WO2020140698A1 - Procédé et appareil d'acquisition de données de tableau, et serveur associé - Google Patents

Procédé et appareil d'acquisition de données de tableau, et serveur associé Download PDF

Info

Publication number
WO2020140698A1
WO2020140698A1 PCT/CN2019/124101 CN2019124101W WO2020140698A1 WO 2020140698 A1 WO2020140698 A1 WO 2020140698A1 CN 2019124101 W CN2019124101 W CN 2019124101W WO 2020140698 A1 WO2020140698 A1 WO 2020140698A1
Authority
WO
WIPO (PCT)
Prior art keywords
morphological
rectangular
coordinates
image data
image
Prior art date
Application number
PCT/CN2019/124101
Other languages
English (en)
Chinese (zh)
Inventor
张林江
Original Assignee
阿里巴巴集团控股有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 阿里巴巴集团控股有限公司 filed Critical 阿里巴巴集团控股有限公司
Publication of WO2020140698A1 publication Critical patent/WO2020140698A1/fr

Links

Images

Classifications

    • 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
    • G06V30/40—Document-oriented image-based pattern recognition
    • G06V30/41—Analysis of document content
    • G06V30/413—Classification of content, e.g. text, photographs or tables

Definitions

  • This specification belongs to the field of Internet technology, and particularly relates to a method, device and server for acquiring table data.
  • such a type of text data for example, contract documents
  • the data acquisition method is usually to directly perform optical character recognition on image data such as scanned pictures containing text data to recognize and extract text information in the image data to obtain electronic file data of the corresponding text.
  • the table data in the text data is different from the above-mentioned individual text characters.
  • it also has certain graphic features, for example, including dividers and dividers.
  • the structure of the table data is more complicated and it is more difficult to recognize.
  • the existing data acquisition method is used to identify the table data in the image data, errors are likely to occur.
  • the dividers in the table are mistakenly recognized as numbers.
  • the text characters in the N rows and M columns of the table are misaligned and so on. Therefore, there is an urgent need for a method that can accurately identify and completely recover the table data in the image data.
  • the purpose of this specification is to provide a method, device and server for acquiring form data to solve the technical problem of large error and inaccuracy in the existing method of extracting form data, so as to achieve efficient and accurate identification and complete restoration to obtain images
  • the content of the table in the data is to provide a method, device and server for acquiring form data to solve the technical problem of large error and inaccuracy in the existing method of extracting form data, so as to achieve efficient and accurate identification and complete restoration to obtain images
  • the content of the table in the data is to provide a method, device and server for acquiring form data to solve the technical problem of large error and inaccuracy in the existing method of extracting form data, so as to achieve efficient and accurate identification and complete restoration to obtain images
  • the content of the table in the data is to provide a method, device and server for acquiring form data to solve the technical problem of large error and inaccuracy in the existing method of extracting form data, so as to achieve efficient and accurate identification and complete restoration to obtain images
  • the content of the table in the data is
  • a method for acquiring form data comprising: acquiring image data of text to be processed; extracting a combined image from the image data, wherein the combined image is a graph including vertical morphological lines and horizontal morphological lines ; Divide the combined image into multiple rectangular units, wherein the multiple rectangular units each carry position coordinates; perform optical character recognition on the multiple rectangular units, and determine whether the multiple rectangular units contain Text information; according to the position coordinates of the rectangular unit, the rectangular unit containing the text information is combined to obtain the table data.
  • An apparatus for acquiring form data includes: an acquiring module for acquiring image data of text to be processed; an extracting module for extracting a combined image from the image data, wherein the combined image is a form that includes a cross Learning vertical and morphological horizontal lines; a segmentation module for dividing the combined graph into a plurality of rectangular units, wherein the plurality of rectangular units respectively carry position coordinates; an identification module is used for the A plurality of rectangular units respectively perform optical character recognition to determine the text information contained in each of the plurality of rectangular units; a combination module is used to combine the rectangular units containing text information according to the position coordinates of the rectangular units to obtain table data.
  • a server includes a processor and a memory for storing processor-executable instructions.
  • the processor executes the instructions, the image data of the text to be processed is obtained; the combined image is extracted from the image data, wherein
  • the combination graph is a graph including vertical morphological lines and horizontal morphological lines; the combination graph is divided into a plurality of rectangular units, wherein the plurality of rectangular units respectively carry position coordinates; Each rectangular unit performs optical character recognition to determine the text information contained in the multiple rectangular units; according to the position coordinates of the rectangular units, the rectangular units containing the text information are combined to obtain table data.
  • the method, device and server for acquiring table data provided in this specification, because the combined image is obtained by first obtaining and extracting from the graphic features of the morphological vertical line and the morphological horizontal line in the image data; then the combined image is divided into multiple Each rectangular unit is divided into optical characters to obtain the text information contained in each rectangular unit, and then the rectangular units containing the text information are combined according to the position coordinates of the rectangular unit to restore the complete table data. Therefore, the technical problem of large error and inaccuracy in extracting table data existing in the existing method is solved, and the content of the table in the image data can be identified efficiently and accurately, and the table content in the image data is completely restored.
  • FIG. 1 is a schematic diagram of an embodiment of a method for acquiring table data provided by an embodiment of this specification in a scenario example;
  • FIG. 2 is a schematic diagram of an embodiment of a method for acquiring table data provided by an embodiment of this specification in a scenario example;
  • FIG. 3 is a schematic diagram of an embodiment of a method for acquiring table data provided by an embodiment of this specification in a scenario example;
  • FIG. 4 is a schematic diagram of an embodiment of a method for acquiring table data provided by an embodiment of this specification in a scenario example;
  • FIG. 5 is a schematic diagram of an embodiment of a flow of a method for acquiring table data provided by an embodiment of this specification
  • FIG. 6 is a schematic diagram of an embodiment of a structure of a server provided by an embodiment of this specification.
  • FIG. 7 is a schematic diagram of an embodiment of a structure of an apparatus for acquiring table data provided by an embodiment of this specification.
  • a graphic structure such as a separator bar in the table data is mistakenly recognized as a text character, or a misalignment occurs in the recognition and extraction of text information at different positions in the table data. That is, when the table data in the image data is processed by the existing acquisition method, the effect is often not ideal, and there is a technical problem of large error and inaccuracy in extracting the table data.
  • this specification specifically analyzes the different characteristics of the two different attribute objects of text characters and graphic structures that the table data has at the same time.
  • image structure features such as lines to find a combined image that may form table data from the image data; then divide the combined image into multiple rectangular units, and perform optical character recognition on each rectangular unit separately to obtain the text information of the rectangular unit;
  • the rectangular unit containing the text information is combined to restore and reconstruct the complete table data of the image, thereby solving the technical problem of large error and inaccuracy in the existing method of extracting table data. It can efficiently and accurately identify and completely restore the table content in the image data.
  • the embodiments of the present specification provide an acquisition method of a table data method.
  • the acquisition method of the table data may be specifically applied to an image data processing system including multiple servers.
  • the legal contract processing system for scanning pictures For example, the legal contract processing system for scanning pictures.
  • the above system may specifically include a server for identifying and acquiring form data in text data from image data.
  • the server can extract the combined image from the acquired image data of the text to be processed by detecting the morphological vertical lines and morphological horizontal lines in the image data; then divide the combined image according to the coordinates Into multiple rectangular units, and perform optical character recognition on each of the multiple rectangular units to identify and determine the text information contained in each rectangular unit; then, according to the coordinates of the rectangular unit, combine and splice the above contained text The rectangular unit of information to get the complete table data.
  • the server can be understood as a service server that is applied to the business system side and can implement functions such as data transmission and data processing.
  • the server may be an electronic device with data calculation, storage, and network interaction functions; or a software program that runs on the electronic device and provides support for data processing, storage, and network interaction.
  • the number of the servers is not specifically limited.
  • the server may specifically be one server, or several servers, or a server cluster formed by several servers.
  • the form data acquisition method provided in the embodiment of the present specification can be used to process the image data containing the contract received by the legal platform to extract the form data in the contract.
  • the legal platform can distribute the image data containing the contract to be entered by the user to the server on the platform that is used to obtain the form data.
  • the above-mentioned legal platform can be specifically used to identify and extract text information in user-uploaded image data containing contracts (such as scanned pictures or photos containing contracts) to convert contract contents into electronic file data.
  • contracts such as scanned pictures or photos containing contracts
  • the above-mentioned legal platform can be specifically used to identify and extract text information in user-uploaded image data containing contracts (such as scanned pictures or photos containing contracts) to convert contract contents into electronic file data.
  • contracts such as scanned pictures or photos containing contracts
  • the server may refer to FIG. 2 to pre-process the image to reduce error interference and improve the accuracy of subsequent identification and acquisition of table data.
  • the server may be specifically configured with OpenCV (that is, Open source Computer Vision Library, source code computer vision library).
  • OpenCV Open source Computer Vision Library, source code computer vision library
  • the above OpenCV can be understood as an API function library about the source code of computer vision.
  • the function code contained in the library has been optimized, and the efficiency of calling and calculating is relatively high.
  • the server can call the corresponding function code through the above OpenCV to efficiently perform data processing on the image data.
  • the server can first convert the image data to obtain the corresponding grayscale image, and then perform Gaussian smoothing on the grayscale image to filter out the more obvious noise information in the grayscale image and improve the accuracy of the image data, thereby completing Preprocessing of image data.
  • the image data is converted into a grayscale image only as an example for schematic description.
  • the image data may also be converted into a binary map first, and then subsequent table data acquisition may be performed based on the binary map. This specification is not limited.
  • the server can first scan and retrieve the graphic structural features (such as structural elements, etc.) in the image data based on morphology, so as to find the difference from the image data first.
  • Text characters, with certain graphic features, may form a table of graphics: combination chart.
  • a specific frame image in the image data is taken as an example, for example, the fifth page image in the image data including the contract is taken as an example.
  • the server can scan and search the morphological vertical line and the morphological horizontal line in the frame image.
  • the above-mentioned morphological vertical lines and morphological horizontal lines can be understood as a structural element related to graphics that is different from text characters. You can refer to Figure 3.
  • the morphological vertical line may specifically be an image unit or a structural element that contains a straight line segment along the vertical direction in the image.
  • the above-mentioned morphological horizontal line may specifically be an image unit or a structural element that contains a straight line segment along the horizontal direction in the image.
  • the server can search for the structural elements in the image by calling the getStructuringElement function, and find all the morphological vertical lines and morphological horizontal lines from it.
  • the above-listed method of obtaining the morphological vertical line and the morphological horizontal line from the image by calling the getStructuringElement function is only a schematic illustration.
  • the morphological vertical line and the morphological horizontal line in the image may also be obtained in other suitable ways. This specification is not limited.
  • each morphological horizontal line mostly intersects one or more of the morphological vertical lines. Therefore, after obtaining the morphological vertical line and the morphological horizontal line in the frame image, the server can further search for the graph containing the structure of the intersecting morphological vertical line and the morphological horizontal line as possible form data Combining graphs to avoid subsequent processing of graphic structures that obviously do not have the graphic features of table data and improve processing efficiency.
  • the morphological horizontal lines and morphological vertical lines can be directly extracted on the original image, and the extracted morphology Horizontal lines and morphological vertical lines cover the extraction position.
  • the combination chart After obtaining the above-mentioned combination chart with more obvious data characteristics of the data table and possibly forming the table data, the combination chart can be further inspected, by checking whether the combination chart meets the preset table format requirements, to be more accurate To determine whether the combination chart is a data table.
  • the above-mentioned preset table format requirements can be specifically understood as a rule set for describing graphic features of data tables different from other graphic structures.
  • each grid graphic (or rectangular frame, see Figure 3) is designed to fill in specific characters, that is, each grid graphic in the data table
  • the minimum area should be able to accommodate at least the next complete character. Therefore, the following rules for graphic area characteristics may be set: the minimum area of the grid pattern in the data table should be greater than a preset area threshold. Also considering that based on people's usual typesetting habits, the table data will be set to the center position when editing the table data. Therefore, you can also set the following rules for graphic position features: the absolute value of the difference between the distance between the left border of the data table and the left border of the image and the distance between the right border of the data table and the right border of the image is less than the Set the distance threshold.
  • the following rules for the quantity characteristics of graphics may also be set: the number of grid graphics in the data table is greater than or equal to a preset quantity threshold (for example, 2), and so on.
  • the extracted combination map in order to determine whether the extracted combination map meets the preset table format requirements, in specific implementation, it can first retrieve the point where the horizontal and vertical morphological lines in the combination map are at the same image position as Intersection point, and then determine the position coordinates of each intersection point in the combined image in the frame image.
  • intersection point can be specifically understood as the pixel point at the position where the morphological vertical line and the morphological horizontal line intersect in the combined image in the frame image. See Figure 3 for details.
  • the server can search for and obtain the coordinates of the intersection point in the combined image in the image by calling the opencv bitwise_and function.
  • the opencv bitwise_and function listed above is only a schematic illustration.
  • the server may also obtain the coordinates of the intersection points in the combined graph in other suitable ways according to specific conditions. This specification is not limited.
  • the server may further search for the graphic structure elements of the above combination diagram, and find a graphic element having a rectangular (or square) structure (ie, a grid in the corresponding table) as a rectangular frame in the combination diagram.
  • a graphic element having a rectangular (or square) structure ie, a grid in the corresponding table
  • the server may search for and obtain the rectangular frame in the combination graph by calling the findContours function.
  • the findContours function is only a schematic illustration.
  • the server may also obtain the rectangular frame in the combination diagram in other suitable ways according to specific conditions. This specification is not limited.
  • the server may determine the endpoint coordinates at the four endpoints of each rectangular frame in the combination graph through position comparison based on the determined intersection coordinate and the rectangular frame in the combination graph. Furthermore, according to the coordinates of the endpoints of the rectangular frame in the combination diagram, it can be determined whether the combination diagram meets the preset table format requirements.
  • the server may calculate the length and width of the rectangular frame according to the coordinates of the endpoints of the rectangular frame, and then calculate the area of the rectangular frame based on the length and width. Then compare the area of the rectangular frame with the preset area threshold. If the area of each rectangular frame in the combination diagram is greater than the preset area threshold, it can be determined that the combination diagram meets the preset table format requirements.
  • the server can also compare the value of the abscissa of the end point coordinates of each rectangular frame in the combination diagram, find the end point with the smallest value of the abscissa as the endpoint on the left border of the combination diagram, and determine the abscissa of the endpoint as the left The abscissa of the border, and then calculate the distance between the left border of the combined image and the left border of the image based on the abscissa of the left border, and record it as d1.
  • the service finds the endpoint with the largest abscissa value as the endpoint on the right border of the combination chart by comparing the values of the abscissa of the endpoint, and determines the abscissa of the endpoint as the abscissa of the right border.
  • the abscissa of the side boundary calculates the distance between the right boundary of the combined drawing and the right boundary of the drawing, and is denoted as d2.
  • the server may calculate the absolute value of the difference between d1 and d2, and compare the absolute value of the above difference with a preset distance threshold. If the absolute value of the above-mentioned difference is less than or equal to the preset distance threshold, it can be determined that the entire combination picture is located at the center of the image, that is, the preset table format requirements are met.
  • the server may determine that the currently extracted combination diagram is indeed a data table in the image. Subsequent text information can be extracted from the combined image.
  • the server may first divide the above combined image into a plurality of rectangular units.
  • each rectangular unit corresponds to a rectangular frame in the combination diagram one by one; however, it is different from the single graphical structure element of the rectangular frame.
  • Each rectangular unit contains text characters or blank state information.
  • separate optical character recognition can be performed on each rectangular unit to accurately identify the text characters in the rectangular unit and determine the text information contained in each rectangular unit.
  • the server may first determine the contour line enclosing the rectangular frame as the dividing line according to the endpoint coordinates of the rectangular frame, and then may cut along the contour line to divide the rectangular unit corresponding to the rectangular frame from the combined diagram. For example, see Figure 4.
  • the coordinates of the four endpoints of a rectangular frame in the combination diagram are A (15, 60), B (15, 40), C (30, 40), and D (30, 60).
  • the server can start from the endpoint A, keep the abscissa 15 unchanged, and find the endpoint with a different ordinate, namely endpoint B, and then connect endpoint A to endpoint B according to a preset division rule.
  • the server starts from the endpoint B, keeps the ordinate 40 unchanged, and finds the endpoint with different abscissas, that is, the endpoint C, and then connects the endpoint B to the endpoint C according to the preset division rule.
  • the server starts from the endpoint C, keeps the abscissa 30 unchanged according to the preset division rule, and finds the endpoint with a different ordinate, namely the endpoint D, and then connects the endpoint C to the endpoint D.
  • the server starts from the endpoint D and keeps the ordinate 60 unchanged according to the preset division rule, and finds the endpoint with different abscissas, that is, endpoint A, and then connects the endpoint D to the endpoint A.
  • a closed connecting line can be obtained: A to B to C to D to A, which is the outline of the rectangular frame.
  • the server may use the outline as a dividing line, and divide the rectangular frame containing the text information in the combined image along the outline to obtain the corresponding rectangular unit.
  • each rectangular unit in the combined graph can be divided.
  • the above-mentioned manner of dividing the rectangular unit is just to better explain the embodiments of the present specification.
  • other suitable methods may also be used to divide a plurality of rectangular units from the combined diagram according to specific circumstances. This specification is not limited.
  • the server in the process of dividing the combined image, also generates position coordinates corresponding to the rectangular unit according to the coordinates of the end points of the rectangular frame.
  • the above position coordinates can be understood as a kind of parameter data used to indicate the position of the rectangular unit in the image of the combined image or describe the positional relationship between the rectangular unit in the image of the combined image and other adjacent rectangular units.
  • the server may calculate the coordinates of the center point of the rectangular frame as the position coordinates of the corresponding rectangular unit according to the endpoint coordinates of the four endpoints of the rectangular frame.
  • the server may also calculate the coordinates of the center points of each rectangular frame first, and then according to the preset arrangement order, for example, from the top to bottom and from left to right, according to the coordinates of the center points of each rectangular frame, determine The row number and column number of each rectangular unit are used as the position coordinates of the corresponding rectangular unit.
  • the rectangular frame A is located in the first row and second column of the combined diagram, that is, the corresponding row number is 1 and the column number is 2, so "1-2" can be used as The position coordinates of the rectangular unit corresponding to the rectangular frame A.
  • the above-listed methods for determining the position coordinates of the rectangular unit are only schematic illustrations. During specific implementation, according to the specific situation, other suitable methods may also be used to determine the position coordinates of the rectangular unit. This specification is not limited.
  • the server can perform optical character recognition (ie, OCR, Optical, Character, Recognition) on each of the multiple rectangular units to determine the text characters in each rectangular unit, and then Determine the text information contained in each rectangular unit. If no text characters are recognized in the rectangular unit, the text information contained in the rectangular unit is left blank. In this way, multiple rectangular units containing corresponding text information can be obtained.
  • optical character recognition ie, OCR, Optical, Character, Recognition
  • the server may combine and combine the rectangular units containing the text information obtained above according to the position coordinates of each rectangular unit.
  • the rectangular unit containing text information can be set at the position of the first row and the second column according to the position coordinates "1-2" of the rectangular unit.
  • a plurality of rectangular units containing text information are sequentially set to corresponding positions, so that a complete data table can be restored.
  • the above-mentioned combination mode is only a schematic illustration. During specific implementation, other combination methods can also be used to perform combination splicing according to other types of position coordinates. This specification is not limited.
  • the server can separately detect the form data of each image in the image data containing the contract to be processed, and then obtain the form data when it is determined that the form data exists, so as to extract the complete image data Form data, and feed back the extracted form data to the legal platform, so as to organize and generate the electronic file data for the contract for storage.
  • the server obtains the After the morphological vertical line and the morphological horizontal line, further feature enhancement processing can be performed on the obtained morphological vertical line and the morphological horizontal line to make the obtained morphological vertical line and morphological horizontal line clearer.
  • the above feature strengthening treatment may specifically be a morphological treatment, and may specifically include corrosion treatment and/or expansion treatment.
  • the data value of the pixel in the middle of the area can be reset (reset to 0 or 1) by sliding the area of the convolution kernel into the frame image.
  • corrosion treatment may be performed first, followed by expansion treatment.
  • the above-mentioned corrosion processing can be understood as an AND operation. Specifically, by corroding the pixels close to the foreground according to the size of the convolution kernel (that is, resetting the value of the corresponding pixel to 0), the foreground object becomes Small, which can reduce the white area around the morphological vertical line or morphological horizontal line to achieve the effect of removing white noise; at the same time, it can also break the structural elements adjacent or even connected to the above morphological vertical line or morphological horizontal line open.
  • the morphological vertical line or the morphological horizontal line after the corrosion processing may be continuously expanded.
  • the above expansion process can be understood as an OR operation.
  • the eroded image can be enlarged and restored through expansion to obtain relatively clear morphological vertical lines and morphological horizontal lines of constant size. .
  • the method for obtaining the table data provided in this specification is due to obtaining and extracting the combined image according to the graphic features of the morphological vertical line and the morphological horizontal line in the image data; then the combined image is divided into multiple
  • the rectangular units are divided into optical characters for each rectangular unit to obtain the text information contained in each rectangular unit, and then the rectangular units containing the text information are combined and restored according to the position coordinates of the rectangular unit to obtain complete table data, thereby solving
  • an embodiment of the present specification also provides a method for acquiring table data, where the method is specifically applied to the server side.
  • the method may include the following:
  • the above-mentioned to-be-processed text may specifically be a to-be-processed contract text, a to-be-processed constitution text, or a to-be-processed specification text.
  • the image data of the text to be processed may be a scanned image containing the text content, a photo containing the text content, or a video containing the text content.
  • the specific content and form of the image data of the text to be processed above are not limited in this specification.
  • S53 Extract a combination graph from the image data, wherein the combination graph is a graph including vertical morphological lines and horizontal morphological lines.
  • the above morphological vertical line and morphological horizontal line can be specifically understood as a structural element related to graphics that is different from text characters.
  • the morphological vertical line may specifically be an image unit or a structural element that contains a straight line segment along the vertical direction in the image.
  • the above-mentioned morphological horizontal line may specifically be an image unit or a structural element that contains a straight line segment along the horizontal direction in the image.
  • the above-mentioned combined graph can be specifically understood as the image data having graphic features similar to the table data, for example, a combined graph including graphic structural elements of crossing morphological vertical lines and morphological horizontal lines.
  • the above-mentioned extraction of the combined image from the image data may include the following: search and obtain the morphological vertical line and the morphological horizontal line in the image data; connect the morphology The vertical line and the morphological horizontal line obtain the combined diagram.
  • the above search and obtain the morphological vertical line and the morphological horizontal line in the image data may include the following content: by calling the getStructuringElement function in OpenCV to search for the structural element in the image , Find the morphological vertical line and morphological horizontal line in the image data.
  • the above-listed method of obtaining the morphological vertical line and the morphological horizontal line from the image by calling the getStructuringElement function is only a schematic illustration.
  • the morphological vertical line and the morphological horizontal line in the image may also be obtained in other suitable ways. This specification is not limited.
  • the morphological vertical line and the morphological horizontal line obtained in the above manner also carry position information in the image data, and then the corresponding information can be connected according to the position information of the morphological vertical line and the morphological horizontal line The morphology vertical line and the morphology horizontal line to get the combined picture.
  • S55 Divide the combined image into a plurality of rectangular units, where the plurality of rectangular units respectively carry position coordinates.
  • the above rectangular unit can be specifically understood as an image unit that corresponds one-to-one with a rectangular frame in the combination diagram, but distinguishes the rectangular frame and contains text information (such as text characters filled or blank) .
  • each rectangular frame can be specifically understood as a rectangular or square-shaped graphic element composed of two morphological vertical lines and two morphological horizontal lines, which simply contain only graphic features.
  • each rectangular frame can be regarded as a grid in the table.
  • the combination diagram is divided into a plurality of rectangular units.
  • the following contents may be included: obtaining the coordinates of the intersection point in the combination diagram; searching and obtaining the rectangular frame in the combination diagram; according to The coordinate of the intersection point in the combined graph determines the coordinates of the end points of the rectangular frame; and according to the coordinate of the endpoints of the rectangular frame, the combined graph is divided into a plurality of rectangular units.
  • intersection point can be specifically understood as the pixel point at the position where the vertical morphological line and the horizontal morphological line in the combination figure intersect.
  • the coordinates of the intersection point in the combined graph in the image can be searched and obtained by calling the opencv bitwise_and function in OpenCV.
  • OpenCV opencv bitwise_and function
  • the rectangular frame in the combined graph can be searched and obtained by calling the findContours function in OpenCV.
  • the findContours function in OpenCV.
  • the server may also obtain the rectangular frame in the combination diagram in other suitable ways according to specific conditions. This specification is not limited.
  • the above OpenCV Open source Computer Vision Library, source code computer vision library
  • the server can call the corresponding function code through the above OpenCV to efficiently perform data processing on the image data.
  • the combination diagram is divided into a plurality of rectangular units.
  • the following may be included: according to the coordinates of the intersection point in the combination diagram, determine the The coordinates of the end points of the rectangular frame; the dividing line is determined according to the coordinates of the end points of the rectangular frame; and the combined image is divided into a plurality of rectangular units according to the dividing lines.
  • the endpoint coordinates of the rectangular frame are determined according to the coordinates of the intersection point in the combination diagram, and in specific implementation, the following content may be included: the coordinates of the intersection point in the combination diagram and the rectangular frame are performed Position comparison to determine the four endpoints of each rectangular frame from the intersection, and then determine the coordinates of the endpoints of each rectangular frame.
  • the above-mentioned determination of the dividing line according to the coordinates of the end points of the rectangular frame may include the following content: according to the coordinates of the four end points of each rectangular frame, the outline line surrounding the rectangular frame is determined as the corresponding dividing line. Furthermore, subsequent division can be performed along the above division line, and each rectangular unit can be obtained from the combination diagram.
  • the method further includes the following content: generating position coordinates of the rectangular units according to the coordinates of the end points of the rectangular frame.
  • the position coordinates of the above rectangular unit can be specifically understood as a type used to indicate the position of the rectangular unit in the image of the combined image or describe the position of the rectangular unit and other adjacent rectangular units in the image of the combined image Parameter data of the relationship.
  • the coordinates of the center point of the rectangular frame may be calculated as the position coordinates of the corresponding rectangular unit according to the endpoint coordinates of the four end points of the rectangular frame. You can also calculate the coordinates of the center point of each rectangular frame first, and then follow the preset arrangement order, for example, from top to bottom and from left to right, according to the coordinates of the center point of each rectangular frame, arrange in order For each rectangular unit, determine the row number and column number of each sorted rectangular unit as the position coordinates of the corresponding rectangular unit.
  • the above-listed methods for determining the position coordinates of the rectangular unit are only schematic illustrations. During specific implementation, according to the specific situation, other suitable methods may also be used to determine the position coordinates of the rectangular unit. This specification is not limited.
  • S57 Perform optical character recognition on the plurality of rectangular units to determine the text information contained in the plurality of rectangular units.
  • each rectangular unit of the plurality of rectangular units may be subjected to separate optical character recognition to separately identify text characters in each rectangular unit, and then determine the location of each rectangular unit. Contains text information.
  • the text information contained in the rectangular unit may be left blank.
  • the rectangular units containing text information adjacent to the position coordinates may be stitched according to the position coordinates of each rectangular unit, and the rectangular units containing text information may be placed in the corresponding At the location of the data, so as to obtain the complete table data.
  • the combined graph is obtained by acquiring and extracting the graphic features such as the morphological vertical line and the morphological horizontal line in the image data; then the combined graph is divided into a plurality of rectangular units, and each rectangular unit is Optical character recognition to obtain the text information contained in each rectangular unit, and then the rectangular units containing the text information are combined and restored according to the position coordinates of the rectangular unit to obtain complete table data, thereby solving the problem of extracting table data existing in the existing methods The technical problem of large error and inaccuracy can be recognized efficiently and accurately, and the content of the table in the image data can be completely restored.
  • the method may further include the following when the method is specifically implemented: performing the image data of the text to be processed Preprocessing, wherein the preprocessing includes: converting the image data into a grayscale image; and/or performing Gaussian smoothing on the image data to filter out noise interference.
  • the preprocessing includes: converting the image data into a grayscale image; and/or performing Gaussian smoothing on the image data to filter out noise interference.
  • the above-mentioned extraction of the combined image from the image data may include the following content: search and obtain morphological vertical lines and morphological horizontal lines in the image data; connect the morphology The vertical line and the morphological horizontal line obtain the combined diagram.
  • the above search and obtain the morphological vertical line and the morphological horizontal line in the image data may include the following content: search and obtain the morphological vertical line in the image data through the getStructuringElement function Lines and morphological horizontal lines.
  • the method may further include the following contents: performing feature enhancement processing on the obtained morphological vertical line and morphological horizontal line respectively, wherein the feature enhancement processing includes at least one of the following: corrosion treatment And expansion treatment.
  • the morphological vertical line and the morphological horizontal line may be etched first, and then the morphological vertical line and the morphological horizontal line after the etching process may be expanded.
  • the white noise generated by the foreground of the morphological vertical line and the morphological horizontal line can be eliminated through the etching process, making the morphological vertical line and the morphological horizontal line clearer, but the morphological vertical line and the The graphical elements of the morphological horizontal lines are reduced. Therefore, after corroding the morphological vertical line and the morphological horizontal line, the morphological vertical line and the morphological horizontal line with a constant size can be recovered by the expansion treatment to be more clear.
  • the above-mentioned combination chart is only that the graphic features are similar to the table data, but it may not be table data.
  • the large text character "Tian” also has graphic features similar to table data. Therefore, the extracted combination chart can be tested to determine whether the combination chart meets the preset table format requirements, so as to more accurately determine whether the combination chart is real table data, and then can only be determined as table data.
  • the combination graph performs data processing, thereby reducing waste of resources and improving processing efficiency.
  • the method may further include: acquiring coordinates of the intersection point in the combined image, where the intersection point is the combination Pixels at the position where the morphological vertical line and the morphological horizontal line intersect in the figure; search and obtain the rectangular frame in the combined map; determine the endpoint coordinates of the rectangular frame according to the coordinates of the intersection point in the combined map; The endpoint coordinates of the rectangular frame determine whether the combined image meets the preset table format requirements.
  • the coordinates of the intersection point in the combined graph in the image can be searched and obtained by calling the opencv bitwise_and function.
  • the server may also obtain the coordinates of the intersection points in the combined graph in other suitable ways according to specific conditions. This specification is not limited.
  • the rectangular frame in the combined graph can be searched and obtained by calling the findContours function.
  • the findContours function is only a schematic illustration.
  • the server may also obtain the rectangular frame in the combination diagram in other suitable ways according to specific conditions. This specification is not limited.
  • the above-mentioned preset table format requirement can be specifically understood as a rule set for describing the graphic features of the data table different from other graphic structures.
  • the specific rules included in the above-mentioned preset table format requirements can be flexibly set according to specific conditions. For example, considering that the data table is different from other graphics, each grid graphic (or rectangular frame) is designed to fill in specific characters, that is, the minimum area of each grid graphic in the data table should be at least tolerable The next complete character. Therefore, the following rules for graphic area characteristics may be set: the minimum area of the grid pattern in the data table should be greater than a preset area threshold. Also considering that based on people's usual typesetting habits, the table data will be set to the center position when editing the table data.
  • the absolute value of the difference between the distance between the left border of the data table and the left border of the image and the distance between the right border of the data table and the right border of the image is less than the Set the distance threshold.
  • the following rules for the quantity characteristics of graphics may also be set: the number of grid graphics in the data table is greater than or equal to a preset quantity threshold (for example, 2), and so on.
  • the above determines whether the combined image meets the preset table format requirements according to the endpoint coordinates of the rectangular frame. In specific implementation, it may include the following: according to the endpoint coordinates of the rectangular frame, calculate The area of the rectangular frame; detecting whether the area of the rectangular frame is greater than a preset area threshold. If the area of the rectangular frame is greater than a preset area threshold, it is determined that the combined map meets the preset table format requirements.
  • the foregoing determines whether the combination map meets the preset table format requirements according to the endpoint coordinates of the rectangular frame.
  • the following may also be included: According to the endpoint coordinates of the rectangular frame in the combination map, respectively Determine the abscissa of the left border and the right border of the combined map; calculate the distance between the left border of the combined map and the left border of the image data based on the left border of the combined map.
  • a distance calculate the distance between the right border of the combination map and the right border of the image data according to the abscissa of the right border of the combination map, and record it as the second distance; calculate the distance difference between the first distance and the second distance Compare the absolute value of the difference with a preset distance threshold to detect whether the absolute value of the distance difference is less than the preset distance threshold. If the absolute value of the distance difference is less than a preset distance threshold, it is determined that the combination map meets the preset table format requirements.
  • the above-mentioned dividing the combined image into a plurality of rectangular units may include the following: determining the dividing line according to the coordinates of the end points of the rectangular frame; dividing the combined image into the following according to the dividing line A plurality of rectangular units, and generating position coordinates of the rectangular unit corresponding to the rectangular frame according to the end point coordinates of the rectangular frame.
  • the image data of the text to be processed may specifically include: a scanned image or a photograph containing a contract to be processed.
  • the image data of the to-be-processed text listed above is only for better explaining the embodiments of the present specification.
  • the image data of the text to be processed may also include image data of other types and contents, for example, a video screenshot containing a manual to be processed, etc. This specification is not limited.
  • the method for obtaining the table data is that the combined picture is obtained by obtaining and extracting the graphic features such as the morphological vertical line and the morphological horizontal line in the image data; then the combined map is divided into multiple The rectangular units are divided into optical characters for each rectangular unit to obtain the text information contained in each rectangular unit, and then the rectangular units containing the text information are combined and restored according to the position coordinates of the rectangular unit to obtain complete table data, thereby solving It solves the technical problems of large error and inaccuracy in the extraction of table data in the existing methods, so that it can be efficiently and accurately identified, and the content of the table in the image data can be completely restored; after the extraction of the combined image, according to the combined image
  • the included intersections, rectangular frames and other graphic factors detect whether the extracted combined image is tabular data in the text, thereby avoiding mistakenly identifying non-tabular data as tables, reducing errors, and improving the accuracy of obtaining tabular data.
  • An embodiment of this specification also provides a server including a processor and a memory for storing processor-executable instructions.
  • the following steps may be performed according to the instructions: acquiring image data of text to be processed; Extracting a combination diagram from the image data, wherein the combination diagram is a graph including vertical morphological and morphological horizontal lines; the combination diagram is divided into a plurality of rectangular units, wherein the plurality of rectangles The units carry position coordinates; perform optical character recognition on the multiple rectangular units to determine the text information contained in the multiple rectangular units; according to the position coordinates of the rectangular units, combine the rectangular units containing text information to obtain Tabular data.
  • this specification also provides another specific server, where the server includes a network communication port 601, a processor 602, and a memory 603.
  • the cables are connected so that each structure can perform specific data interactions.
  • the network communication port 601 may be specifically used to input image data of text to be processed
  • the processor 602 may be specifically used to extract a combined image from the image data, wherein the combined image is a graph including vertical morphological lines and horizontal morphological lines; the combined image is divided into A plurality of rectangular units, wherein the plurality of rectangular units respectively carry position coordinates; optical character recognition is performed on the plurality of rectangular units to determine the text information contained in the plurality of rectangular units; according to the position of the rectangular unit Coordinates, combined with rectangular cells containing text information, get table data.
  • the memory 603 may specifically be used to store image data of text to be processed input via the network communication port 601 and store corresponding instruction programs based on the processor 602.
  • the network communication port 601 may be a virtual port that is bound to different communication protocols so that different data can be sent or received.
  • the network communication port may be port 80 responsible for web data communication, port 21 responsible for FTP data communication, or port 25 responsible for mail data communication.
  • the network communication port may also be a physical communication interface or a communication chip.
  • it can be a wireless mobile network communication chip, such as GSM, CDMA, etc.; it can also be a Wifi chip; it can also be a Bluetooth chip.
  • the processor 602 can be implemented in any suitable manner.
  • the processor may adopt, for example, a microprocessor or a processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) executable by the (micro)processor, a logic gate, a switch, an application specific integrated circuit ( Application Specific (Integrated Circuit, ASIC), programmable logic controller and embedded microcontroller, etc.
  • a computer-readable program code such as software or firmware
  • the memory 603 may include multiple levels. In a digital system, as long as it can store binary data, it can be a memory. In an integrated circuit, a circuit with a storage function without a physical form is also called a memory. , Such as RAM, FIFO, etc.; in the system, the storage device with physical form is also called memory, such as memory stick, TF card, etc.
  • the embodiments of the present specification also provide a computer storage medium based on the above-mentioned table data acquisition method, where the computer storage medium stores computer program instructions, which are implemented when the computer program instructions are executed: acquiring image data of text to be processed ; Extract a combination graph from the image data, wherein the combination graph is a graph that includes crossed morphological vertical lines and morphological horizontal lines; divide the combination map into a plurality of rectangular units, wherein, the A plurality of rectangular units respectively carry position coordinates; perform optical character recognition on the plurality of rectangular units respectively to determine the text information contained in the plurality of rectangular units; according to the position coordinates of the rectangular units, combine rectangles containing text information Unit, get the table data.
  • the storage medium includes, but is not limited to, random access memory (Random Access Memory, RAM), read-only memory (Read-Only Memory, ROM), cache (Cache), hard disk (Hard Disk Drive, HDD) Or memory card (Memory Card).
  • RAM Random Access Memory
  • ROM read-only memory
  • cache cache
  • HDD Hard Disk Drive
  • Memory Card Memory Card
  • the memory may be used to store computer program instructions.
  • the network communication unit may be an interface configured to perform network connection communication according to the standard specified by the communication protocol.
  • the embodiment of the present specification also provides an apparatus for acquiring table data.
  • the apparatus may specifically include the following structural modules:
  • the obtaining module 71 can be specifically used to obtain image data of text to be processed
  • the extracting module 72 may be specifically used for extracting a combined image from the image data, wherein the combined image is a graph including vertical morphological lines and horizontal morphological lines;
  • the segmentation module 73 may be specifically used to segment the combined image into multiple rectangular units, where the multiple rectangular units each carry position coordinates;
  • the recognition module 74 may be specifically configured to perform optical character recognition on the plurality of rectangular units respectively and determine the text information contained in the plurality of rectangular units respectively;
  • the combining module 75 can be specifically used to combine rectangular units containing text information according to the position coordinates of the rectangular units to obtain table data.
  • the extraction module 72 may specifically include the following structural units:
  • the first search unit may specifically be used to search for and obtain morphological vertical lines and morphological horizontal lines in the image data
  • the connecting unit may specifically be used to connect the morphological vertical line and the morphological horizontal line to obtain the combined graph.
  • the apparatus may further specifically include a detection module, configured to detect whether the combination graph meets a preset table format requirement.
  • the detection module may specifically include the following structural units:
  • the obtaining unit may be specifically configured to obtain the coordinates of the intersection point in the combined graph, where the intersection point may specifically be a pixel point at a position where the morphological vertical line and the morphological horizontal line intersect in the combined map;
  • the second search unit may specifically be used to search for and obtain a rectangular frame in the combination diagram
  • the first determining unit may specifically be used to determine the coordinates of the end point of the rectangular frame according to the coordinates of the intersection in the combined graph;
  • the second determining unit may be specifically configured to determine whether the combined image meets the preset table format requirements according to the endpoint coordinates of the rectangular frame.
  • the second determining unit may be specifically configured to calculate the area of the rectangular frame according to the coordinates of the endpoints of the rectangular frame; and detect whether the area of the rectangular frame is greater than a preset area threshold.
  • the segmentation module 73 may specifically include the following structural units:
  • the third determining unit can be specifically used to determine the dividing line according to the coordinates of the end points of the rectangular frame
  • the dividing unit may specifically be used to divide the combined image into a plurality of rectangular units according to the dividing line, and generate position coordinates of the rectangular unit corresponding to the rectangular frame according to the end point coordinates of the rectangular frame.
  • the apparatus may further specifically include a preprocessing module for preprocessing the image data of the text to be processed, wherein the preprocessing may specifically include: converting the image data to gray Degree image; and/or, perform Gaussian smoothing on the image data, etc.
  • the image data of the text to be processed may specifically include: a scanned image or a photograph containing a contract to be processed.
  • the image data of the to-be-processed text listed above is only for better explaining the embodiments of the present specification.
  • the image data of the text to be processed may also include image data of other types and contents, for example, a video screenshot containing a manual to be processed, etc. This specification is not limited.
  • the units, devices, or modules explained in the foregoing embodiments may be specifically implemented by computer chips or entities, or implemented by products with certain functions.
  • the functions are divided into various modules and described separately.
  • the functions of each module may be implemented in one or more software and/or hardware, or the modules that implement the same function may be implemented by a combination of multiple submodules or subunits.
  • the device embodiments described above are only schematic.
  • the division of the unit is only a division of logical functions.
  • there may be another division manner for example, multiple units or components may be combined or integrated To another system, or some features can be ignored, or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical, or other forms.
  • the table data acquisition device provided by the embodiment of the present specification is obtained by the extraction module and extracted according to the morphological vertical lines and morphological horizontal lines in the image data to obtain the combined picture;
  • the module divides the combined image into multiple rectangular units, and performs optical character recognition on each rectangular unit type to obtain the text information contained in each rectangular unit, and then uses the combination module to divide the rectangle containing the text information according to the position coordinates of the rectangular unit.
  • Units are combined and restored to obtain complete table data, thereby solving the technical problem of large error and inaccuracy in the existing method of extracting table data, so as to achieve efficient and accurate identification, and completely restore the table content in the image data;
  • the combination module detects whether the extracted combination chart is tabular data in the text according to the intersection points, rectangular frames and other graphical factors contained in the combo chart, so as to avoid mistakenly identifying non-table data as Tables reduce errors and improve the accuracy of obtaining table data.
  • the method can be logically programmed to enable the controller to use logic gates, switches, special integrated circuits, programmable logic controllers and embedded To achieve the same function in the form of a microcontroller, etc. Therefore, such a controller can be regarded as a hardware component, and the device for implementing various functions included therein can also be regarded as a structure within the hardware component. Or even, the device for realizing various functions can be regarded as both a software module of the implementation method and a structure within a hardware component.
  • program modules include routines, programs, objects, components, data structures, classes, etc. that perform specific tasks or implement specific abstract data types.
  • This specification can also be practiced in distributed computing environments in which tasks are performed by remote processing devices connected through a communication network.
  • program modules may be located in local and remote computer storage media including storage devices.

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Artificial Intelligence (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Processing Or Creating Images (AREA)
  • Character Input (AREA)
  • Image Analysis (AREA)

Abstract

L'invention concerne un procédé et un appareil d'acquisition de données de tableau, ainsi qu'un serveur. Le procédé selon l'invention consiste : à obtenir des données d'image de texte à traiter ; à extraire un graphique combiné à partir des données d'image, le graphique combiné étant un graphique contenant des lignes verticales morphologiques et des lignes horizontales morphologiques se croisant ; à diviser le graphique combiné en une pluralité d'unités rectangulaires ; à effectuer une reconnaissance optique de caractères sur les unités rectangulaires, respectivement, et à déterminer des informations textuelles des unités rectangulaires ; et, en fonction des coordonnées de position des unités rectangulaires, à combiner les unités rectangulaires contenant les informations textuelles afin d'obtenir des données de tableau. Selon l'invention, les problèmes techniques liés aux erreurs et imprécisions importantes dans l'extraction de données de tableau dans un procédé existant peuvent être résolus par l'obtention de caractéristiques graphiques telles que des lignes verticales et des lignes horizontales morphologiques dans des données d'image et par l'obtention d'un graphique combiné, en fonction des caractéristiques graphiques, puis par la division du graphique combiné en une pluralité d'unités rectangulaires pour une reconnaissance optique de caractères afin d'obtenir des informations textuelles des unités rectangulaires, et par la réalisation d'une réduction de combinaison en fonction des coordonnées de position afin d'obtenir des données de tableau.
PCT/CN2019/124101 2019-01-04 2019-12-09 Procédé et appareil d'acquisition de données de tableau, et serveur associé WO2020140698A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201910006706.1A CN110008809B (zh) 2019-01-04 2019-01-04 表格数据的获取方法、装置和服务器
CN201910006706.1 2019-01-04

Publications (1)

Publication Number Publication Date
WO2020140698A1 true WO2020140698A1 (fr) 2020-07-09

Family

ID=67165348

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2019/124101 WO2020140698A1 (fr) 2019-01-04 2019-12-09 Procédé et appareil d'acquisition de données de tableau, et serveur associé

Country Status (2)

Country Link
CN (1) CN110008809B (fr)
WO (1) WO2020140698A1 (fr)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111881883A (zh) * 2020-08-10 2020-11-03 晶璞(上海)人工智能科技有限公司 一种基于卷积特征提取与形态学处理的表格文档提取方法
CN112364834A (zh) * 2020-12-07 2021-02-12 上海叠念信息科技有限公司 一种基于深度学习和图像处理的表格识别的还原方法
CN112712014A (zh) * 2020-12-29 2021-04-27 平安健康保险股份有限公司 表格图片结构解析方法、系统、设备和可读存储介质
CN114926852A (zh) * 2022-03-17 2022-08-19 支付宝(杭州)信息技术有限公司 表格识别重构方法、装置、设备、介质及程序产品

Families Citing this family (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110008809B (zh) * 2019-01-04 2020-08-25 阿里巴巴集团控股有限公司 表格数据的获取方法、装置和服务器
CN110675384B (zh) * 2019-09-24 2022-06-07 广东博智林机器人有限公司 图像处理方法及装置
CN111126409B (zh) * 2019-12-26 2023-08-18 南京巨鲨显示科技有限公司 一种医学图像区域识别方法及系统
CN111160234B (zh) * 2019-12-27 2020-12-08 掌阅科技股份有限公司 表格识别方法、电子设备及计算机存储介质
CN111027521B (zh) * 2019-12-30 2023-12-29 上海智臻智能网络科技股份有限公司 文本处理方法及系统、数据处理设备及存储介质
CN111325110B (zh) * 2020-01-22 2024-04-05 平安科技（深圳）有限公司 基于ocr的表格版式恢复方法、装置及存储介质
CN113343740B (zh) * 2020-03-02 2022-05-06 阿里巴巴集团控股有限公司 表格检测方法、装置、设备和存储介质
CN111460774B (zh) * 2020-04-02 2023-06-30 北京易优联科技有限公司 曲线中数据的还原方法、装置、存储介质、电子设备
CN111640130A (zh) * 2020-05-29 2020-09-08 深圳壹账通智能科技有限公司 表格还原方法及装置
CN111757182B (zh) * 2020-07-08 2022-05-31 深圳创维－Rgb电子有限公司 图像花屏检测方法、设备、计算机设备和可读存储介质
CN111985506A (zh) * 2020-08-21 2020-11-24 广东电网有限责任公司清远供电局 一种图表信息提取方法、装置和存储介质
CN112200117B (zh) * 2020-10-22 2023-10-13 长城计算机软件与系统有限公司 表格识别方法及装置
CN112733855B (zh) * 2020-12-30 2024-04-09 科大讯飞股份有限公司 表格结构化方法、表格恢复设备及具有存储功能的装置
CN112861736B (zh) * 2021-02-10 2022-08-09 上海大学 基于图像处理的文献表格内容识别与信息提取方法
CN113569677A (zh) * 2021-07-16 2021-10-29 国网天津市电力公司 一种基于扫描件的纸质试验报告生成方法

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130016381A1 (en) * 2011-07-12 2013-01-17 Fuji Xerox Co., Ltd. Image processing apparatus, non-transitory computer readable medium storing program and image processing method
CN104462044A (zh) * 2014-12-16 2015-03-25 上海合合信息科技发展有限公司 表格图像识别编辑方法及装置
CN105426856A (zh) * 2015-11-25 2016-03-23 成都数联铭品科技有限公司 一种图像表格文字识别方法
CN108132916A (zh) * 2017-11-30 2018-06-08 厦门市美亚柏科信息股份有限公司 解析pdf表格数据的方法、存储介质
CN110008809A (zh) * 2019-01-04 2019-07-12 阿里巴巴集团控股有限公司 表格数据的获取方法、装置和服务器

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6996295B2 (en) * 2002-01-10 2006-02-07 Siemens Corporate Research, Inc. Automatic document reading system for technical drawings
CN107622230B (zh) * 2017-08-30 2019-12-06 中国科学院软件研究所 一种基于区域识别与分割的pdf表格数据解析方法
CN107943857A (zh) * 2017-11-07 2018-04-20 中船黄埔文冲船舶有限公司 自动读取AutoCAD表格的方法、装置、终端设备与存储介质
CN109086714B (zh) * 2018-07-31 2020-12-04 国科赛思(北京)科技有限公司 表格识别方法、识别系统及计算机装置

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130016381A1 (en) * 2011-07-12 2013-01-17 Fuji Xerox Co., Ltd. Image processing apparatus, non-transitory computer readable medium storing program and image processing method
CN104462044A (zh) * 2014-12-16 2015-03-25 上海合合信息科技发展有限公司 表格图像识别编辑方法及装置
CN105426856A (zh) * 2015-11-25 2016-03-23 成都数联铭品科技有限公司 一种图像表格文字识别方法
CN108132916A (zh) * 2017-11-30 2018-06-08 厦门市美亚柏科信息股份有限公司 解析pdf表格数据的方法、存储介质
CN110008809A (zh) * 2019-01-04 2019-07-12 阿里巴巴集团控股有限公司 表格数据的获取方法、装置和服务器

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111881883A (zh) * 2020-08-10 2020-11-03 晶璞(上海)人工智能科技有限公司 一种基于卷积特征提取与形态学处理的表格文档提取方法
CN112364834A (zh) * 2020-12-07 2021-02-12 上海叠念信息科技有限公司 一种基于深度学习和图像处理的表格识别的还原方法
CN112712014A (zh) * 2020-12-29 2021-04-27 平安健康保险股份有限公司 表格图片结构解析方法、系统、设备和可读存储介质
CN112712014B (zh) * 2020-12-29 2024-04-30 平安健康保险股份有限公司 表格图片结构解析方法、系统、设备和可读存储介质
CN114926852A (zh) * 2022-03-17 2022-08-19 支付宝(杭州)信息技术有限公司 表格识别重构方法、装置、设备、介质及程序产品

Also Published As

Publication number Publication date
CN110008809B (zh) 2020-08-25
CN110008809A (zh) 2019-07-12

Similar Documents

Publication Publication Date Title
WO2020140698A1 (fr) Procédé et appareil d'acquisition de données de tableau, et serveur associé
US20210256253A1 (en) Method and apparatus of image-to-document conversion based on ocr, device, and readable storage medium
WO2019119966A1 (fr) Procédé de traitement d'image de texte, dispositif, équipement et support d'informations
CN110942074B (zh) 字符切分识别方法、装置、电子设备、存储介质
CN109753953B (zh) 图像中定位文本的方法、装置、电子设备和存储介质
CN109410215A (zh) 图像处理方法、装置、电子设备及计算机可读介质
CN105469027A (zh) 针对文档图像的水平和垂直线检测和移除
CN109948521B (zh) 图像纠偏方法和装置、设备及存储介质
US20180082456A1 (en) Image viewpoint transformation apparatus and method
CN112651953B (zh) 图片相似度计算方法、装置、计算机设备及存储介质
US20190266431A1 (en) Method, apparatus, and computer-readable medium for processing an image with horizontal and vertical text
CN113642584A (zh) 文字识别方法、装置、设备、存储介质和智能词典笔
CN114359932B (zh) 文本检测方法、文本识别方法及装置
CN115719356A (zh) 图像处理方法、装置、设备和介质
CN116844177A (zh) 一种表格识别方法、装置、设备及存储介质
CN112507938A (zh) 一种文本图元的几何特征计算方法及识别方法、装置
CN115620321B (zh) 表格识别方法及装置、电子设备和存储介质
CN108304840B (zh) 一种图像数据处理方法以及装置
CN114120305B (zh) 文本分类模型的训练方法、文本内容的识别方法及装置
US11570331B2 (en) Image processing apparatus, image processing method, and storage medium
JP2012003358A (ja) 背景判別装置、方法及びプログラム
CN115019321A (zh) 一种文本识别、模型训练方法、装置、设备及存储介质
CN114140805A (zh) 图像处理方法、装置、电子设备及存储介质
CN113486881A (zh) 一种文本识别方法、装置、设备及介质
CN114648751A (zh) 一种处理视频字幕的方法、装置、终端及存储介质

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 19907609

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 19907609

Country of ref document: EP

Kind code of ref document: A1