization processing on groudtluth, and then acquiring a degradation image by combining a degradation model; step 2, constructing a deep learning model; the deep learning model is composed of a feature extraction module, a feature nonlinear mapping module and an image reconstruction module, wherein the feature extraction module is composed of a plurality of convolution layers, convolution kernels are 3 multiplied by 3, the feature nonlinear mapping module is composed of one 1 multiplied by 1 convolution layer, and the image reconstruction module is composed of two 3 multiplied by 3 convolution layers; step 3, carrying out sub-image division processing on the degraded image and the groundtrunk to form a training image pair; step 4, training a deep learning model by using the training image pair; and 5, inputting the image to be processed into a trained deep learning model to obtain an enhanced scanned text image. This scheme focuses on how to process paper documents with degradation problems to enhance image quality and thus digital conversion of the paper documents, but does not involve screening of document content.
Patent document 2 (CN 111507351 a) discloses a method for digitizing an ancient book document, comprising the steps of: s1, acquiring data: collecting image data of an ancient book document, and performing text line annotation and text line annotation on the image data at a space level to obtain a training data set; s2, training a single word detection model and detecting: preprocessing the training data set; setting different anchor sizes based on a universal target detection frame YOLO-v3, and then training the preprocessed training data set under the YOLO-v3 detection frame to obtain a single-word detection model; directly inputting the whole image to detect by using the trained single character detection model to obtain a single character detection result; s3, training a single word classification model and classifying: in the step S1, the single character labeling can obtain a picture of a single character, a single character classification model is constructed by utilizing a convolutional neural network, and the single character classification model is trained by utilizing the picture of the single character to obtain a single character classification model; inputting a single-word picture by using the trained single-word classification model to obtain a classification recognition result; s4, extracting a layout straight line: detecting the linear position in the ancient book document, and extracting parts of different area blocks of the ancient book document content to obtain the position relation among the area blocks; s5, structuring the output document. This solution focuses on the accurate recognition of characters of a paper document, but it also does not involve a screening process of the document content.
Patent document 3 (CN 110999271 a) discloses a method for measuring characteristics of paper, the method comprising: (a) Providing a plurality of paper sensors on an automatic transport mechanism; (b) Detecting a timing of the sheet being under the plurality of sheet sensors by means of the plurality of sheet sensors as the sheet travels through the automatic conveying mechanism; (c) Based on the detection of the timing, the size, position or orientation of the sheet is calculated by means of one or more processors. This scheme focuses on how to improve the numerical conversion efficiency of paper documents, but it also does not involve screening processing of document contents.
According to the analysis of the prior art, the patent technology related to the prior art can not effectively distinguish and screen the content of the paper document, and can not meet the actual digital conversion requirement.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention provides an intelligent digital conversion method, an intelligent digital conversion system, electronic equipment and a storage medium for paper documents, so as to realize accurate identification of work clothes in various complex scenes.
The first aspect of the invention provides an intelligent digital conversion method for paper documents, which comprises the following steps:
s10, task attribute information digitally converted from a paper document is received;
s20, determining target content of the paper document based on the task attribute information;
s30, identifying and extracting the target content to finish digital conversion.
Optionally, the task attribute information includes task category and task number.
Optionally, in step S20, the determining the target content of the paper document based on the task attribute information includes:
extracting and identifying the task attribute information to obtain task types and task quantity;
if the number of the tasks is equal to one, determining target content of the paper document based on the task category;
if the number of the tasks is greater than one, determining target content of the paper document based on each task category, performing aggregation processing on the determined target content, and determining the aggregated target content as the target content of the paper document.
Optionally, in step S30, before the identifying and extracting the target content, the method further includes:
locating a target area image of the paper document;
performing first processing on the target area image based on the target content to obtain a first image combination, wherein the first image combination comprises a first sub-image corresponding to each target content and a second sub-image not corresponding to each target content;
and performing second processing on the first image combination to obtain a second image combination, wherein the second image combination is used for identifying and extracting the target content.
Optionally, the performing a second process on the first image combination includes:
the second sub-image is recognized in a suspension mode, and meanwhile, the logical page number of the paper document corresponding to the second sub-image is recorded;
when the real-time logical page number of the current page of the paper document is matched with the logical page number, performing writing trace identification on a target area image of the current page;
and establishing a corresponding relation between the second sub-image and each target content based on the writing trace identification result.
Optionally, step S30 further includes:
if the writing trace identification result of the second sub-image is yes and the identification and extraction of the target content of the second sub-image are failed, transferring the second sub-image to a third image combination;
and outputting the third image combination to a user.
Optionally, step S30 further includes:
and storing the identified and extracted digital content in a classified manner based on the corresponding relation between each task category and the target content.
The invention provides a paper document digital conversion system, which comprises a processing module, a storage module, a communication module and a scanning module, wherein the processing module is respectively connected with the storage module, the communication module and the scanning module; wherein,,
the memory module is used for storing executable computer program codes;
the communication module is used for receiving task attribute information input by a user and transmitting the task attribute information to the processing module;
the scanning module is used for acquiring the image information of the paper document and transmitting the image information to the processing module;
the processing module is configured to perform the method of any of the preceding claims by invoking the executable computer program code in the storage module.
A third aspect of the present invention provides an electronic device comprising:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform the method of any one of the preceding claims.
A fourth aspect of the invention provides a computer storage medium having stored thereon a computer program which, when executed by a processor, performs a method as claimed in any one of the preceding claims.
According to the scheme, task attribute information of digital conversion of the paper document is received, target content of the paper document is determined based on the task attribute information, and identification and extraction are carried out on the target content so as to complete the digital conversion. According to the scheme provided by the invention, different types of contents in the converted paper document can be selected based on various requirements of the user, namely, the conventional printed contents can be included, the annotation contents handwritten by the user can be also included, and the better digital conversion experience of the paper document can be provided for the user.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an intelligent digital conversion method for paper documents, disclosed in an embodiment of the invention;
FIG. 2 is a schematic diagram of a digital conversion system for paper documents according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantageous technical effects of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings and detailed description. It should be understood that the detailed description is intended to illustrate the invention, and not to limit the invention.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
Example 1
Referring to fig. 1, fig. 1 is a schematic flow chart of an intelligent digital conversion method for paper documents according to an embodiment of the invention. As shown in FIG. 1, the intelligent digital conversion method for the paper document comprises the following steps:
s10, task attribute information digitally converted from a paper document is received;
s20, determining target content of the paper document based on the task attribute information;
s30, identifying and extracting the target content to finish digital conversion.
In the embodiment of the invention, a user can select a proper digital conversion task based on actual requirements, such as full-page scanning conversion, text scanning conversion, handwriting annotation additional conversion/non-conversion and the like, so that the system can acquire task attribute information according to the task attribute information, then determine the target content of a proper paper document based on the task attribute information, and further identify and extract the content to finish digital conversion. According to the scheme provided by the invention, different types of contents in the converted paper document can be selected based on various requirements of the user, namely, the conventional printed contents can be included, the annotation contents handwritten by the user can be also included, and the better digital conversion experience of the paper document can be provided for the user.
When extracting the target content, OCR (Optical CharacterRecognition ) refers to a process that electronic equipment checks characters printed on paper, determines shapes of the characters by detecting dark and bright modes, and translates the shapes into computer characters by using a character recognition method, wherein the current OCR character recognition is mainly based on a deep learning technology to ensure recognition accuracy. The present invention is not described in detail herein, as it is already prior art. It should be noted that, the identification and extraction of the target content in the present invention includes not only character content identification, but also image identification, that is, the character content area and the illustration area of the paper document page are positioned first, character identification, extraction and storage are performed on the character content area by adopting the OCR technology, and the illustration area can be directly intercepted and stored.
Optionally, the task attribute information includes task category and task number.
In the embodiment of the invention, when the user selects the digital conversion, the selection interface can provide the task module corresponding to the whole page scanning conversion, the text scanning conversion, the handwriting annotation additional conversion/non-conversion and the like for the user, the user can select according to the self requirement, and can select singly or more, and accordingly, the task attribute information can comprise task types and task quantity.
Optionally, in step S20, the determining the target content of the paper document based on the task attribute information includes:
extracting and identifying the task attribute information to obtain task types and task quantity;
if the number of the tasks is equal to one, determining target content of the paper document based on the task category;
if the number of the tasks is greater than one, determining target content of the paper document based on each task category, performing aggregation processing on the determined target content, and determining the aggregated target content as the target content of the paper document.
In the embodiment of the invention, the system extracts and identifies the task attribute information, so that the task category and the task number corresponding to the real requirement of the user can be obtained. Meanwhile, if the number of tasks is only one, for example, full page scan conversion, the full page of the paper document can be determined as target content, namely, full page indiscriminate digital conversion; if the number of tasks is more than one, for example, text scan conversion and handwriting annotation additional conversion, then the target content includes a text region image and a handwriting annotation region image, and correspondingly, the subsequent recognition task also includes respectively recognizing the two types of region images.
In the case that the number of tasks is multiple, the target contents corresponding to different tasks need to be sorted through aggregation processing, for example, overlapping target contents are subjected to de-duplication processing and the like, so that repeated implementation of subsequent same contents is avoided, the waste of calculation force is reduced, and the conversion efficiency is improved.
Optionally, in step S30, before the identifying and extracting the target content, the method further includes:
locating a target area image of the paper document;
performing first processing on the target area image based on the target content to obtain a first image combination, wherein the first image combination comprises a first sub-image corresponding to each target content and a second sub-image not corresponding to each target content;
and performing second processing on the first image combination to obtain a second image combination, wherein the second image combination is used for identifying and extracting the target content.
In the embodiment of the invention, as the digital conversion of the handwritten annotation content is involved, the print content and the handwritten annotation content can be distinguished by the identification of fonts so as to be respectively identified, but some documents can be inserted with the handwritten content of the print body, which is the conventional operation of the publishing and printing industry, and obviously, the identification of fonts cannot be distinguished. In view of this, the present invention performs first processing on the target area image based on the target content, that is, each target area image to be identified is primarily determined, where the first sub-image in the first image combination is the target content (for example, printed text) that can be directly determined, and the second sub-image is the content that cannot be determined accurately, for example, whether it is a printed handwritten annotation or a handwritten annotation cannot be determined. The invention can determine the true category of the content which cannot be determined accurately by carrying out the second processing on the second sub-image in the first image combination, and can directly carry out the subsequent identification after the processing.
Optionally, the performing a second process on the first image combination includes:
the second sub-image is recognized in a suspension mode, and meanwhile, the logical page number of the paper document corresponding to the second sub-image is recorded;
when the real-time logical page number of the current page of the paper document is matched with the logical page number, performing writing trace identification on a target area image of the current page;
and establishing a corresponding relation between the second sub-image and each target content based on the writing trace identification result.
In the embodiment of the present invention, aiming at the real category problem of the handwriting annotation, the present invention recognizes that the significant difference between the handwriting annotation content and the annotation content of the printing body is that the deformation characteristic of the paper, that is, if the handwriting annotation is printed, the back surface of the paper does not have obvious writing marks, namely "bulges", and the handwriting annotation (especially, ball-point pen, pen and the like) can cause obvious bulges on the back surface of the paper. Therefore, the invention temporarily stores the second sub-image, but records the logical page number thereof, when the page turning occurs on the paper document and the logical page number of the paper page after the page turning is matched with the logical page number corresponding to the second sub-image in the temporarily stores processing (namely, the two belong to the front side and the back side), the detection and identification of the bulge are carried out on the paper page after the page turning, if the bulge can be identified at the position corresponding to the second sub-image, the corresponding second sub-image can be determined as handwriting annotation, but not the printed handwriting annotation, and correspondingly, the second sub-image can be associated with the corresponding target content based on the identification result of the bulge. It should be explained that, since the areas covered by the ink are covered by the handwriting, it is difficult to identify the depressions corresponding to the protrusions from the front side of the paper, and the areas covered by the handwriting on the back side of the paper do not have obvious ink, so that the handwriting annotation is identified from the back side.
For the "protrusion" recognition method, a depth of field recognition method, or a laser detection method, etc., which are conventional techniques for flatness recognition, are used, and the present invention is not repeated here.
And, for the logical page number, it may be determined based on the recognized page number "1" at the time of digital conversion, for example, if the page number "1" is on the left page, the logical page number to which the page number "2" matches is the page number "3"; if page number "1" is on the right page, then the logical page number for which page number "2" matches is page number "1". In the former case, the scheme of the invention is backward matching, while in the latter case, the "current page" referred to in the foregoing description of the scheme of the invention should be the history page, i.e., forward matching.
Optionally, step S30 further includes:
if the writing trace identification result of the second sub-image is yes and the identification and extraction of the target content of the second sub-image are failed, transferring the second sub-image to a third image combination;
and outputting the third image combination to a user.
In the embodiment of the invention, although it can be determined whether the second sub-image is a handwritten annotation, when the target content is extracted, the font of the handwritten annotation is generally not easily recognized as the font specification of the printed content, so that the extraction failure is easy to occur. In view of this, the present invention further shifts the corresponding second sub-image to a third image combination, and outputs the third image combination to the user for recognition by a person. This ensures the accuracy of the digital conversion with little human effort.
Optionally, step S30 further includes:
and storing the identified and extracted digital content in a classified manner based on the corresponding relation between each task category and the target content.
In the embodiment of the invention, when the task types selected by the user are different, particularly the task number is multiple, the identified digital content is classified, stored and output, so that the method is beneficial to the user to find and use. Of course, since the user may identify a plurality of paper documents at the same time, association relation should be established for the digital content identified at a time based on task attribute, so that the management efficiency of the user on the digital document can be further improved.
Example two
Referring to fig. 2, fig. 2 is a schematic structural diagram of a digital conversion system for paper documents according to an embodiment of the present invention. As shown in fig. 2, the digital conversion system (100) for paper documents according to the embodiment of the invention comprises a processing module (101), a storage module (102), a communication module (103) and a scanning module (104), wherein the processing module (101) is respectively connected with the storage module (102), the communication module (103) and the scanning module (104); wherein,,
-said storage module (102) for storing executable computer program code;
the communication module (103) is used for receiving task attribute information input by a user and transmitting the task attribute information to the processing module (101);
the scanning module (104) is used for acquiring the image information of the paper document and transmitting the image information to the processing module (101);
the processing module (101) is configured to perform the method according to embodiment one by invoking the executable computer program code in the storage module (102).
The specific function of the digital conversion system for paper documents in this embodiment refers to the first embodiment, and since the system in this embodiment adopts all the technical solutions of the foregoing embodiments, at least the system has all the beneficial effects brought by the technical solutions of the foregoing embodiments, which are not described in detail herein.
Example III
Referring to fig. 3, fig. 3 is an electronic device according to an embodiment of the present invention, including:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform the method as described in embodiment one.
Example IV
The embodiment of the invention also discloses a computer storage medium, and a computer program is stored on the storage medium, and when the computer program is run by a processor, the computer program executes the method in the embodiment one.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the elements and method steps of the examples described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or as a combination of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed system or apparatus/terminal device and method may be implemented in other manners. For example, the system or apparatus/terminal device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical function division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The present invention is not limited to the details and embodiments described herein, and thus additional advantages and modifications may readily be made by those skilled in the art, without departing from the spirit and scope of the general concepts defined in the claims and the equivalents thereof, and the invention is not limited to the specific details, representative apparatus and illustrative examples shown and described herein.
Claims (10)
1. An intelligent digital conversion method for paper documents is characterized by comprising the following steps:
s10, task attribute information digitally converted from a paper document is received;
s20, determining target content of the paper document based on the task attribute information;
s30, identifying and extracting the target content to finish digital conversion.
2. The intelligent digital conversion method for paper documents according to claim 1, wherein the method comprises the following steps: the task attribute information comprises task categories and task numbers.
3. The intelligent digital conversion method for paper documents according to claim 2, wherein the method comprises the following steps: in step S20, the determining the target content of the paper document based on the task attribute information includes:
extracting and identifying the task attribute information to obtain task types and task quantity;
if the number of the tasks is equal to one, determining target content of the paper document based on the task category;
if the number of the tasks is greater than one, determining target content of the paper document based on each task category, performing aggregation processing on the determined target content, and determining the aggregated target content as the target content of the paper document.
4. A method for intelligent digital conversion of paper documents according to claim 3, wherein: in step S30, before the identifying and extracting the target content, the method further includes:
locating a target area image of the paper document;
performing first processing on the target area image based on the target content to obtain a first image combination, wherein the first image combination comprises a first sub-image corresponding to each target content and a second sub-image not corresponding to each target content;
and performing second processing on the first image combination to obtain a second image combination, wherein the second image combination is used for identifying and extracting the target content.
5. The intelligent digital conversion method for paper documents according to claim 4, wherein the method comprises the following steps: the second processing of the first image combination includes:
the second sub-image is recognized in a suspension mode, and meanwhile, the logical page number of the paper document corresponding to the second sub-image is recorded;
when the real-time logical page number of the current page of the paper document is matched with the logical page number, performing writing trace identification on a target area image of the current page;
and establishing a corresponding relation between the second sub-image and each target content based on the writing trace identification result.
6. The intelligent digital conversion method for paper documents according to claim 5, wherein the method comprises the following steps: step S30 further includes:
if the writing trace identification result of the second sub-image is yes and the identification and extraction of the target content of the second sub-image are failed, transferring the second sub-image to a third image combination;
and outputting the third image combination to a user.
7. The intelligent digital conversion method for paper documents according to claim 5, wherein the method comprises the following steps: step S30 further includes:
and storing the identified and extracted digital content in a classified manner based on the corresponding relation between each task category and the target content.
8. The digital conversion system of the paper document comprises a processing module, a storage module, a communication module and a scanning module, wherein the processing module is respectively connected with the storage module, the communication module and the scanning module; wherein,,
the memory module is used for storing executable computer program codes;
the communication module is used for receiving task attribute information input by a user and transmitting the task attribute information to the processing module;
the scanning module is used for acquiring the image information of the paper document and transmitting the image information to the processing module;
the method is characterized in that: the processing module for performing the method of any of claims 1-7 by invoking the executable computer program code in the storage module.
9. An electronic device, comprising:
a memory storing executable program code;
a processor coupled to the memory;
the method is characterized in that: the processor invokes the executable program code stored in the memory to perform the method of any of claims 1-7.
10. A computer storage medium having a computer program stored thereon, characterized in that: the computer program, when executed by a processor, performs the method of any of claims 1-7.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310162207.8A CN116129457A (en) | 2023-02-24 | 2023-02-24 | Intelligent digital conversion method and system for paper document |
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| CN202310162207.8A CN116129457A (en) | 2023-02-24 | 2023-02-24 | Intelligent digital conversion method and system for paper document |
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