CN112434498B - Intelligent form construction method based on cloud platform - Google Patents
Intelligent form construction method based on cloud platform Download PDFInfo
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- CN112434498B CN112434498B CN202011436326.0A CN202011436326A CN112434498B CN 112434498 B CN112434498 B CN 112434498B CN 202011436326 A CN202011436326 A CN 202011436326A CN 112434498 B CN112434498 B CN 112434498B
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- 238000010276 construction Methods 0.000 title claims abstract description 9
- 238000000034 method Methods 0.000 claims abstract description 15
- 230000001172 regenerating effect Effects 0.000 claims abstract description 4
- 230000005540 biological transmission Effects 0.000 claims description 15
- 230000009467 reduction Effects 0.000 claims description 13
- 230000003287 optical effect Effects 0.000 claims description 3
- 230000004048 modification Effects 0.000 abstract description 6
- 238000012986 modification Methods 0.000 abstract description 6
- 238000004364 calculation method Methods 0.000 description 2
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/177—Editing, e.g. inserting or deleting of tables; using ruled lines
- G06F40/18—Editing, e.g. inserting or deleting of tables; using ruled lines of spreadsheets
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/183—Tabulation, i.e. one-dimensional positioning
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- G06T5/70—
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/22—Image preprocessing by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
- G06V30/10—Character recognition
- G06V30/14—Image acquisition
- G06V30/148—Segmentation of character regions
- G06V30/153—Segmentation of character regions using recognition of characters or words
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/06—Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
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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
- H04N1/00095—Systems or arrangements for the transmission of the picture signal
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
- G06T2207/20064—Wavelet transform [DWT]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
- G06V30/10—Character recognition
Abstract
The invention provides an intelligent form construction method based on a cloud platform, which comprises the steps of S1, obtaining a form image of a paper form needing to be modified, and transmitting the form image to the cloud platform; s2, identifying the form image in the cloud platform, and acquiring form items contained in the paper form and relative position information among the form items; s3, regenerating the electronic form in the cloud platform based on the form items and the relative position information between the form items. The method can be well suitable for large-scale form modification work, and is undoubtedly quicker and higher in efficiency compared with manual form re-editing.
Description
Technical Field
The invention relates to the field of form construction, in particular to a cloud platform-based intelligent form construction method.
Background
In the existing economic life, the situation that various paper forms need to be modified and then printed again is often encountered, when electronic documents of the paper forms do not exist, only manual re-use of editing software can be used for re-compiling an electronic form according to the paper forms, then the contents in the electronic form are modified according to the needs, so that the modified electronic form is obtained, and the electronic form is printed to obtain the re-printed electronic form. This is time consuming and inefficient if the number of electronic forms that need to be modified is excessive.
Disclosure of Invention
In view of the above problems, the present invention aims to provide a method for constructing a smart form based on a cloud platform.
The invention provides a cloud platform-based intelligent form construction method, which comprises the following steps:
s1, obtaining a form image of a paper form to be modified, and transmitting the form image to a cloud platform;
s2, identifying the form image in the cloud platform, and acquiring form items contained in the paper form and relative position information among the form items;
s3, regenerating the electronic form in the cloud platform based on the form items and the relative position information between the form items.
Preferably, obtaining a form image of a paper form requiring modification comprises: the method comprises the steps of obtaining a form image of a paper form needing to be modified through a scanner or a shooting device, and storing the form image in a local computing terminal.
Preferably, transmitting the form image to a cloud platform includes:
transmitting the form image to a cloud platform in a wired transmission or wireless transmission mode;
transmitting the form image to a cloud platform in a wired transmission mode, wherein the method comprises the following steps: the computing terminal transmits the form image to a router through a transmission optical cable, and the router transmits the form image to the cloud platform through the Internet;
transmitting the form image to a cloud platform in a wireless transmission mode, including: the computing terminal transmits the form image to a router through a WiFi network, and the router transmits the form image to the cloud platform through the Internet.
Preferably, the form entry is obtained by:
and performing character recognition on the form image to obtain a form item.
Preferably, the relative position information between the respective form items is obtained by:
randomly selecting a form item, and establishing a rectangular coordinate system by taking a pixel point in the center of a first character in the form item as an origin of a coordinate system;
taking the position of the first character in each form item in the rectangular coordinate system as the coordinate of the form item;
based on the coordinates of the respective form items, relative position information between the respective form items is calculated.
Preferably, the form item includes a data item name and a content corresponding to the data item.
Compared with the prior art, the invention has the advantages that:
according to the method and the device, the form image is identified through the cloud platform, the electronic form is regenerated based on the form items obtained through identification and the relative position relation among the form items, and then a user can modify the electronic form as required and reprint the modified electronic form, so that a modified paper form file is obtained. The method can be well suitable for large-scale form modification work, and is undoubtedly quicker and higher in efficiency compared with manual form re-editing.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a diagram of an exemplary embodiment of a method for constructing a smart form based on a cloud platform according to the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In one embodiment as shown in fig. 1, the invention provides a cloud platform-based smart form construction method, which comprises the following steps:
s1, obtaining a form image of a paper form to be modified, and transmitting the form image to a cloud platform;
s2, identifying the form image in the cloud platform, and acquiring form items contained in the paper form and relative position information among the form items;
s3, regenerating the electronic form in the cloud platform based on the form items and the relative position information between the form items.
The user can further modify the electronic form according to actual needs after obtaining the electronic form to obtain the electronic form after the modification, compare in the manual mode of reediting the electronic form of manual work, this application is undoubtedly more convenient.
Preferably, obtaining a form image of a paper form requiring modification comprises: the method comprises the steps of obtaining a form image of a paper form needing to be modified through a scanner or a shooting device, and storing the form image in a local computing terminal.
The local computing terminal can be a smart phone, various computers, a singlechip and the like.
Preferably, transmitting the form image to a cloud platform includes:
transmitting the form image to a cloud platform in a wired transmission or wireless transmission mode;
transmitting the form image to a cloud platform in a wired transmission mode, wherein the method comprises the following steps: the computing terminal transmits the form image to a router through a transmission optical cable, and the router transmits the form image to the cloud platform through the Internet;
transmitting the form image to a cloud platform in a wireless transmission mode, including: the computing terminal transmits the form image to a router through a WiFi network, and the router transmits the form image to the cloud platform through the Internet.
Preferably, the form entry is obtained by:
and performing character recognition on the form image to obtain a form item.
Preferably, the relative position information between the respective form items is obtained by:
randomly selecting a form item, and establishing a rectangular coordinate system by taking a pixel point in the center of a first character in the form item as an origin of a coordinate system;
taking the position of the first character in each form item in the rectangular coordinate system as the coordinate of the form item;
based on the coordinates of the respective form items, relative position information between the respective form items is calculated.
Preferably, the method for using the central pixel point of the first character in the form item as the origin of the coordinate system includes:
storing pixel points contained in the characters into a set U1, arbitrarily selecting one pixel point as an origin of coordinates for the pixel points contained in U1, and establishing a rectangular coordinate system of the region;
calculate the average coordinates of the pixel points in U1:
in the formula, nfU1 represents the total number of pixels in U1, xiRepresents the abscissa, y, of the pixel point i in the U1 in the rectangular coordinate system of the regioniRepresents the ordinate, avep, of the pixel point i in the U1 in the rectangular region coordinate systemxDenotes the abscissa, avep, in mean coordinatesyDenotes the ordinate in the mean coordinate, (avep)x，avepy) And (4) representing average coordinates, and taking a pixel point which is closest to the average coordinates in U1 as a pixel point at the center of the first character.
By setting the coordinates in such a way, compared with the coordinate in which the center of the form item is directly used as the form item, the calculation amount is less, the calculation speed is higher, and the method is favorable for quickly positioning each form item.
Preferably, performing character recognition on the form image to obtain a form item, including:
adjusting the brightness of the form image to obtain a brightness adjustment image;
converting the brightness adjustment image into a gray image;
carrying out noise reduction processing on the gray level image to obtain a noise reduction image;
carrying out binarization processing on the noise-reduced image to obtain a binarized image;
and carrying out character recognition processing on the binary image by using a character recognition algorithm to obtain a form item.
Preferably, the adjusting brightness of the form image to obtain a brightness-adjusted image includes:
adjusting brightness of the form image by:
converting the form image into a Lab color space, recording coordinates of a pixel point which is currently subjected to brightness adjustment as (x, y), and recording a pixel value of the pixel point as br (x, y), wherein br (x, y) represents a numerical value of a brightness component of the pixel point in the Lab color space;
if br (x, y) < ythre, processing the pixel point with the coordinate (x, y) by using the following formula:
in the formula, abr (x, y) represents a pixel value in the Lab color space after processing a pixel point with coordinates (x, y), tj1 represents a preset first control coefficient, te represents the total number of L components of different values of the form image in the Lab color space, and ythre represents a judgment threshold;
if br (x, y) is more than or equal to ythre, processing the pixel point with the coordinate (x, y) by using the following formula:
in the formula, tj2 represents a preset second control coefficient;
and after the brightness adjustment of all pixel points in the form image is finished, converting the Lab color space into the RGB color space to obtain a brightness adjustment image.
By converting the image into the Lab color space, the influence of color factors on brightness adjustment can be avoided, and a more accurate brightness adjustment result can be obtained. When the specific brightness adjustment is carried out, the pixel point currently being processed is compared with the judgment threshold value, and then different processing functions are selected in a self-adaptive mode to carry out the brightness adjustment processing on the pixel point currently being processed, so that the processing process is more pertinent, the processing accuracy is improved, a high-quality image is provided for subsequent character recognition, and the influence of factors such as unbalanced brightness on the subsequent image recognition is avoided.
Preferably, the determination threshold is a threshold calculated by using the ohd method for the form image.
Preferably, the performing noise reduction processing on the grayscale image to obtain a noise-reduced image includes:
detecting pulse noise points in the gray level image, and performing pulse noise reduction processing on all the pulse noise points to obtain a pulse noise reduction image;
and performing wavelet denoising processing on the pulse denoising image to obtain a final denoising image.
The image is subjected to noise reduction treatment in a noise point detection mode, so that the problem of excessively low processing speed caused by noise reduction treatment on all pixel points can be solved.
Preferably, detecting impulse noise in the grayscale image comprises:
calculating the pulse index of a pixel point in the gray level image:
wherein ge represents a pixel point in a gray scale image, mcidx (ge) represents a pulse index of the pixel point in ge, nei represents a set of pixel points in a neighborhood with a preset size of ge, h (k) represents a pixel value of a pixel point k in nei, h (ge) represents a pixel value of ge, ma (h) (k) -h (ge)) represents a maximum value of h (k) -h (ge), mi (h (k) -h (ge)) represents a minimum value of h (k) -h (ge)), neni represents a total number of the pixel points in nei, tjm represents a preset constant type adjustment parameter, fc1 represents a variance of pixel points of all pixel points in nei which are the same as the horizontal coordinate of ge, and fc2 represents a variance of pixel points of all pixel points in nei which are the same as the vertical coordinate of ge;
and comparing the pulse index with a preset index threshold, and if the pulse index is greater than the index threshold, determining the pixel point as a pulse noise point.
Preferably, the pulse noise reduction processing is performed on the pulse noise, and comprises the following steps:
pulse noise reduction processing using the following formula
In the formula, h (t) represents a pixel value of the impulse noise t, ah (t) represents a pixel value of the impulse noise t after the impulse noise reduction processing, Φ 1 and Φ 2 represent proportional parameters, Φ 1+ Φ 2 ═ 1, pj represents a mean value of pixel values of pixels in a neighborhood of a preset size of the impulse noise t, dy1 represents a total number of pixels in the neighborhood whose gradient amplitude is greater than that of the impulse noise t, dy2 represents a total number of pixels in the neighborhood whose gradient amplitude is less than that of the impulse noise t, and δ represents a preset control coefficient.
Whether the pixel point is the pulse noise point or not is judged through the pulse index, and the phenomenon that the edge pixel point is mistaken for the pulse noise point can be effectively avoided instead of only considering the pixel of the pixel point. When the pulse index is calculated, the relationship between the pulse pixel and the pixel in the neighborhood of the pulse pixel is fully considered, and whether the current pixel is an edge pixel or not is judged through fc1 and fc2, so that a more accurate noise reduction effect is obtained.
Preferably, the form item includes a data item name and a content corresponding to the data item.
The content can be characters or numbers. Data items such as "name", "number", "weight", etc. are data items, and the corresponding contents of the data items are "specific name", "specific number of values", "specific weight of values", respectively.
While embodiments of the invention have been shown and described, it will be understood by those skilled in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
Claims (3)
1. A smart form construction method based on a cloud platform is characterized by comprising the following steps:
s1, obtaining a form image of a paper form to be modified, and transmitting the form image to a cloud platform;
s2, identifying the form image in the cloud platform, and acquiring form items contained in the paper form and relative position information among the form items;
s3, regenerating the electronic form in the cloud platform based on the form items and the relative position information between the form items;
the acquiring of the form image of the paper form to be modified includes: acquiring a form image of a paper form to be modified through a scanner or a shooting device, and storing the form image in a local computing terminal;
the transmitting the form image to a cloud platform includes:
transmitting the form image to a cloud platform in a wired transmission or wireless transmission mode;
transmitting the form image to a cloud platform in a wired transmission mode, wherein the method comprises the following steps:
the computing terminal transmits the form image to a router through a transmission optical cable, and the router transmits the form image to the cloud platform through the Internet;
transmitting the form image to a cloud platform in a wireless transmission mode, including:
the computing terminal transmits the form image to a router through a WiFi network, and the router transmits the form image to the cloud platform through the Internet;
the form item is obtained by:
performing character recognition on the form image to obtain a form item;
performing character recognition on the form image to obtain a form item, wherein the character recognition comprises the following steps:
adjusting the brightness of the form image to obtain a brightness adjustment image;
converting the brightness adjustment image into a gray image;
carrying out noise reduction processing on the gray level image to obtain a noise reduction image;
carrying out binarization processing on the noise-reduced image to obtain a binarized image;
carrying out character recognition processing on the binary image by using a character recognition algorithm to obtain a form item;
the adjusting the brightness of the form image to obtain a brightness adjusted image includes:
adjusting brightness of the form image by:
converting the form image into a Lab color space, recording coordinates of a pixel point which is currently subjected to brightness adjustment as (x, y), and recording a pixel value of the pixel point as br (x, y), wherein br (x, y) represents a numerical value of a brightness component of the pixel point in the Lab color space;
if br (x, y) < ythre, processing the pixel point with the coordinate (x, y) by using the following formula:
in the formula, abr (x, y) represents a pixel value in the Lab color space after processing a pixel point with coordinates (x, y), tj1 represents a preset first control coefficient, te represents the total number of L components of different values of the form image in the Lab color space, and ythre represents a judgment threshold;
if br (x, y) is more than or equal to ythre, processing the pixel point with the coordinate (x, y) by using the following formula:
in the formula, tj2 represents a preset second control coefficient;
and after the brightness adjustment of all pixel points in the form image is finished, converting the Lab color space into the RGB color space to obtain a brightness adjustment image.
2. The cloud platform-based smart form construction method according to claim 1, wherein the relative position information between the form items is obtained by:
randomly selecting a form item, and establishing a rectangular coordinate system by taking a pixel point in the center of a first character in the form item as an origin of a coordinate system;
taking the position of the first character in each form item in the rectangular coordinate system as the coordinate of the form item;
based on the coordinates of the respective form items, relative position information between the respective form items is calculated.
3. The cloud platform-based smart form building method of claim 2, wherein the form item includes a data item name and a content corresponding to the data item.
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| US9041727B2 (en) * | 2012-03-06 | 2015-05-26 | Apple Inc. | User interface tools for selectively applying effects to image |
| US10318576B2 (en) * | 2013-12-12 | 2019-06-11 | Nant Holdings Ip, Llc | Image recognition verification |
| CN109191466A (en) * | 2018-07-19 | 2019-01-11 | 中国矿业大学 | A kind of image partition method and system based on spectral clustering |
| CN109684957A (en) * | 2018-12-14 | 2019-04-26 | 新博卓畅技术（北京）有限公司 | A kind of method and system showing system data according to paper form automatically |
| CN112464629B (en) * | 2019-09-09 | 2024-01-16 | 钉钉控股（开曼）有限公司 | Form filling method and device |
| CN111538975B (en) * | 2020-04-27 | 2024-02-23 | 中国银行股份有限公司 | Image processing method and device |
| CN111666520A (en) * | 2020-05-14 | 2020-09-15 | 深圳思为科技有限公司 | Method and device for generating electronic form based on form image |
| CN111986222A (en) * | 2020-08-21 | 2020-11-24 | 国网宁夏电力有限公司营销服务中心(国网宁夏电力有限公司计量中心) | Intelligent electric meter chip image binarization processing method based on self-adaptive mixed threshold value |
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