CN113516044A - Paper contract credit enhancement method and system based on OCR and Hash algorithm - Google Patents
Paper contract credit enhancement method and system based on OCR and Hash algorithm Download PDFInfo
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Abstract
The invention discloses a paper contract credit enhancement method based on OCR and Hash algorithm, which relates to the technical field of image processing and comprises the following steps: acquiring a paper contract sample, and training the paper contract sample by using a CNN convolutional neural network to obtain an OCR recognition model; acquiring a paper contract picture or an electronic contract document to be identified, extracting character contents in the paper contract picture or the electronic contract document by using an OCR (optical character recognition) model, and generating a continuous character string; carrying out hash hashing on the continuous character strings by using a hash algorithm to obtain corresponding hash values; and adding the obtained hash value to the appointed position of the paper contract picture or the electronic contract document, and storing or printing the paper contract picture or the electronic contract document. The invention also discloses a paper contract credit enhancement system based on OCR and Hash algorithm, which is combined with the method, can improve the safety index of the paper contract and realize the quick verification of the paper contract.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a paper contract credit enhancement method and system based on an OCR (optical character recognition) and hash algorithm.
Background
With the development of the OCR technology, the mobile terminal can be used for realizing the accurate recognition of characters, particularly a neural network model which is specially trained, and the accuracy of the OCR recognition is greatly improved. The hash algorithm maps an arbitrary length binary value to a shorter fixed length binary value, and this small binary value is called a hash value. Hash values are a unique and extremely compact representation of a piece of data as a value. If a piece of plaintext is hashed and even if only one letter of the piece is altered, the subsequent hash will produce a different value. It is computationally infeasible to find two different inputs whose hash is the same value, so the hash value of the data can verify the integrity of the data.
Although technical means such as electronic contracts and electronic signatures can provide better guarantee for contract credit at present, traditional paper contracts are still widely used in many occasions. How to perform credit enhancement with low cost and prevent falsification aiming at the traditional paper contract also has practical significance.
Disclosure of Invention
Aiming at the requirements and the defects of the prior art development, the invention provides a paper contract credit enhancement method and a paper contract credit enhancement system based on an OCR (optical character recognition) and a Hash algorithm.
Firstly, the invention relates to a paper contract credit enhancement method based on OCR and Hash algorithm, which adopts the following technical scheme for solving the technical problems:
a paper contract credit enhancement method based on OCR and hash algorithm comprises the following implementation contents:
s1, obtaining a paper contract sample, and training the paper contract sample by using a CNN convolutional neural network to obtain an OCR recognition model;
s2, acquiring a paper contract picture or an electronic contract document to be identified, extracting the text content in the paper contract picture or the electronic contract document by using an OCR (optical character recognition) model, and generating a continuous character string;
step S3, carrying out hash hashing on the continuous character strings by using a hash algorithm to obtain corresponding hash values;
and step S4, adding the obtained hash value to the appointed position of the paper contract picture or the electronic contract document, and saving or printing the paper contract picture or the electronic contract document.
Optionally, the step S2-step S3 are executed again for the paper contract picture or the electronic contract document that has been identified, the hash value obtained this time is automatically compared with the hash value obtained for the first time, and the verification of the paper contract picture or the electronic contract document is completed through the comparison result.
Specifically, the related paper contract picture can be in a PNG or JPEG format;
and inserting the related paper contract picture into PDF or WORD to generate an electronic contract document in PDF or WORD format.
Specifically, the related hash algorithm is any one of an SM3 algorithm, an SHA128 algorithm, an SHA256 algorithm, and an MD5 algorithm.
Specifically, the obtained hash value is directly saved at the designated position of the paper contract picture or the electronic contract document in a watermark mode.
Specifically, the hash value obtained by hashing the continuous character string by using the hash algorithm may be separately stored.
Secondly, the paper contract credit enhancement system based on OCR and Hash algorithm of the invention adopts the following technical scheme to solve the technical problems:
a paper contract credit enhancement system based on OCR and hash algorithm comprises the following implementation structures:
the acquisition module is used for acquiring a paper contract sample and acquiring a paper contract picture or an electronic contract document to be identified;
the training module is used for training a paper contract sample by utilizing a CNN convolutional neural network to obtain an OCR recognition model;
the OCR recognition model is used for extracting the text content in the paper contract picture or the electronic contract document and generating a continuous character string;
the hash algorithm module is used for carrying out hash hashing on the continuous character strings to obtain corresponding hash values;
and the processing module is used for adding the obtained hash value to the specified position of the paper contract picture or the electronic contract document and storing or printing the paper contract picture or the electronic contract document.
The structure of the paper contract credit enhancement system also comprises a verification module;
and for the identified paper contract pictures or electronic contract documents, the verification module automatically compares the two hash values of the same paper contract picture or electronic contract document, and outputs the result of passing the verification when the comparison results are consistent.
Specifically, the related paper contract picture can be in a PNG or JPEG format;
and inserting the related paper contract picture into PDF or WORD to generate an electronic contract document in PDF or WORD format.
Specifically, the related hash algorithm module selects SM3 algorithm/SHA 128 algorithm/SHA 256 algorithm/MD 5 algorithm;
the processing module directly stores the obtained hash value at the designated position of the paper contract picture or the electronic contract document in a watermark mode, or the processing module independently stores the obtained hash value.
Compared with the prior art, the paper contract credit enhancement method and system based on OCR and Hash algorithm have the advantages that:
according to the invention, the watermark is added at the appointed position of the paper contract picture or the electronic contract document by utilizing the OCR and the Hash algorithm, so that the safety index of the paper contract picture or the electronic contract document is improved, and the quick verification of the paper contract picture or the electronic contract document is realized.
Drawings
FIG. 1 is a flow chart of a method according to a first embodiment of the present invention;
fig. 2 is a block diagram of module connection according to a second embodiment of the present invention.
The reference information in the drawings indicates:
1. an acquisition module, 2, a training module, 3, an OCR recognition model, 4, a Hash algorithm module,
5. and the processing module 6 is a checking module.
Detailed Description
In order to make the technical scheme, the technical problems to be solved and the technical effects of the present invention more clearly apparent, the following technical scheme of the present invention is clearly and completely described with reference to the specific embodiments.
The first embodiment is as follows:
with reference to fig. 1, the embodiment provides a paper contract credit enhancement method based on OCR and hash algorithm, and the implementation content of the method includes:
and S1, obtaining a paper contract sample, and training the paper contract sample by using the CNN convolutional neural network to obtain an OCR recognition model.
And step S2, acquiring the paper contract picture or the electronic contract document to be identified, extracting the text content in the paper contract picture or the electronic contract document by using an OCR (optical character recognition) model, and generating a continuous character string.
In this embodiment, the paper contract picture may be in a PNG or JPEG format;
the paper contract picture is inserted into PDF or WORD, and an electronic contract document in PDF or WORD format can be generated.
And step S3, carrying out hash hashing on the continuous character strings by using a hash algorithm to obtain corresponding hash values.
In this embodiment, the hash algorithm is any one of an SM3 algorithm, an SHA128 algorithm, an SHA256 algorithm, and an MD5 algorithm.
And step S4, directly storing the obtained hash value at the appointed position of the paper contract picture or the electronic contract document in a watermark mode, and storing or printing the paper contract picture or the electronic contract document.
Of course, the resulting hash value may also be saved separately.
Example two:
with reference to fig. 2, the embodiment provides a paper contract credit enhancement system based on OCR and hash algorithm, and the implementation structure of the system includes an obtaining module 1, a training module 2, an OCR recognition model 3, a hash algorithm module 4, and a processing module 5.
The acquisition module 1 is used for acquiring a paper contract sample on one hand and acquiring a paper contract picture or an electronic contract document to be identified on the other hand. The paper contract picture can be in PNG or JPEG format; and inserting the paper contract picture into PDF or WORD to generate an electronic contract document in PDF or WORD format.
The training module 2 is used for training a paper contract sample by using a CNN convolutional neural network to obtain an OCR recognition model 3.
The OCR recognition model 3 is used to extract text contents in a paper contract picture or an electronic contract document and generate a continuous character string.
The SM3 algorithm/SHA 128 algorithm/SHA 256 algorithm/MD 5 algorithm is selected as the hash algorithm module 4, and the hash algorithm module 4 performs hash on the continuous character strings to obtain corresponding hash values.
The processing module 5 directly stores the obtained hash value at the designated position of the paper contract picture or the electronic contract document in a watermark mode, or the processing module 5 separately stores the obtained hash value and then stores or prints the paper contract picture or the electronic contract document.
In order to further enhance the credit of the contract and avoid errors in extracting information, the structure of the paper contract credit enhancement system also comprises a verification module 6. For the identified paper contract pictures or electronic contract documents, the verification module 6 automatically compares the two hash values of the same paper contract picture or electronic contract document, and outputs the result of passing the verification when the comparison results are consistent.
In summary, the method and the system for enhancing the paper contract credit based on the OCR and the Hash algorithm can improve the safety index of the paper contract picture or the electronic contract document and realize the quick verification of the paper contract picture or the electronic contract document.
The principles and embodiments of the present invention have been described in detail using specific examples, which are provided only to aid in understanding the core technical content of the present invention. Based on the above embodiments of the present invention, those skilled in the art should make any improvements and modifications to the present invention without departing from the principle of the present invention, and therefore, the present invention should fall into the protection scope of the present invention.
Claims (10)
1. A paper contract credit enhancement method based on OCR and hash algorithm is characterized in that the realization content comprises the following steps:
s1, obtaining a paper contract sample, and training the paper contract sample by using a CNN convolutional neural network to obtain an OCR recognition model;
s2, acquiring a paper contract picture or an electronic contract document to be identified, extracting the text content in the paper contract picture or the electronic contract document by using an OCR (optical character recognition) model, and generating a continuous character string;
step S3, carrying out hash hashing on the continuous character strings by using a hash algorithm to obtain corresponding hash values;
and step S4, adding the obtained hash value to the appointed position of the paper contract picture or the electronic contract document, and saving or printing the paper contract picture or the electronic contract document.
2. An OCR and Hash algorithm based paper contract credit enhancement method as claimed in claim 1, wherein the steps S2-S3 are executed again for the identified paper contract picture or electronic contract document, the hash value obtained this time is compared with the hash value obtained for the first time automatically, and the verification of the paper contract picture or electronic contract document is completed through the comparison result.
3. An OCR and Hash algorithm based paper contract credit enhancement method as claimed in claim 1, wherein the paper contract picture can be in PNG or JPEG format;
and inserting the paper contract picture into PDF or WORD to generate an electronic contract document in PDF or WORD format.
4. An OCR and hash algorithm based paper contract credit enhancement method as claimed in claim 1, wherein the hash algorithm selects any one of SM3 algorithm, SHA128 algorithm, SHA256 algorithm, MD5 algorithm.
5. An OCR and hash algorithm based paper contract credit enhancement method as claimed in claim 1, wherein the obtained hash value is directly saved at the designated position of the paper contract picture or the electronic contract document by means of watermark.
6. An OCR and Hash algorithm based paper contract credit enhancement method as claimed in claim 1, wherein the hash value obtained by Hash hashing consecutive character strings using Hash algorithm can also be stored separately.
7. A paper contract credit enhancement system based on OCR and hash algorithm is characterized in that the implementation structure comprises:
the acquisition module is used for acquiring a paper contract sample and acquiring a paper contract picture or an electronic contract document to be identified;
the training module is used for training a paper contract sample by utilizing a CNN convolutional neural network to obtain an OCR recognition model;
the OCR recognition model is used for extracting the text content in the paper contract picture or the electronic contract document and generating a continuous character string;
the hash algorithm module is used for carrying out hash hashing on the continuous character strings to obtain corresponding hash values;
and the processing module is used for adding the obtained hash value to the specified position of the paper contract picture or the electronic contract document and storing or printing the paper contract picture or the electronic contract document.
8. An OCR and hashing algorithm based paper contract credit enhancement system according to claim 7, further comprising a verification module;
and for the identified paper contract pictures or electronic contract documents, the verification module automatically compares the two hash values of the same paper contract picture or electronic contract document, and outputs the result of passing the verification when the comparison results are consistent.
9. An OCR and Hash algorithm based paper contract credit enhancement system in accordance with claim 7, wherein the paper contract picture can be in PNG or JPEG format;
and inserting the paper contract picture into PDF or WORD to generate an electronic contract document in PDF or WORD format.
10. An OCR and hash algorithm based paper contract credit enhancement system as claimed in claim 7, wherein said hash algorithm module selects SM3 algorithm/SHA 128 algorithm/SHA 256 algorithm/MD 5 algorithm;
the processing module directly stores the obtained hash value at the designated position of the paper contract picture or the electronic contract document in a watermark mode, or the processing module independently stores the obtained hash value.
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| CN202110538654.XA CN113516044A (en) | 2021-05-18 | 2021-05-18 | Paper contract credit enhancement method and system based on OCR and Hash algorithm |
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