WO2023216745A1

WO2023216745A1 - Table reconstruction method and electronic device

Info

Publication number: WO2023216745A1
Application number: PCT/CN2023/084482
Authority: WO
Inventors: 王伟印; 张晓程
Original assignee: 上海弘玑信息技术有限公司
Priority date: 2022-05-13
Filing date: 2023-03-28
Publication date: 2023-11-16
Also published as: CN114943978A; CN114943978B

Abstract

The present application belongs to the technical field of data processing. Disclosed are a table reconstruction method and an electronic device. The method comprises: performing text recognition on an image to be processed, so as to obtain a text area recognition result of said image, wherein the text area recognition result includes area text content and area position information of a text area; according to the area position information, determining each table row coordinate and each table column coordinate of a target table; generating a blank table according to each table row coordinate and each table column coordinate; and according to the area position information, adding the area text content into the blank table, so as to obtain the target table. In this way, a framed table or a frameless table in an image to be processed can be reconstructed, thereby improving the accuracy and application range of table reconstruction.

Description

A table reconstruction method and electronic device

Cross-references to related applications

This application claims priority to the Chinese patent application submitted to the China Patent Office on May 13, 2022, with application number 202210523453.7 and application title "A method and electronic device for table reconstruction", the entire content of which is incorporated herein by reference. Applying.

Technical field

The present application relates to the field of data processing technology, specifically, to a table reconstruction method and electronic equipment.

Background technique

With the development of information technology and the popularization of paperless information office, people have higher and higher requirements for the convenience of data processing. In some office scenarios, it is usually necessary to perform table recognition and table reconstruction on table images to obtain reconstructed tables.

Under the existing technology, image processing operations such as dilation and corrosion are usually used to determine the lines in the table image, and the table is reconstructed based on the coordinates of each line and the intersection point of each line.

However, if the table in the table image contains borderless cells or cells with unclear borders, there will be a certain deviation in the reconstructed table using this method.

Contents of the invention

The purpose of the embodiments of the present application is to provide a table reconstruction method and electronic device, so as to reduce the deviation of the reconstructed table when reconstructing the table in the table image.

On the one hand, a method for table reconstruction is provided, including:

Perform text recognition on the image to be processed, and obtain the text area recognition result of the image to be processed. The text area recognition result contains the regional text content and regional location information of the text area;

According to the regional location information, determine the row coordinates of each table and the coordinates of each table column of the target table;

Generate a blank table based on the row coordinates of each table and the coordinates of each table column;

According to the regional location information, add the regional text content to the blank table to obtain the target table.

In the above implementation process, the table is reconstructed through the regional text content and regional position information of each text area identified in the image to be processed. The framed table in the image to be processed can also be reconstructed without a frame in the image to be processed. table, improving the accuracy of table reconstruction.

In one embodiment, the area position information includes the area vertex coordinates of the text area. Performing text recognition on the image to be processed and obtaining the text area recognition result of the image to be processed includes: performing text detection on the image to be processed and obtaining multiple areas of the text area. Vertex coordinates, the area vertex coordinates are the coordinates of the vertices of the text area; perform text recognition on the text area to obtain the area text content.

In the above implementation process, text recognition is performed on the graph to be processed, and the vertex coordinates of each area in the text area and the text content of the area are determined, so that the location and content of each text area can be accurately identified.

In one implementation, the regional vertex coordinates include the regional vertex abscissa and the regional vertex ordinate. According to the regional position information, determining the table row coordinates and the table column coordinates of the target table includes: determining the maximum ordinate in each region vertex. The ordinate and the minimum ordinate; determine the maximum abscissa and the minimum abscissa in the abscissa of each area vertex; According to the area position information, determine the number of first areas for each ordinate and the number of second areas for each abscissa. The first area number is the number of text areas containing a certain ordinate, and the second area number is the number of text areas containing a certain horizontal coordinate. The number of text areas for coordinates; determine the coordinates of each table row based on the maximum ordinate, the minimum ordinate, and the number of first areas; determine the coordinates of each table column based on the maximum abscissa, the minimum abscissa, and the number of second areas.

In the above implementation process, the row coordinates and column coordinates of each table are determined through the location of each text area, and the rows and columns of the frameless table can be identified, which improves the accuracy of table reconstruction.

In one implementation, determining the coordinates of each table row based on the maximum ordinate, the minimum ordinate, and the number of first areas includes: determining the trough ordinate and the trough ordinate based on each ordinate and its corresponding number of first areas. The number of first areas is not higher than the number of first areas in the adjacent ordinates of the trough ordinate, and the adjacent ordinates of the trough ordinate are the previous ordinate and the next ordinate of the trough ordinate; according to the maximum ordinate, The minimum vertical coordinate, and the trough vertical coordinate, are used to obtain the coordinates of each table row.

In the above implementation process, since the number of text areas traversed by the horizontal lines where the table row coordinates are located is relatively small, the table row coordinates are determined based on the number of first areas of the text areas traversed by the horizontal lines where the vertical coordinates are located. .

In one implementation, determining the coordinates of each table column according to the maximum abscissa, the minimum abscissa, and the number of second areas includes: determining the trough abscissa and the trough abscissa according to each abscissa and its corresponding number of second areas. The number of second areas is not higher than the number of second areas of the adjacent abscissa of the wave trough abscissa, and the adjacent abscissas of the wave trough abscissa are the previous abscissa and the next abscissa of the trough abscissa; according to the maximum abscissa, The minimum abscissa and the trough abscissa are used to obtain the coordinates of each table column.

In the above implementation process, since the number of text areas that the vertical lines where the table column coordinates are located passes through is relatively small, therefore, the table column coordinates are determined based on the number of second areas of the text areas where the vertical lines where the abscissa coordinates are located pass through. .

In one embodiment, after generating a blank table based on each table row coordinate and each table column coordinate, the method further includes: determining the cell position information of the cells in the blank table based on each table row coordinate and each table column coordinate; According to the area position information and cell position information, determine the target cell covered by the text area; among them, there are coordinate points in the text area that are located in the target cell and do not coincide with the boundary of the target cell; if it is determined that the text area covers If there are multiple target cells, merge the target cells.

In the above implementation process, multiple target cells covered by the text area are merged according to the area where the cell is located and the area where the text area is located, thereby solving the problem of how to set merged cells that exist in the table.

In one implementation, adding the regional text content to the blank table according to the regional location information to obtain the target table includes: performing the following steps for each cell in the blank table: if based on the regional location information, determine a If the cell only contains one text area, then the area text content in the text area contained in a cell is added to a cell; if it is determined based on the area position information that a cell contains at least two text areas, then the area text content is added according to the area position information. Position information, sort the regional text content in each text area contained in a cell, and add the sorted regional text content to a cell.

In the above implementation process, the regional text content of multiple text areas in the same cell is first sorted, and then the sorted regional text content is added to the cell, thus solving how to add multiple text areas to the same cell. Issues with area text content of text areas.

In one embodiment, determining that a cell contains only one text area based on the area location information includes: determining the center point coordinates of the text area based on the area location information, and the center point coordinates are the coordinates of the center point of the text area; if According to the cell position information of a cell, it is determined that the center point coordinate of only one text area is located in the cell, then it is determined that a cell contains only one text area.

In the above implementation process, the text area contained in the cell can be quickly determined based on the coordinates of the center point of the text area and the area where the cell is located.

In one implementation, adding the regional text content in the text area contained in a cell to a cell includes: setting the attribute value of the text attribute of a cell to the text area contained in the cell. The regional text content.

In the above implementation process, by setting the text attribute, you can add regional text content within the cell.

In one implementation, determining that a cell contains at least two text areas according to the area position information includes: if it is determined that the number of text areas is multiple, determining each text area separately according to the area position information of each text area. The center point coordinate of At least two text areas.

In the above implementation process, multiple text areas contained in a cell can be quickly determined based on the coordinates of the center point of the text area and the area where the cell is located.

In one implementation, the center point coordinates include the center point abscissa and the center point ordinate. Sorting the regional text content in each text area contained in a cell includes: in descending order of the center point ordinate. , sort the regional text content in each text area contained in a cell; sort the regional text content in each text area with the same central point ordinate in ascending order of the center point abscissa.

In the above implementation process, each text area in the same cell is sorted according to the abscissa coordinate and the ordinate coordinate of the center point of each text area.

In one implementation, adding the sorted regional text content to a cell includes: setting the attribute value of a text attribute of a cell to the sorted regional text content.

On the one hand, a table reconstruction device is provided, including:

The recognition unit is used to perform text recognition on the image to be processed and obtain the text area recognition result of the image to be processed. The text area recognition result contains the regional text content and regional position information of the text area; the determination unit is used to determine based on the regional position information. The row coordinates of each table and the coordinates of each column of the target table; the generating unit is used to generate a blank table based on the row coordinates and column coordinates of each table; the obtaining unit is used to add the regional text content to the blank based on the regional location information form to obtain the target form.

In one embodiment, the regional position information includes the regional vertex coordinates of the text area, and the recognition unit is used to: perform text detection on the image to be processed, and obtain multiple regional vertex coordinates of the text area, where the regional vertex coordinates are the coordinates of the vertices of the text area; Perform text recognition on the text area to obtain the text content of the area.

In one embodiment, the regional vertex coordinates include the regional vertex abscissa and the regional vertex ordinate, and the determination unit is used to: determine the maximum ordinate and the minimum ordinate in the ordinate of each regional vertex; determine the maximum ordinate in the abscissa of each regional vertex. The abscissa and the minimum abscissa; according to the area position information, determine the number of the first area for each ordinate and the number of the second area for each abscissa. The number of the first area is the number of text areas containing a certain ordinate, and the second The number of areas is the number of text areas containing a certain abscissa; determine the coordinates of each table row based on the maximum ordinate, the minimum ordinate, and the number of first areas; determine the coordinates of each table row based on the maximum abscissa, the minimum abscissa, and the number of second areas , determine the coordinates of each table column.

In one embodiment, the determining unit is configured to: determine the trough ordinate based on each ordinate and its corresponding number of first areas, and the number of the first areas of the trough ordinate is not higher than the number of adjacent ordinates of the trough ordinate. The number of areas, The adjacent vertical coordinates of the trough vertical coordinate are the previous ordinate and the next ordinate of the trough vertical coordinate; according to the maximum ordinate, the minimum ordinate, and the trough vertical coordinate, the coordinates of each table row are obtained.

In one embodiment, the determination unit is configured to: determine the trough abscissa according to each abscissa and its corresponding number of second areas, and the number of the second areas of the trough abscissa is not higher than the number of adjacent abscissas of the trough abscissa. Second, the number of areas. The adjacent abscissas of the trough abscissa are the previous abscissa and the next abscissa of the trough. According to the maximum abscissa, the minimum abscissa, and the trough abscissa, the coordinates of each table column are obtained.

In one implementation, the generation unit is also used to: determine the cell position information of the cells in the blank table based on each table row coordinate and each table column coordinate; determine the text area coverage based on the area position information and the cell position information. The target cell; among them, there are coordinate points in the text area that are located in the target cell and do not coincide with the boundary of the target cell; if it is determined that there are multiple target cells covered by the text area, the target cells will be merged.

In one implementation, the unit is obtained by: performing the following steps for each cell in the blank table: if it is determined that a cell contains only one text area based on the area position information, then the text contained in a cell is The regional text content in the area is added to a cell; if it is determined that a cell contains at least two text areas according to the area position information, the area text in each text area contained in a cell is added according to the area position information. Sort the content and add the sorted range text content to a cell.

In one implementation, the obtaining unit is used to: determine the center point coordinates of the text area based on the area position information, and the center point coordinates are the coordinates of the center point of the text area; if based on the cell position information of a cell, determine only If the center point coordinates of a text area are located within the cell, it is determined that a cell contains only one text area.

In one implementation, the obtaining unit is used to: set the attribute value of the text attribute of a cell to the regional text content in the text area contained in the cell.

In one implementation, the obtaining unit is configured to: if it is determined that the number of text areas is multiple, determine the center point coordinates of each text area according to the area position information of each text area, and the center point coordinates are the center of the text area. The coordinates of the point; if based on the cell position information of a cell, it is determined that the center point coordinates of at least two text areas are located in the cell, then it is determined that a cell contains at least two text areas.

In one implementation, the center point coordinates include the center point abscissa and the center point ordinate, and the obtaining unit is used to: according to the descending order of the center point ordinate, the regional text in each text area contained in a cell is Sort the content; sort the regional text content in each text area with the same central point ordinate in ascending order of the center point's abscissa.

In one implementation, the obtaining unit is used to: set the attribute value of the text attribute of a cell to the sorted regional text content.

On the one hand, an electronic device is provided, including a processor and a memory. The memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, various optional table reconstruction methods such as those mentioned above are executed. Implement the steps for the method provided in How.

In one aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method provided in any of the above optional implementations of table reconstruction are executed.

On the one hand, a computer program product is provided. When the computer program product is run on a computer, it causes the computer to perform the steps of the method provided in any of the above optional implementations of table reconstruction.

Additional features and advantages of the application will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

Description of drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present application, therefore This should not be regarded as limiting the scope. For those of ordinary skill in the art, other relevant drawings can be obtained based on these drawings without exerting creative efforts.

Figure 1 is a flow chart of a table reconstruction method provided by an embodiment of the present application;

Figure 2 is an example diagram of a user attribute table image provided by an embodiment of the present application;

Figure 3 is a specific flow chart of a method for reconstructing a user attribute table provided by an embodiment of the present application;

Figure 4 is an example diagram 1 of a first curve provided by the embodiment of the present application;

Figure 5 is an example diagram 1 of a second curve provided by the embodiment of the present application;

Figure 6 is an example diagram of merging table images provided by the embodiment of the present application;

Figure 7 is a specific flow chart of a method for merging table reconstruction provided by an embodiment of the present application;

Figure 8 is an example of Figure 2 of a first curve provided by the embodiment of the present application;

Figure 9 is an example of Figure 2 of a second curve provided by the embodiment of the present application;

Figure 10 is a structural block diagram of a table reconstruction device provided by an embodiment of the present application;

Figure 11 is a schematic structural diagram of an electronic device in an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations. Accordingly, the following detailed description of the embodiments of the application provided in the appended drawings is not intended to limit the scope of the claimed application, but rather to represent selected embodiments of the application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without any creative work shall fall within the scope of protection of this application.

It should be noted that similar reference numerals and letters represent similar items in the following figures, therefore, once an item is defined in one figure, it does not need further definition and explanation in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", etc. are only used to differentiate the description and cannot be understood as indicating or implying relative importance.

First, some terms involved in the embodiments of this application will be described to facilitate understanding by those skilled in the art.

Terminal device: It can be a mobile terminal, a fixed terminal or a portable terminal, such as a mobile phone, a site, a unit, a device, a multimedia computer, a multimedia tablet, an Internet node, a communicator, a desktop computer, a laptop computer, a notebook computer, a netbook computer, Tablet computers, personal communication system devices, personal navigation devices, personal digital assistants, audio/video players, digital cameras/camcorders, positioning devices, television receivers, radio broadcast receivers, e-book devices, gaming devices, or any combination thereof, Includes accessories and peripherals for these devices or any combination thereof. It is also foreseeable that the terminal device can support any type of user-oriented interface (such as wearable devices), etc.

Server: It can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers. It can also provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, Cloud servers for middleware services, domain name services, security services, and basic cloud computing services such as big data and artificial intelligence platforms.

Optical Character Recognition (OCR): refers to electronic equipment checking characters printed on paper, determining their shape by detecting dark and light patterns, and then using character recognition methods to translate the shape into computer text the process of.

In order to reduce the deviation of the reconstructed table when reconstructing the table in the table image. Embodiments of the present application provide a table reconstruction method and electronic device.

In this embodiment of the present application, the execution subject is an electronic device. Optionally, the electronic device may be a server or a terminal device.

Refer to Figure 1, which is a flow chart of a table reconstruction method provided by an embodiment of the present application. The specific implementation process of the method is as follows:

Step 100: Perform text recognition on the image to be processed, and obtain the text area recognition result of the image to be processed.

Specifically, when performing step 100, the following steps can be adopted:

S1001: Perform text detection on the image to be processed and obtain multiple area vertex coordinates of the text area.

In one implementation, if the text area is a rectangle, text detection is performed on the image to be processed to obtain the regional vertex coordinates of one or more rectangular text areas.

It should be noted that the coordinates of the area vertices are the coordinates of the vertices of the text area. The coordinates of the regional vertex include the horizontal coordinate of the regional vertex and the vertical coordinate of the regional vertex. Since the text area is a rectangle, the number of area vertex coordinates of each text area is 4.

In actual applications, the text area can also be in other shapes, such as a quadrilateral, which is not limited here.

S1002: Perform text recognition on the text area and obtain the text content of the area.

In one implementation, OCR technology is used to perform text recognition on the text area to obtain regional text content in the text area.

Among them, the regional text content is the information recognized in the text area. Regional text content can include at least one of the following: text, formulas, and dates.

In actual applications, the regional text content can also be other types of information, which is not limited here.

S1003: Based on the regional vertex coordinates and regional text content of the text area, obtain the text area recognition result of the image to be processed.

Among them, the text area recognition result includes the area text content and area location information of the text area. The area position information includes the area vertex coordinates of the text area.

In one implementation, the region vertex coordinates are used as the region position information in the text area recognition result.

Step 101: Determine the coordinates of each table row and each table column of the target table based on the area position information in the text area recognition result.

Specifically, when performing step 101, the following steps can be taken:

S1011: Determine the maximum ordinate and the minimum ordinate among the ordinates of the vertices of each region.

In one implementation, if there are multiple text areas, then the maximum ordinate and the minimum ordinate among the ordinates of all area vertices of each text area are determined.

S1012: Determine the maximum abscissa coordinate and the minimum abscissa coordinate among the vertex abscissas of each area.

In one implementation, if there are multiple text areas, then the maximum abscissa and the minimum abscissa of the abscissas of all area vertices of each text area are determined.

In this way, the boundary of the target table can be determined by the maximum ordinate, minimum ordinate, maximum abscissa, and minimum abscissa.

S1013: Determine the number of first regions for each ordinate and the number of second regions for each abscissa according to the region location information.

Among them, the first area quantity is the number of text areas containing a certain vertical coordinate, and the second area quantity is the number of text areas containing a certain abscissa. It should be noted that the text area contains a certain vertical coordinate, which means that the vertical coordinate of the coordinate point in the text area is the above-mentioned certain vertical coordinate. The text area contains a certain abscissa, which means that the abscissa of the coordinate point in the text area is the above-mentioned abscissa.

In one implementation, the abscissa interval and ordinate interval of the text area are determined based on the regional position information of the text area. If it is determined that a certain ordinate is located within the ordinate interval of the text area, it is determined that the text area contains the ordinate, If it is determined that a certain abscissa is located in the abscissa interval of the text area, then it is determined that the text area contains the abscissa.

As an example, taking any text area in each text area as an example, the abscissa interval of a certain text area is determined based on the maximum and minimum values of the abscissa coordinates among the four area vertex coordinates of the text area. The vertical coordinate interval of a text area is determined based on the maximum and minimum values of the vertical coordinate among the four regional vertex coordinates of the text area.

In this way, it is possible to determine the first area number of the text area that each ordinate line (the ordinates of each coordinate point in the ordinate line is the same) passes through, and the number of first areas of each abscissa line (each coordinate point in the abscissa line The number of the second area of the text area that the abscissas are the same) passes through.

S1014: Determine the coordinates of each table row of the target table based on the maximum ordinate, the minimum ordinate, and the number of first areas.

Specifically, according to each ordinate and its corresponding first area number, the trough ordinate that meets the trough ordinate condition is determined, and each table row coordinate is obtained based on the maximum ordinate, the minimum ordinate, and the trough ordinate.

Among them, the condition of the trough ordinate is: the number of the first areas in the trough ordinate is not higher than the number of the first areas in the adjacent ordinate of the trough ordinate, and the adjacent ordinate of the trough ordinate is the previous ordinate of the trough ordinate. and the latter ordinate.

In one implementation, obtaining the coordinates of each table row based on the maximum ordinate, the minimum ordinate, and the trough ordinate includes: using the maximum ordinate and the minimum ordinate as table row coordinates; and generating based on each trough ordinate. The trough ordinate interval (each ordinate within the trough ordinate interval is the trough ordinate), screen out the trough ordinate interval that does not include the maximum ordinate and the trough ordinate interval that does not include the minimum ordinate; in the filtered trough In the ordinate interval, if it is determined that the trough ordinate interval contains only one trough ordinate, then the trough ordinate interval will be used as the table row coordinate. If it is determined that the trough ordinate interval contains multiple trough ordinates, then the trough ordinate interval will be used as the table row coordinate. Select a trough vertical coordinate as the table row coordinate. Optionally, a trough ordinate can be randomly selected from the trough ordinate interval. In actual applications, the specific method of selection can be set according to the actual application scenario, and is not limited here.

S1015: Determine the coordinates of each table column based on the maximum abscissa, the minimum abscissa, and the number of second areas.

Specifically, according to each abscissa and its corresponding number of second areas, determine the trough abscissa that meets the conditions of the trough abscissa, and obtain the coordinates of each table column based on the maximum abscissa, the minimum abscissa, and the trough abscissa.

Among them, the condition of the wave trough abscissa is: the number of the second areas of the wave trough abscissa is not higher than the number of the second areas of the adjacent abscissa of the wave trough abscissa, and the adjacent abscissa of the wave trough abscissa is the previous abscissa of the wave trough abscissa. and the latter abscissa.

In one implementation, the coordinates of each table column are obtained based on the maximum abscissa, the minimum abscissa, and the trough abscissa, including:

Use the maximum abscissa and the minimum abscissa as table column coordinates; generate a trough abscissa interval based on each trough abscissa (each abscissa within the trough abscissa interval is a trough abscissa); filter out the maximum abscissa that does not include the trough abscissa. The trough abscissa interval of , and the trough abscissa interval that does not include the minimum abscissa; in the filtered trough abscissa interval, If it is determined that the trough abscissa interval contains only one trough abscissa, then the trough abscissa is used as the table column coordinate. If it is determined that the trough abscissa interval contains multiple trough abscissas, then one trough abscissa is selected from the trough abscissa interval. Coordinates, as table column coordinates. Optionally, you can select a trough abscissa coordinate from the trough abscissa coordinate interval as the table column coordinate. In actual applications, the specific method of selection can be set according to the actual application scenario, and is not limited here.

Step 102: Generate a blank table based on the row coordinates of each table and the coordinates of each table column.

Furthermore, you can also merge the target cells covered by the text area in the blank table. The target cell covered by the text area meets the following conditions: there is a coordinate point in the text area that is located within the target cell and does not coincide with the boundary of the target cell.

For example, if coordinate point b in text area A is located in cell C and does not coincide with the boundary of cell C, then cell C is determined to be the target cell covered by text area A.

Among them, when merging the target cells covered by the text area in the blank table, you can include:

S1021: Determine the cell position information of the cells in the blank table based on the row coordinates of each table and the coordinates of each table column.

In one implementation, the cells in the blank table are rectangular, and the cell position information of the cell includes four cell vertex coordinates of the cell. The cell vertex coordinates are the coordinates of the cell's vertex. The cell vertex coordinates include the cell vertex ordinate and the cell vertex abscissa.

S1022: Determine the target cell covered by the text area based on the area position information and the cell position information.

S1023: If it is determined that the text area covers multiple target cells, merge the target cells.

In one implementation, if there are multiple text areas, then for the target text area in each text area (the target text area is any text area in each text area), if it is determined that the target cell covered by the target text area is If there are multiple, the target cells covered by the target text area will be merged.

Step 103: According to the region position information, add the regional text content in the text region recognition result to the blank table to obtain the target table.

Specifically, perform the following steps for each cell in the blank table:

S1031: If it is determined that a cell contains only one text area based on the area position information, then the area text content in the text area contained in a cell is added to a cell.

Among them, a cell contains a text area, which means that all coordinate points in the text area are located in the cell, that is, the coverage area of the cell is not smaller than the text area.

In one implementation, determining that a cell contains only one text area based on the area location information may include: determining the center point coordinates of the text area based on the area location information. If based on the cell location information of a cell, determining only If the center point coordinate of a text area is located in the cell, it is determined that a cell contains only one text area. Among them, the center point coordinates are the coordinates of the center point of the text area. The coordinates of the center point include the abscissa coordinate of the center point and the ordinate coordinate of the center point. This is because in step 102, if the text area covers multiple cells, the multiple cells covered by the text area have been merged. The text area can only be located in one cell. Therefore, only the center point coordinates of the text area are used. , you can determine the cell where the text area is located.

In one implementation, adding the regional text content in the text area contained in a cell to a cell may include: setting the attribute value of the text attribute of a cell to the text area contained in the cell. The text content of the area within.

S1032: If it is determined that a cell contains at least two text areas according to the area position information, then the area text content in each text area contained in a cell is sorted according to the area position information, and the sorted areas are Field text content is added to a cell.

In one implementation, determining that a cell contains at least two text areas based on area location information may include: if it is determined that the number of text areas is multiple, determining each text area based on the area location information of each text area. The coordinates of the center point of the area. If, according to the cell position information of a cell, it is determined that the center point coordinates of at least two text areas are located in the cell, it is determined that a cell contains at least two text areas.

In one implementation, sorting the regional text content in each text area contained in a cell may include: sorting the regions in each text area contained in a cell in ascending order of the ordinate of the center point. Sort the text content; sort the regional text content in each text area with the same central point ordinate in ascending order of the center point's abscissa.

In one implementation, adding the sorted regional text content to a cell may include: setting the attribute value of a text attribute of a cell to the sorted regional text content.

This is because if there are multiple areas of text content in a cell, the content in the cell will be recognized as multiple areas of text through OCR technology recognition. For example, a line break will be recognized as two areas of text content. Therefore, it is necessary to sort the text content of multiple ranges in the same cell.

In actual applications, the text content in each area can be sorted according to the actual application scenario, and there is no restriction here.

It should be noted that when the cell is empty, since the cell does not contain a text area, there is no need to perform other processing on the empty cell.

In this way, the target table corresponding to the image to be processed can be generated.

In the embodiment of this application, text recognition technology is used for text recognition to obtain the position and content of each text area in each image to be processed, which reduces the amount of development. Furthermore, the framed table in the image to be processed can be reconstructed, and The frameless table in the image to be processed can be reconstructed, which improves the accuracy of table reconstruction, and it can accurately identify merged cells and the situation where the same cell contains text content in multiple areas, further improving the accuracy of table reconstruction.

A specific application scenario is used below to illustrate the above embodiment. Refer to Figure 2, which is an example of a user attribute table image. Figure 2 shows a user attribute table image containing multiple user attribute information. The user attribute table image is an image to be processed that requires table reconstruction. Refer to Figure 3, which is a specific flow chart of a method for reconstructing a user attribute table. The method shown in Figure 3 is used to reconstruct the user attribute table in the user attribute table image shown in Figure 2. The specific implementation process of this method as follows:

Step 300: Perform text recognition on the user attribute table image, and obtain the text area recognition result of the user attribute table image.

Specifically, OCR technology is used to perform text detection and text recognition on the user attribute table image shown in Figure 2, and the regional text content and regional location information of 34 text areas are obtained. The area position information includes the vertex coordinates of each area of the text area, that is, the vertex coordinates of the first area, the vertex coordinates of the second area, the vertex coordinates of the third area, and the vertex coordinates of the fourth area.

In one implementation, the output format of the identified regional text content and the regional location information of each regional text content is {'content':'regional text content','location':[first region vertex coordinates, second Area vertex coordinates, third area vertex coordinates, fourth area vertex coordinates]}. The text area recognition results of the user attribute table image in Figure 2 are:

{'content':'Salary','location':[245,40,245,21,288,22,287,41]};

{'content':'WorkAge','location':[438,40,439,22,499,23,499,40]};

{'content':'Name','location':[144,39,144,22,185,23,185,40]};

{'content':'Number','location':[37,39,37,23,90,23,90,39]};

{'content':'Bonus','location':[347,39,347,23,389,23,389,39]};

{'content':'1000','location':[249,84,249,66,284,66,284,84]};

{'content':'LiLei','location':[149,83,149,66,182,66,182,83]};

{'content':'1','location':[56,84,56,66,71,66,71,84]};

{'content':'10','location':[358,83,358,67,378,67,378,83]};

{'content':'10','location':[459,83,459,67,479,67,479,83]};

{'content':'Han','location':[150,118,150,102,180,102,180,118]};

{'content':'20','location':[459,127,459,110,479,110,479,127]};

{'content':'2','location':[56,127,56,110,71,110,71,127]};

{'content':'3000','location':[249,127,249,111,284,111,284,127]};

{'content':'90','location':[358,127,358,111,378,111,378,127]};

{'content':'Meimei','location':[141,135,141,119,190,119,190,135]};

{'content':'Weiyin','location':[142,163,142,146,188,146,188,163]};

{'content':'5000','location':[249,171,249,154,284,154,284,171]};

{'content':'888','location':[354,171,354,154,381,154,381,171]};

{'content':'30','location':[459,171,459,154,479,154,479,171]};

{'content':'3','location':[56,171,56,154,71,154,71,171]};

{'content':'Wang','location':[143,179,143,160,187,162,186,181]};

{'content':'Fangzheng','location':[129,207,129,189,200,190,200,207]};

{'content':'8000','location':[249,215,249,198,284,198,284,215]};

{'content':'40','location':[458,215,458,198,480,198,480,215]};

{'content':'4','location':[56,216,56,198,71,198,71,216]};

{'content':'303','location':[354,215,354,199,381,199,381,215]};

{'content':'Dashi','location':[145,224,145,206,184,205,184,223]};

{'content':'Chongxu','location':[135,251,136,234,195,235,194,252]};

{'content':'10000','location':[246,259,246,242,287,242,287,259]};

{'content':'400','location':[354,258,354,242,382,242,382,258]};

{'content':'50','location':[459,259,459,242,479,242,479,259]};

{'content':'5','location':[56,259,56,242,71,242,71,259]};

{'content':'Daozhang','location':[132,267,133,249,198,250,197,268]}].

Step 301: Determine the maximum ordinate and the minimum ordinate among the ordinates of the vertices of each region in the text area recognition result.

Specifically, through the vertical coordinates of the vertices of each text area in Figure 2, the maximum vertical coordinate table_top=268 and the minimum vertical coordinate table_bottom=21 are determined.

Step 302: Determine the maximum abscissa and the minimum abscissa of the abscissas of the vertices of each region in the text area recognition result.

Specifically, through the abscissa coordinates of the vertices of each text area in Figure 2, the maximum abscissa table_right=499 and the minimum abscissa table_left=37 are determined.

Step 303: Determine the number of first regions for each ordinate and the number of second regions for each abscissa according to the region position information in the text region recognition result.

Specifically, for the target ordinate in [table_bottom, table_top] (ie [21, 268]) (the target ordinate is any ordinate in [table_bottom, table_top]), determine the target ordinate line (target ordinate line Everyone on the table sits down The ordinate of the punctuation point is the number of text areas passed through by the target ordinate), and the first area number of the target ordinate is obtained. For the target abscissa in [table_left, table_right] (i.e. [37, 499]) (the target abscissa is any abscissa in [table_left, table_right]), determine the target abscissa line (each point on the target abscissa line The abscissas of the coordinate points are the number of text areas passed through by the target abscissa line), and the second area number of the target abscissa line is obtained.

Step 304: Determine the coordinates of each table row of the target table based on the maximum ordinate, the minimum ordinate, and the number of first areas.

Refer to Figure 4, which is an example of the first curve. In one implementation, 21 and 268 are determined as table row coordinates, and based on the number of first areas in each ordinate, the first curve shown in Figure 4 is generated, and through the first curve in Figure 4, the The coordinates of multiple table rows are [67, 119, 172, 223, 259].

It should be noted that the points on the first curve shown in Figure 4 are continuous and are only used to illustrate the corresponding relationship between each ordinate and the number of the first regions. In practical applications, each ordinate may also be discontinuous (the ordinate is usually obtained by sampling), which is not limited here.

Step 305: Determine the coordinates of each table column based on the maximum abscissa, the minimum abscissa, and the number of second areas.

Refer to Figure 5, which is an example of the second curve. In one implementation, 37 and 499 are determined as the abscissa of the table, and based on the number of the second areas of each abscissa, the second curve shown in Figure 5 is generated, and through the second curve in Figure 5, the number of The abscissa coordinates of each table are [139, 325, 456, 621] in order.

It should be noted that the points on the second curve shown in Figure 5 are continuous and are only used to illustrate the corresponding relationship between each abscissa and the number of second regions. In practical applications, each abscissa may also be discontinuous (the abscissa is usually obtained by sampling), which is not limited here.

Step 306: Generate a blank table based on the row coordinates of each table and the coordinates of each table column.

Step 307: According to the area location information, add the area text content in the text area recognition result to the blank form to obtain the target form.

For example, in Figure 2, the coordinates of the second column are between troughs [139,325], and the position of the second row is between troughs [67,119], then based on the regional location information of "Han" and "Meimei", determine " Han" and "Meimei" are both located in the second column and row, and "Han" is located above "Meimei".

In this way, the user attribute table in the user attribute table image shown in Figure 2 can be reconstructed.

Another specific application scenario is used below to illustrate the above embodiment. Refer to Figure 6, which is an example of merging table images. The merged table image is an image to be processed that requires table reconstruction. Refer to Figure 7, which is a specific flow chart of a method for reconstructing a merged table. The method shown in Figure 7 is used to reconstruct the merged table in the merged table image shown in Figure 6. The specific implementation process of this method is as follows:

Step 700: Perform text recognition on the merged table image to obtain the text area recognition result of the user attribute table image.

Specifically, OCR technology is used to perform text detection and text recognition on the merged table image shown in Figure 6, and the regional text content and regional location information of 8 text areas are obtained. The area position information includes the vertex coordinates of each area of the text area, that is, the vertex coordinates of the first area, the vertex coordinates of the second area, the vertex coordinates of the third area, and the vertex coordinates of the fourth area.

In one implementation, the output format of the identified regional text content and the regional location information of each regional text content is {'content':'regional text content','location':[first region vertex coordinates, second Area vertex coordinates, third area vertex coordinates, fourth area vertex coordinates]}. The text area recognition results of the merged table image in Figure 6 are:

{'content':'500','location':[642,137,642,84,728,84,728,137]};

{'content':'1000','location':[481,136,480,94,583,92,584,133]};

{'content':'Lilei','location':[286,131,286,102,366,102,366,131]};

{'content':'500','location':[641,193,642,140,728,142,727,195]};

{'content':'2000','location':[477,193,477,142,586,141,586,192]};

{'content':'HanMeimel','location':[213,190,213,157,437,157,437,190]};

{'content':'3000','location':[555,250,553,202,661,198,663,246]};

{'content':'ChongXu','location':[246,247,245,217,413,216,413,246]}].

Step 701: Determine the maximum ordinate and the minimum ordinate among the ordinates of the vertices of each region in the text area recognition result.

Specifically, through the vertical coordinates of the vertices of each text area in Figure 6, the maximum vertical coordinate table_top=250 and the minimum vertical coordinate table_bottom=84 are determined.

Step 702: Determine the maximum abscissa and the minimum abscissa of the abscissas of the vertices of each region in the text area recognition result.

Specifically, through the abscissa coordinates of the vertices of each text area in Figure 6, the maximum abscissa table_right=728 and the minimum abscissa table_left=213 are determined.

Step 703: Determine the number of first regions for each ordinate and the number of second regions for each abscissa according to the region position information in the text region recognition result.

Step 704: Determine the coordinates of each table row of the target table based on the maximum ordinate, the minimum ordinate, and the number of first areas.

Refer to Figure 8, which is an example of the first curve. FIG. 8 is only used to illustrate the corresponding relationship between each ordinate and the number of first regions. In one implementation, 84 and 250 are determined as table row coordinates, and based on the number of first areas in each ordinate, the first curve shown in Figure 8 is generated, and through the first curve in Figure 8, the The coordinates of multiple table rows are [137,195].

Step 705: Determine the coordinates of each table column based on the maximum abscissa, the minimum abscissa, and the number of second areas.

Refer to Figure 9, which is an example of the second curve. FIG. 9 is only used to illustrate the corresponding relationship between each abscissa and the number of second regions. In one implementation, 213 and 728 are determined as the abscissas of the table, and based on the number of the second areas of each abscissa, the second curve shown in Figure 9 is generated, and through the second curve in Figure 9, the number of The abscissas of the tables are [437,586] in sequence.

Step 706: Generate a blank table based on the row coordinates of each table and the coordinates of each table column.

Step 707: According to the region position information, add the regional text content in the text region recognition result to the blank table to obtain the target table.

Based on the same inventive concept, the embodiment of the present application also provides a device for table reconstruction. Since the principle of solving the problem of the above device and equipment is similar to a method for table reconstruction, the implementation of the above device can be referred to the implementation of the method. The repetitive parts will not be repeated.

As shown in Figure 10, it is a schematic structural diagram of a table reconstruction device provided by an embodiment of the present application, including:

The recognition unit 1001 is used to perform text recognition on the image to be processed, and obtain the text area recognition result of the image to be processed. The text area recognition result includes the regional text content and regional location information of the text area;

The determination unit 1002 is used to determine the table row coordinates and the table column coordinates of the target table according to the regional location information;

The generation unit 1003 is used to generate a blank table based on the row coordinates of each table and the coordinates of each table column;

The obtaining unit 1004 is used to add the regional text content to the blank table according to the region location information to obtain the target table.

In one embodiment, the area location information includes the area vertex coordinates of the text area, and the identification unit 1001 is used to: perform text detection on the image to be processed, and obtain multiple area vertex coordinates of the text area, where the area vertex coordinates are the coordinates of the vertices of the text area. ; Perform text recognition on the text area and obtain the text content of the area.

In one implementation, the regional vertex coordinates include the regional vertex abscissa and the regional vertex ordinate. The determining unit 1002 is used to: determine the maximum ordinate and the minimum ordinate in the ordinate of each regional vertex; determine the maximum ordinate in the abscissa of each regional vertex. The maximum abscissa and the minimum abscissa; according to the area position information, determine the number of the first area for each ordinate and the number of the second area for each abscissa. The number of the first area is the number of text areas containing a certain ordinate. The number of the second area is the number of text areas containing a certain abscissa; determine the coordinates of each table row based on the maximum ordinate, the minimum ordinate, and the number of the first area; determine the coordinates of each table row based on the maximum abscissa, the minimum abscissa, and the second area Quantity, determine the coordinates of each table column.

In one implementation, the determining unit 1002 is configured to determine the trough ordinate based on each ordinate and its corresponding number of first areas. The number of first areas in the trough ordinate is not higher than the number of adjacent ordinates in the trough ordinate. The number of the first area, the adjacent ordinates of the trough ordinate are the previous ordinate and the next ordinate of the trough ordinate; according to the maximum ordinate, the minimum ordinate, and the trough ordinate, the coordinates of each table row are obtained.

In one implementation, the determining unit 1002 is configured to: determine the trough abscissa according to each abscissa and its corresponding number of second areas. The number of the second areas of the trough abscissa is not higher than the number of adjacent abscissas of the trough abscissa. The second area quantity, the adjacent abscissa of the trough abscissa is the previous abscissa and the next abscissa of the trough; according to the maximum abscissa, the minimum abscissa, and the trough abscissa, the coordinates of each table column are obtained.

In one implementation, the generation unit 1003 is also used to: determine the cell position information of the cells in the blank table according to each table row coordinate and each table column coordinate; determine the text area according to the area position information and the cell position information. The covered target cells; where there are coordinate points in the text area that are within the target cells and do not coincide with the boundaries of the target cells; if it is determined that there are multiple target cells covered by the text area, the target cells will be merged.

In one implementation, the obtaining unit 1004 is used to: perform the following steps for each cell in the blank table: if it is determined that a cell contains only one text area according to the area position information, then the The regional text content in the text area is added to a cell; if it is determined that a cell contains at least two text areas according to the area position information, then the areas in each text area contained in a cell are added according to the area position information. Sort the text content and add the sorted range text content to a cell.

In one implementation, the obtaining unit 1004 is used to: determine the center point coordinates of the text area based on the area position information, and the center point coordinates are the coordinates of the center point of the text area; if based on the cell position information of a cell, determine only If the center point coordinate of a text area is located in the cell, it is determined that a cell contains only one text area.

In one implementation, the obtaining unit 1004 is used to: set the attribute value of the text attribute of a cell to the regional text content in the text area contained in the cell.

In one implementation, the obtaining unit 1004 is configured to: if it is determined that the number of text areas is multiple, determine the center point coordinates of each text area according to the area position information of each text area, and the center point coordinates are The coordinates of the center point; if based on the cell position information of a cell, it is determined that the center point coordinates of at least two text areas are located in the cell, then it is determined that a cell contains at least two text areas.

In one implementation, the center point coordinates include the center point abscissa and the center point ordinate. The obtaining unit 1004 is used to: according to the descending order of the center point ordinate, the areas within each text area contained in a cell are Sort the text content; sort the regional text content in each text area with the same central point ordinate in ascending order of the center point's abscissa.

In one implementation, the obtaining unit 1004 is used to set the attribute value of the text attribute of a cell to the sorted regional text content.

Figure 11 shows a schematic structural diagram of an electronic device 1100. Referring to FIG. 11 , the electronic device 1100 includes a processor 1110 and a memory 1120 . Optionally, it may also include a power supply 1130 , a display unit 1140 , and an input unit 1150 .

The processor 1110 is the control center of the electronic device 1100. It uses various interfaces and lines to connect various components, and executes various functions of the electronic device 1100 by running or executing software programs and/or data stored in the memory 1120, thereby controlling the electronic device 1100. Device 1100 performs overall monitoring.

In the embodiment of the present application, the processor 1110 executes each step in the above embodiment when calling the computer program stored in the memory 1120.

Optionally, the processor 1110 may include one or more processing units; preferably, the processor 1110 may integrate an application processor and a modem processor, where the application processor mainly processes operating systems, user interfaces, applications, etc., The modem processor primarily handles wireless communications. It can be understood that the above modem processor may not be integrated into the processor 1110. In some embodiments, the processor and memory can be implemented on a single chip, and in some embodiments, they can also be implemented on separate chips.

The memory 1120 may mainly include a program storage area and a data storage area, where the program storage area may store operating systems, various applications, etc.; the storage data area may store data created according to the use of the electronic device 1100 , etc. In addition, the memory 1120 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 volatile solid-state storage device.

The electronic device 1100 also includes a power supply 1130 (such as a battery) that supplies power to various components. The power supply can be logically connected to the processor 1110 through a power management system, thereby managing functions such as charging, discharging, and power consumption through the power management system.

The display unit 1140 may be used to display information input by the user or information provided to the user, as well as various menus of the electronic device 1100, etc. In the embodiment of the present invention, it is mainly used to display the display interface of each application in the electronic device 1100 and the display interface. text, pictures and other objects. The display unit 1140 may include a display panel 1141. The display panel 1141 can be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), etc.

The input unit 1150 may be used to receive information such as numbers or characters input by the user. The input unit 1150 may include a touch panel 1151 and other input devices 1152. Among them, the touch panel 1151, also called a touch screen, can collect the user's touch operations on or near it (for example, the user uses any suitable object or accessory such as a finger, a touch pen, etc. on or near the touch panel 1151. nearby operations).

Specifically, the touch panel 1151 can detect the user's touch operation and detect the signals brought by the touch operation, convert these signals into contact point coordinates, send them to the processor 1110, and receive and execute the commands sent by the processor 1110. . In addition, the touch panel 1151 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic wave. Other input devices 1152 may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control keys, power on/off keys, etc.), trackball, mouse, joystick, etc.

Of course, the touch panel 1151 can cover the display panel 1141. When the touch panel 1151 detects a touch operation on or near it, it is sent to the processor 1110 to determine the type of the touch event, and then the processor 1110 determines the type of the touch event according to the type of the touch event. Corresponding visual output is provided on display panel 1141. Although in Figure 11, the touch panel 1151 and the display panel 1141 are used as two independent components to implement the input and output functions of the electronic device 1100, in some implementations For example, the touch panel 1151 and the display panel 1141 can be integrated to implement the input and output functions of the electronic device 1100 .

The electronic device 1100 may also include one or more sensors, such as a pressure sensor, a gravity acceleration sensor, a proximity light sensor, and the like. Of course, according to the needs of specific applications, the above-mentioned electronic device 1100 may also include other components such as cameras. Since these components are not the key components used in the embodiments of this application, they are not shown in Figure 11 and will not be described in detail. .

Those skilled in the art can understand that FIG. 11 is only an example of an electronic device and does not constitute a limitation on the electronic device. It may include more or fewer components than shown in the figure, or some components may be combined, or different components may be used.

In the embodiment of the present application, a computer-readable storage medium has a computer program stored thereon. When the computer program is executed by the processor, the communication device can perform each step in the above embodiment.

For the convenience of description, each of the above parts is divided into modules (or units) according to their functions and described separately. Of course, when implementing this application, the functions of each module (or unit) can be implemented in the same or multiple software or hardware.

Those skilled in the art will understand that embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment that combines software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce a use A device for realizing the functions specified in one process or multiple processes of the flowchart and/or one block or multiple blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory that causes a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction means, the instructions The device implements the functions specified in a process or processes of the flowchart and/or a block or blocks of the block diagram.

These computer program instructions may also be loaded onto a computer or other programmable data processing device, causing a series of operating steps to be performed on the computer or other programmable device to produce computer-implemented processing, thereby executing on the computer or other programmable device. Instructions provide steps for implementing the functions specified in a process or processes of a flowchart diagram and/or a block or blocks of a block diagram.

Claims

A method for table reconstruction, which is characterized by including:

Perform text recognition on the image to be processed, and obtain the text area recognition result of the image to be processed, where the text area recognition result includes the regional text content and regional location information of the text area;

Determine each table row coordinate and each table column coordinate of the target table according to the regional location information;

Generate a blank table based on the row coordinates of each table and the coordinates of each table column;

According to the area location information, the area text content is added to the blank form to obtain the target form.
The method of claim 1, wherein the area location information includes the area vertex coordinates of the text area, and the text recognition of the image to be processed is performed to obtain the text area recognition result of the image to be processed, including :

Perform text detection on the image to be processed to obtain multiple area vertex coordinates of the text area, where the area vertex coordinates are the coordinates of the vertices of the text area;

Perform text recognition on the text area to obtain the text content of the area.
The method of claim 2, wherein the regional vertex coordinates include the regional vertex abscissa and the regional vertex ordinate, and the coordinates of each table row and each table column of the target table are determined based on the regional location information. Coordinates, including:

Determine the maximum vertical coordinate and the minimum vertical coordinate among the vertical coordinates of the vertices of each region;

Determine the maximum abscissa and minimum abscissa of the abscissa of each area vertex;

According to the area position information, the first area number of each ordinate and the second area number of each abscissa are determined, the first area number is the number of text areas containing a certain ordinate, and the second area The number is the number of text areas containing a certain abscissa;

Determine the coordinates of each table row according to the maximum ordinate, the minimum ordinate, and the number of first areas;

Each table column coordinate is determined according to the maximum abscissa, the minimum abscissa, and the second area number.
The method of claim 3, wherein determining the coordinates of each table row based on the maximum ordinate, the minimum ordinate, and the number of first areas includes:

Determine the trough ordinate according to each ordinate and its corresponding number of first areas. The number of first areas in the trough ordinate is not higher than the number of first areas in adjacent ordinates of the trough ordinate. The trough ordinate is The adjacent ordinates of the ordinate are the previous ordinate and the next ordinate of the trough ordinate;

According to the maximum ordinate, the minimum ordinate, and the trough ordinate, the coordinates of each table row are obtained.
The method of claim 3, wherein determining the coordinates of each table column based on the maximum abscissa, the minimum abscissa, and the number of second areas includes:

The wave trough abscissa is determined according to each abscissa and its corresponding number of second areas. The number of the second areas of the wave trough abscissa is not higher than the number of second areas of the adjacent abscissa of the wave trough abscissa. The wave trough abscissa is The adjacent abscissas of the abscissa are the previous abscissa and the next abscissa of the wave trough abscissa;

According to the maximum abscissa, the minimum abscissa, and the trough abscissa, the coordinates of each table column are obtained.
The method according to any one of claims 1 to 5, characterized in that, according to the row coordinates of each table and After generating the coordinates of each table column and generating a blank table, the method also includes:

Determine the cell position information of the cells in the blank table according to the coordinates of each table row and the coordinates of each table column;

According to the area position information and the cell position information, the target cell covered by the text area is determined; wherein, there is a cell in the text area that is located within the target cell and is not related to the target cell. Coordinate points where the boundaries coincide;

If it is determined that the text area covers multiple target cells, the target cells are merged.
The method according to any one of claims 1 to 5, wherein adding the regional text content to the blank form according to the regional location information to obtain the target form includes:

For each cell in the blank table, perform the following steps:

If it is determined that a cell contains only one text area based on the area position information, then add the area text content in the text area contained in the one cell to the one cell;

If it is determined that one cell contains at least two text areas according to the area position information, then the area text content in each text area contained in the one cell is sorted according to the area position information, and the sorted The range of text content is added to the one cell.
The method of claim 7, wherein determining that a cell contains only one text area based on the area location information includes:

Determine the center point coordinates of the text area according to the area position information, and the center point coordinates are the coordinates of the center point of the text area;

If, according to the cell position information of the one cell, it is determined that the center point coordinate of only one text area is located in the cell, it is determined that the one cell contains only one text area.
The method of claim 7, wherein adding the regional text content in the text area contained in the one cell to the one cell includes:

Set the attribute value of the text attribute of the one cell to the regional text content in the text area contained in the one cell.
The method of claim 7, wherein determining that one cell contains at least two text areas based on the area position information includes:

If it is determined that the number of text areas is multiple, then determine the center point coordinates of each text area according to the area position information of each text area, and the center point coordinates are the coordinates of the center point of the text area;

If it is determined that the center point coordinates of at least two text areas are located in the cell according to the cell position information of the one cell, then it is determined that the one cell contains at least two text areas.
The method of claim 10, wherein the coordinates of the center point include the abscissa coordinate of the center point and the ordinate of the center point, and the regional text content in each text area contained in the one cell is sorted, include:

Sort the regional text content in each text area contained in the one cell in ascending order of the ordinate of the center point;

According to the ascending order of the abscissa coordinate of the center point, the regional text content in each text area with the same ordinate of the center point is sorted again.
The method of claim 7, wherein adding the sorted regional text content to one of the cells includes:

Set the attribute value of the text attribute of the one cell to the sorted area text content.
A device for table reconstruction, which is characterized by including:

A recognition unit, configured to perform text recognition on the image to be processed, and obtain the text area recognition result of the image to be processed, where the text area recognition result includes the regional text content and regional location information of the text area;

A determination unit configured to determine the coordinates of each table row and the coordinates of each table column of the target table based on the regional location information;

The generation unit is used to generate a blank table based on the row coordinates of each table and the coordinates of each table column;

An obtaining unit is configured to add the regional text content to the blank form according to the regional location information to obtain the target form.
An electronic device, characterized in that it includes a processor and a memory, and the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the operation is as described in any of claims 1-12. 1. The method described.
A computer-readable storage medium, characterized in that the storage medium stores a computer program, and the computer program can be executed by a processor to complete the method of any one of claims 1-12.
A computer program product, characterized in that when the computer program product is run on a computer, it causes the computer to execute the method according to any one of claims 1-12.