Drawing processing device and drawing processing method

Abstract

[Problem] To provide a drawing processing device capable of acquiring information written in a table included in drawing data. [Solution] A drawing processing device according to the present invention includes: a drawing reception unit 202 that receives drawing data D10 in which characters are written inside boxes separated by lines and the boxes contain one or a plurality of tables in which the attributes of the characters are defined; and a drawing processing unit 204A that acquires table information, which relates to a table to be detected having a to-be-detected feature, from a candidate region 14 within a drawing region 10 of the drawing data D10 received by the drawing reception unit 202, the candidate region 14 having said table to be detected disposed therein.

Description

Drawing processing device and drawing processing method

[0001] The present invention relates to a drawing processing device and a drawing processing method.

[0002] Drawings used in various fields such as machinery, architecture, civil engineering, electricity, and apparel contain, for example, lines (external lines, dimension lines, etc.) representing shapes and structures, as well as various types of information written in text. Because the text written on drawings is important information for understanding the contents of the drawings, systems for utilizing this information have been developed. For example, Patent Document 1 discloses a support system that acquires text representing dimensional quantities written in association with the dimension lines of a figure and creates a list showing the dimensional quantities of the figure.

[0003] Japanese Patent Application Publication No. 10-293777

[0004] In addition to the characters representing dimensional quantities, various information is written in a tabular format on the drawing, as described above. The tabular information is written in boxes separated by ruled lines, with attributes defined for each box and characters corresponding to each attribute. However, the support system disclosed in Patent Document 1 can only acquire characters representing dimensional quantities that are written in association with the dimension lines of figures, and does not acquire characters written in a tabular format from the drawing. Therefore, it is not possible to properly acquire important information for understanding the contents of the drawing.

[0005] The present invention has been made in response to the above-mentioned problems, and aims to provide a drawing processing device and a drawing processing method that are capable of acquiring information contained in tables included in drawing data.

[0006] In order to achieve the above object, a drawing processing device according to one embodiment of the present invention comprises: a drawing reception unit that receives drawing data in which characters are written in boxes separated by lines and the boxes contain one or more tables in which attributes of the characters are defined; and a drawing processing unit that acquires table information regarding the table to be detected from a candidate area in the drawing area of ​​the drawing data received by the drawing reception unit in which the table to be detected, which has the characteristics of the table to be detected, is located.

[0007] According to a drawing processing apparatus according to an aspect of the present invention, it is possible to acquire information written in a table included in drawing data.

[0008] Problems, configurations, and effects other than those described above will become apparent from the detailed description of the invention that follows.

[0009] 1 is an overall configuration diagram showing an example of a drawing management system 1. FIG. 2 is a diagram showing an example of drawing data D10. FIG. 3 is a diagram showing an example of a drawing database 210. FIG. 4 is a block diagram showing an example of a drawing processing device 2A according to the first embodiment. FIG. 5 is a functional explanatory diagram showing an example of a learning model generation unit 201A according to the first embodiment. FIG. 6 is a functional explanatory diagram showing examples of a drawing acceptance unit 202, a character recognition unit 203, and a drawing processing unit 204A according to the first embodiment. FIG. 7 is a hardware configuration diagram showing an example of a computer 900. FIG. 8 is a flowchart showing an example of the operation (drawing processing method) of the drawing processing device 2A according to the first embodiment. FIG. 9 is a block diagram showing an example of a drawing processing device 2B according to the second embodiment. FIG. 10 is a functional explanatory diagram showing an example of a learning model generation unit 201B according to the second embodiment. FIG. 11 is a functional explanatory diagram showing examples of a drawing acceptance unit 202, a character recognition unit 203, and a drawing processing unit 204B according to the second embodiment. FIG. 12 is a flowchart showing an example of the operation (drawing processing method) of the drawing processing device 2B according to the second embodiment.

[0010] Hereinafter, an embodiment for carrying out the present invention will be described with reference to the drawings. The scope necessary for the explanation to achieve the object of the present invention will be schematically shown, and the scope necessary for explaining the relevant part of the present invention will be mainly explained, and the parts that are omitted from the explanation will be based on publicly known techniques.

[0011] 1 is a diagram showing an overall configuration of an example of a drawing management system 1. The drawing management system 1 functions as a system for managing drawing data D10.

[0012] The drawing data D10 handled by the drawing management system 1 is, for example, any drawing recorded as digital data, such as mechanical drawings such as assembly drawings and parts drawings, architectural drawings, electrical circuit drawings, pneumatic circuit drawings, hydraulic circuit drawings, and apparel drawings. In this case, the drawing data D10 may be vector-format data or raster-format data. For example, the drawing data D10 may be CAD data (an example of vector format) output by various CAD software, or image data (an example of raster format) output by scanning a drawing printed on paper using a scanner or the like. The drawing data D10 may be drawn using any projection method or may be a three-dimensional drawing. The drawing data D10 may also include tables, and may be, for example, documents such as slips recorded as digital data.

[0013] 1, the drawing management system 1 includes a drawing processing device 2A and a user terminal device 3. The drawing processing device 2A and the user terminal device 3 are connected to a wired or wireless network 4 and are configured to be able to send and receive various data to and from each other. Note that the number of drawing processing devices 2A and user terminal devices 3 and the connection configuration of the network 4 are not limited to the example in FIG. 1 and may be changed as appropriate.

[0014] The drawing processing device 2A is a server-type computer or a cloud-type computer, and is configured as a general-purpose or dedicated computer (see FIG. 7 described later), etc. The drawing processing device 2A includes a drawing database 210 that can register drawing data D10 and additional information (described in detail later) included in the drawing data D10 in association with each other.

[0015] The drawing processing device 2A receives new drawing data D10 from the user terminal device 3, acquires additional information included in the drawing data D10, and registers the information in the drawing database 210. The drawing processing device 2A also provides the user terminal device 3 with display information for referencing and editing the drawing data D10 and additional information already registered (existing) in the drawing database 210.

[0016] The user terminal device 3 is a client-type computer, and is configured by a general-purpose or dedicated computer (see FIG. 7 described later), etc. The user terminal device 3 accepts various input operations via a display screen such as an application or a browser, and outputs various information via the display screen or voice, in order to register new drawing data D10, refer to and edit existing drawing data D10, etc.

[0017] 2 is a diagram showing an example of the drawing data D10. In this embodiment, the drawing data D10 will be mainly described as an assembly drawing, as shown in FIG.

[0018] The drawing area 10 of the drawing data D10 includes a shape area 11, a title block 12, and a parts list 13. The drawing area 10 corresponds to the entire area of ​​the paper when the drawing data D10 is printed on a paper medium.

[0019] The shape area 11 is an area where the shape and structure of an assembly or part are described. Lines that define the shape and structure of an assembly or part, such as outline lines, dimension lines, hidden lines, center lines, imaginary lines, etc., are described in the shape area 11. Characters indicating dimensions, tolerances, part numbers, etc. are also described in the shape area 11.

[0020] The title block 12 and the parts list 13 are types of tables included in the drawing data D10. A table has vertical and horizontal ruled lines and boxes separated by the ruled lines. Characters are written in the boxes, and attributes of the characters written in the box are defined for each box. Boxes are also classified by properties that indicate the type of box. Examples of properties include attribute heading properties, serial number heading properties, attributeless field properties, attributed field properties, etc.

[0021] As shown in FIG. 2 , the attributes of the title block 12 include, for example, product name, drawing number, scale, date, designer, approver, etc. The boxes in the title block 12 are classified into attribute-containing field properties, attribute header properties, and attribute-free field properties. The boxes classified as attribute-containing field properties contain field characters (in the example of FIG. 2 , “1:2,” “2024 / 1 / 11,” “ASSY A,” and “F1-222-33-A”) that represent the contents of the title block 12, and attribute characters (in the example of FIG. 2 , “scale,” “date,” “product name,” and “drawing number”) that define the attributes of the field characters. The boxes classified as attribute header properties contain attribute characters (in the example of FIG. 2 , “designer” and “approver”) that define the attributes of the field characters. The boxes classified as attribute-free field properties contain field characters (in the example of FIG. 2 , “AAA” and “BBB”) that represent the contents of the title block 12.

[0022] As shown in FIG. 2 , attributes of the BOM 13 include, for example, number, item name, material, and quantity. The boxes in the first row from the top of the BOM 13 are classified as attribute header properties, and attribute header characters defining the attributes of each column of the BOM 13 as headers (in the example of FIG. 2 , "Number," "Item Name," "Material," and "Quantity") are entered. The boxes in the first column on the left side of the BOM 13 are classified as serial number header properties, and serial number header characters defining the serial numbers of each row of the BOM 13 as headers (in the example of FIG. 2 , "1," "2," and "3") are entered. The other boxes in the BOM 13 are classified as attributeless field properties, which do not contain attribute characters, and field characters (in the example of FIG. 2 , "COVER," "PPP," "1," "BODY," "QQQ," "1," "LEG," "RRR," and "4") are entered as the contents of the BOM 13.

[0023] The types of tables included in the drawing data D10 are not limited to the title block 12 and the parts list 13, but may be other types of tables. The arrangement and number of boxes constituting a table may be changed as appropriate depending on the type of table, and the attributes defined for each box are not limited to the above examples.

[0024] 3 is a diagram showing an example of the drawing database 210. In the drawing database 210, for each piece of drawing data D10 in image data format, shape information D11 included in the drawing data D10 and additional information D12 included in the drawing data D10 are registered in association with each other.

[0025] The shape information D11 is registered in the drawing database 210 by cutting out the shape area 11 included in the drawing area 10.

[0026] The additional information D12 is registered in the drawing database 210 by acquiring the characters (mainly field characters) written in the drawing area 10 as text data by attribute. Fig. 3 illustrates a case where the text data by attribute acquired from the title block 12 and parts list 13 included in the drawing data D10 shown in Fig. 2 is registered in the drawing database 210 as the additional information D12.

[0027] In the drawing database 210, the additional information D12 associated with the drawing data D10 and registered is not limited to the contents of the title block 12 and the parts list 13, but can be associated with any information as needed. For example, the drawing database 210 may be configured to be able to register information based on the shape region 11 (dimensions, tolerances, surface treatment, heat treatment, etc.) and information regarding estimate requests (user name, estimate date and time, estimated price, etc.), but is not limited to these.

[0028] (Configuration of drawing processing device 2A) Fig. 4 is a block diagram showing an example of a drawing processing device 2A according to the first embodiment. Fig. 5 is a functional explanatory diagram showing an example of a learning model generation unit 201A according to the first embodiment. Fig. 6 is a functional explanatory diagram showing examples of a drawing acceptance unit 202, a character recognition unit 203, and a drawing processing unit 204A according to the first embodiment.

[0029] The drawing processing device 2A includes a control unit 20, a data storage unit 21, a trained model storage unit 22, a communication unit 23, an input unit 24, and an output unit 25.

[0030] The communication unit 23 is connected to an external device (e.g., the user terminal device 3, etc.) via the network 4 and functions as a communication interface for transmitting and receiving various types of data. The input unit 24 accepts various input operations, and the output unit 25 functions as a user interface by outputting various types of information via a display screen or voice. Note that the input unit 24 and the output unit 25 may be omitted.

[0031] The data storage unit 21 stores a drawing database 210 and an information processing program 211A. As shown in Fig. 3, the drawing database 210 stores a plurality of pieces of information included in the drawing data D10 in association with each other. The specific configuration of the drawing database 210 is not limited to the example shown in Fig. 3 and may be designed as appropriate.

[0032] The trained model storage unit 22 stores trained learning models 220. The learning models 220 stored in the trained model storage unit 22 may be provided to other devices via the network 4, a recording medium, or the like. The number of learning models 220 stored in the trained model storage unit 22 is not limited to one, and multiple inference models with different conditions, such as differences in machine learning methods or data, may be stored and made available selectively or in parallel.

[0033] 3, the data storage unit 21 and the trained model storage unit 22 are shown as two storage units, but they may be configured as a single storage unit or three or more storage units. Furthermore, at least one of the data storage unit 21 and the trained model storage unit 22 may be configured as a storage unit of an external computer (e.g., a server-type computer or a cloud-type computer).

[0034] The control unit 20 functions as a transmission / reception control unit 200, a learning model generation unit 201A, a drawing acceptance unit 202, a character recognition unit 203, a drawing processing unit 204A, and a database management unit 205 by executing the information processing program 211A recorded in the data storage unit 21.

[0035] (Transmission / reception control unit 200) The transmission / reception control unit 200 transmits and receives various types of data to and from an external device (for example, the user terminal device 3, etc.). For example, the transmission / reception control unit 200 transmits display information to the user terminal device 3 for outputting various display screens on the user terminal device 3, and receives operation information from the user terminal device 3 for accepting input operations performed on the display screen of the user terminal device 3. In doing so, the transmission / reception control unit 200 cooperates with the respective units 201 to 205 to transmit display information to the user terminal device 3 and receive operation information from the user terminal device 3.

[0036] (Learning Model Generation Unit 201A) As shown in FIGS. 4 and 5, the learning model generation unit 201A includes a learning data acquisition unit 2010A and a machine learning unit 2011A.

[0037] The learning data acquisition unit 2010A references the drawing database 210 and acquires learning data D13 consisting of input data and output data. The learning data D13 is data used as teacher data (training data), verification data, and test data in supervised learning. The output data constituting the learning data D13 is data used as a correct answer label in supervised learning.

[0038] The input data constituting the learning data D13 is the drawing data D10. Note that the input data constituting the learning data D13 may include, as the recognition result of the character recognition unit 203, text data indicating the characters written in the drawing area 10 and position data indicating the positions at which the characters are written.

[0039] The output data constituting the learning data D13 is a candidate area 14 that surrounds a table to be detected within the drawing area 10 of the drawing data D10. In the drawing data D10 shown in FIG. 2, the table to be detected corresponds to the title block 12 and the parts list 13, but in this embodiment, the description will be focused on the case where the table to be detected is the parts list 13.

[0040] The learning data acquisition unit 2010A acquires learning data D13 by annotating drawing data D10 registered in the drawing database 210. For example, the learning data acquisition unit 2010A acquires learning data D13 by displaying the drawing data D10 on a display screen of the drawing processing device 2A or the user terminal device 3 and accepting an input operation of a candidate area 14 as an annotation in the drawing area 10 on the display screen so as to surround a table to be detected. Note that the learning data acquisition unit 2010A may acquire learning data D13 in cooperation with an external device connected via the network 4.

[0041] The machine learning unit 2011A performs machine learning to make the learning model 220 learn the correlation between input data and output data using multiple sets of learning data D13 acquired by the learning data acquisition unit 2010A. As the learning model 220, for example, a neural network type (including deep learning) such as a convolutional neural network, a recurrent neural network, or a vision transformer, a tree type such as a decision tree or a regression tree, ensemble learning such as bagging or boosting, a clustering type such as hierarchical clustering, non-hierarchical clustering, k-nearest neighbors, or k-means, a multivariate analysis such as principal component analysis, factor analysis, or logistic regression, a support vector machine, or the like can be used.

[0042] The timing at which the machine learning unit 2011A performs machine learning on the learning model generation unit 201A may be when the number of pieces of drawing data D10 registered in the drawing database 210 exceeds a predetermined number, or when instructions are received from the user, but is not limited to these.

[0043] (Drawing Receiving Unit 202) The drawing receiving unit 202 receives the drawing data D10 from the user terminal device 3 via the transmission / reception control unit 200, for example, to receive new drawing data D10.

[0044] (Character Recognition Unit 203) The character recognition unit 203 recognizes characters included in the new drawing data D10 accepted by the drawing accepting unit 202. The character recognition unit 203 recognizes characters included in the drawing data D10, for example, by performing optical character recognition (OCR) and reading the characters as text data. As the character recognition results, text data indicating the characters and position data indicating the position where the characters are written are acquired. At this time, the character recognition results may be displayed on the display screen of the user terminal device 3, and the user may perform editing operations. Note that if text data is embedded in the drawing data D10, the character recognition unit 203 may recognize characters included in the drawing data D10 by reading the text data.

[0045] (Drawing processing unit 204A) As shown in Figure 6, the drawing processing unit 204A acquires table information regarding the table to be detected from the candidate area 14 in the drawing area 10 of the new drawing data D10 accepted by the drawing accepting unit 202, in which the table to be detected, which has the characteristics of the detection target, is located.

[0046] Specifically, the drawing processing unit 204A performs a candidate area identification process to identify a candidate area 14 in which the table to be detected is located within the drawing area 10 of the new drawing data D10, and a table information acquisition process to acquire table information from the candidate area 14 identified by the candidate area identification process.

[0047] As the candidate area identification process, the drawing processing unit 204A inputs new drawing data D10 into the learning model 220, thereby identifying the candidate area 14 included in the drawing area 10 of the drawing data D10. Note that if not only the drawing data D10 but also text data indicating characters written in the drawing area 10 and position data indicating the position where the characters are written are input to the learning model 220, the recognition result of the character recognition unit 203 for the drawing data D10 can be input.

[0048] In the table information acquisition process, the drawing processing unit 204A acquires table information based on the characters in boxes placed in the candidate area 14 among the characters recognized by the character recognition unit 203 and the attributes defined for the boxes. In this process, the drawing processing unit 204A acquires table information by recognizing the table format configuration based on the arrangement and properties of each box, for example, and treating the characters in the boxes as characters for each attribute.

[0049] (Database management unit 205) The database management unit 205 associates table information acquired as a processing result of the drawing processing unit 204A on new drawing data D10 with the drawing data D10 as additional information D12 and registers it in the drawing database 210. Then, the database management unit 205 transmits display information for displaying the processing result of the drawing processing unit 204A to the user terminal device 3 via the transmission / reception control unit 200.

[0050] Furthermore, the database management unit 205 reads out the drawing data D10 registered in the drawing database 210 and transmits display information for displaying the registered drawing data D10 to the user terminal device 3 via the transmission / reception control unit 200. Then, when the database management unit 205 receives operation information for editing the drawing data D10 from the user terminal device 3 via the transmission / reception control unit 200, it modifies the drawing data D10 registered in the drawing database 210.

[0051] 7 is a hardware configuration diagram showing an example of a computer 900. The drawing processing device 2A and the user terminal device 3 in the drawing management system 1 are configured by a general-purpose or dedicated computer 900.

[0052] 7, the computer 900 includes, as its main components, a bus 910, a processor 912, a memory 914, an input device 916, an output device 917, a display device 918, a storage device 920, a communication I / F (interface) unit 922, an external device I / F unit 924, an I / O (input / output) device I / F unit 926, and a media input / output unit 928. Note that the above components may be omitted as appropriate depending on the application of the computer 900.

[0053] The processor 912 is composed of one or more arithmetic processing devices (such as a CPU (Central Processing Unit), an MPU (Micro-processing unit), a DSP (Digital Signal Processor), or a GPU (Graphics Processing Unit)), and operates as a control unit that controls the entire computer 900. The memory 914 stores various data and programs 930, and is composed of, for example, a volatile memory (DRAM, SRAM, etc.) that functions as a main memory, a non-volatile memory (ROM), a flash memory, etc.

[0054] The input device 916 is composed of, for example, a keyboard, a mouse, a numeric keypad, an electronic pen, a microphone, etc., and functions as an input unit. The output device 917 is composed of, for example, a sound (audio) output device, a vibration device, etc., and functions as an output unit. The display device 918 is composed of, for example, a liquid crystal display, an organic EL display, electronic paper, a projector, etc., and functions as an output unit. The input device 916 and the display device 918 may be integrated, such as a touch panel display. The storage device 920 is composed of, for example, an HDD, an SSD, etc., and functions as a storage unit. The storage device 920 stores various data necessary for executing the operating system and the program 930.

[0055] The communication I / F unit 922 is connected to a network 940 such as the Internet or an intranet (which may be the same as network 4 in FIG. 1) via a wired or wireless connection and functions as a communication unit that transmits and receives data to and from other computers in accordance with a predetermined communication standard. The external device I / F unit 924 is connected to an external device 950 such as a camera, printer, scanner, or reader / writer via a wired or wireless connection and functions as a communication unit that transmits and receives data to and from the external device 950 in accordance with a predetermined communication standard. The I / O device I / F unit 926 is connected to I / O devices 960 such as various sensors and actuators and functions as a communication unit that transmits and receives various signals and data, such as detection signals from sensors and control signals to actuators, to and from the I / O devices 960. The media input / output unit 928 is composed of a drive device such as a DVD drive or a CD drive and reads and writes data from and to media (non-transitory storage media) 970 such as DVDs and CDs.

[0056] In the computer 900 having the above configuration, the processor 912 loads a program 930 stored in the storage device 920 into the memory 914, executes the program, and controls each unit of the computer 900 via the bus 910. The program 930 may be stored in the memory 914 instead of the storage device 920. The program 930 may be recorded on the medium 970 in an installable file format or an executable file format and provided to the computer 900 via the media input / output unit 928. The program 930 may be provided to the computer 900 by downloading it via the communication I / F unit 922 over the network 940. Furthermore, the computer 900 may implement various functions realized by the processor 912 executing the program 930 using hardware such as an FPGA or an ASIC.

[0057] The computer 900 is an electronic device of any type, such as a desktop computer or a portable computer. The computer 900 may be a client computer, a server computer, a cloud computer, or an embedded computer such as a control panel or a controller (including a microcomputer, a programmable logic controller, or a sequencer).

[0058] (Operation of drawing processing device 2A) Figure 8 is a flowchart showing an example of the operation (drawing processing method) of the drawing processing device 2A according to the first embodiment. Note that the series of drawing processing methods by the drawing processing device 2A shown in Figure 8 will be described as being executed when the drawing processing device 2A receives new drawing data D10 from a user terminal device 3 operated by a user. Also, the description will be given assuming that a trained learning model 220 is stored in the trained model storage unit 22 by the trained model generation unit 201A performing a training data acquisition step, a machine learning step, and a trained model storage step as shown in Figure 5.

[0059] First, in step S100 (drawing reception step), the drawing reception unit 202 receives new drawing data D10 by receiving the drawing data D10 from the user terminal device 3. At this time, the drawing reception unit 202 may receive a plurality of pieces of drawing data D10.

[0060] Next, in step S110 (character recognition step), the character recognition unit 203 recognizes characters included in the drawing data D10 received in step S100.

[0061] Next, in step S120 (drawing processing step), the drawing processing unit 204A inputs new drawing data D10 into the learning model 220, thereby performing a candidate area identification process to identify the candidate area 14 of the parts list 13 included in the drawing area 10 of the drawing data D10.

[0062] Then, in step S130, the drawing processing unit 204A performs a table information acquisition process to acquire table information of the parts table 13 based on the characters in the boxes placed in the candidate area 14 of the parts table 13, among the characters recognized in step S110, and the attributes defined for the boxes.

[0063] Next, in step S140 (database management process), the database management unit 205 registers the table information obtained as a result of processing steps S120 and S130 as additional information D12 in the drawing database 210, associating it with the drawing data D10 accepted in step S100.

[0064] Then, in step S141, the database management unit 205 transmits display information for displaying the processing results of steps S120 and S130 to the user terminal device 3. As a result, the additional information D12 registered for the new drawing data D10 is displayed on the display screen of the user terminal device 3.

[0065] As described above, according to the drawing processing device 2A and drawing processing method of this embodiment, the drawing processing unit 204A identifies the candidate area 14 in which the table to be detected is located, and obtains table information from the identified candidate area 14. Therefore, even if the position of the table relative to the drawing area 10 of the drawing data D10, the number of rows and columns of the table, the attributes of each box that makes up the table, and the like differ depending on the drawing data D10, it is possible to obtain the information written in the table included in the drawing data D10 as table information.

[0066] In this case, the drawing processing unit 204A uses a learning model 220 that has already learned the correlation between the drawing data D10 and the candidate area 14, thereby being able to identify the candidate area 14 and obtain table information without performing complex image processing.

[0067] Second Embodiment Fig. 9 is a block diagram showing an example of a drawing processing device 2B according to a second embodiment. Fig. 10 is a functional explanatory diagram showing an example of a learning model generation unit 201B according to the second embodiment. Fig. 11 is a functional explanatory diagram showing an example of a drawing acceptance unit 202, a character recognition unit 203, and a drawing processing unit 204B according to the second embodiment.

[0068] The second embodiment differs from the first embodiment in that the drawing processing device 2B acquires table information using two learning models 220A and 220B. The following describes the drawing processing device 2B according to the second embodiment, focusing on the differences from the first embodiment.

[0069] The trained model storage unit 22 stores a trained first training model 220A and a trained second training model 220B.

[0070] The control unit 20 functions as a transmission / reception control unit 200, a learning model generation unit 201B, a drawing acceptance unit 202, a character recognition unit 203, a drawing processing unit 204B, and a database management unit 205 by executing the information processing program 211B recorded in the data storage unit 21.

[0071] (Learning Model Generation Unit 201B) As shown in FIGS. 9 and 10, the learning model generation unit 201B includes a learning data acquisition unit 2010B and a machine learning unit 2011B.

[0072] The learning data acquisition unit 2010B refers to the drawing database 210 and acquires the first learning data D14 and the second learning data D15.

[0073] The input data constituting the first training data D14 is the drawing data D10. Note that the input data constituting the first training data D14 may include, as the recognition result of the character recognition unit 203, text data indicating the characters written in the drawing area 10 and position data indicating the positions at which the characters are written.

[0074] The output data constituting the first learning data D14 is a table area 15A surrounding a table in the drawing area 10 of the drawing data D10. If the drawing data D10 includes multiple tables, multiple table areas 15A are specified to surround each table. That is, in the drawing data D10 shown in FIG. 2, the table areas 15A correspond to the area surrounding the title block 12 and the area surrounding the parts list 13.

[0075] The input data constituting the second training data D15 is the drawing data D10. Note that the input data constituting the second training data D15 may include, as the recognition result of the character recognition unit 203, text data indicating the characters written in the drawing area 10 and position data indicating the positions at which the characters are written.

[0076] The output data constituting the second learning data D15 is a feature region 15B that surrounds a box of the table to be detected in the drawing region 10 of the drawing data D10. The table to be detected corresponds to the title block 12 and the parts list 13 in the drawing data D10 shown in Fig. 2, but in this embodiment, the description will focus on the case where the table to be detected is the parts list 13. Therefore, in the drawing data D10 shown in Fig. 2, the feature region 15B corresponds to the region surrounding the parts list 13.

[0077] The learning data acquisition unit 2010B performs annotation on the drawing data D10 registered in the drawing database 210, thereby acquiring first learning data D14 and second learning data D15.

[0078] For example, the learning data acquisition unit 2010B acquires the first learning data D14 by displaying the drawing data D10 on the display screen of the drawing processing device 2B or the user terminal device 3, and accepting input operations on the table area 15A as annotations so as to surround the title column 12 and parts list 13 in the drawing area 10 on the display screen.

[0079] In addition, the learning data acquisition unit 2010B displays the drawing data D10 on the display screen of the drawing processing device 2B or the user terminal device 3, and acquires the second learning data D15 by accepting input operations of the feature area 15B as annotations so as to surround the box of the table to be detected in the drawing area 10 on the display screen.

[0080] The machine learning unit 2011B performs machine learning of the first learning model 220A using multiple sets of first learning data D14 acquired by the learning data acquisition unit 2010B. The machine learning unit 2011B also performs machine learning of the second learning model 220B using multiple sets of second learning data D15 acquired by the learning data acquisition unit 2010B.

[0081] (Drawing processing unit 204B) As shown in Figure 11, the drawing processing unit 204B performs a table area identification process that identifies a table area 15A in which a table is located within the drawing area 10 of the new drawing data D10, a feature area identification process that identifies a feature area 15B in which a box belonging to the table to be detected is located within the drawing area 10 of the new drawing data D10, a candidate area identification process that identifies a candidate area 14 based on the table area 15A identified in the table area identification process and the feature area 15B identified in the feature area identification process, and a table information acquisition process that acquires table information related to the table to be detected from the candidate area 14 identified in the candidate area identification process.

[0082] In the table area identification process, the drawing processing unit 204B inputs new drawing data D10 into the first learning model 220A, thereby identifying a table area 15A included in the drawing area 10 of the drawing data D10. That is, in the table area identification process, a table area 15A in which a table is likely to be located is identified in the drawing area 10. Therefore, in the table area identification process, an area in which something that resembles a table is likely to be located is identified as the table area 15A, without identifying the type of table, for example, a title block 12 or a parts list 13.

[0083] As the characteristic region identification process, the drawing processing unit 204B inputs new drawing data D10 into the second learning model 220B, thereby identifying a characteristic region 15B included in the drawing region 10 of the drawing data D10. That is, the characteristic region identification process identifies, within the drawing region 10, a characteristic region 15B in which a box belonging to the table to be detected (in this embodiment, the parts list 13) is likely to be located. Therefore, in the characteristic region identification process, an area that is likely to contain a feature of the table to be detected (e.g., the arrangement or number of boxes) is identified as the characteristic region 15B, without identifying whether a table is located therein.

[0084] In the candidate area identification process, the drawing processing unit 204B identifies, as a candidate area 14, an area where the table area 15A identified in the table area identification process overlaps with the feature area 15B identified in the feature area identification process. That is, an area where the table area 15A identified in the table area identification process as an area where a table-like object is likely to be located overlaps with the feature area 15B identified in the feature area identification process as an area where a feature-like object is likely to be included in the table to be detected is an area where a table-like object is located and a feature-like object is included in the table to be detected. Therefore, in the candidate area identification process, such an area is identified as a candidate area 14 where the table to be detected (in this embodiment, the parts list 13) is located. The drawing processing unit 204B may identify, as a candidate area 14, an area where the table area 15A and the feature area 15B overlap, or may identify, as a candidate area 14, a table area 15 where at least a portion of the table area 15 overlaps with the feature area 15B.

[0085] As part of the table information acquisition process, the drawing processing unit 204B acquires table information based on the characters recognized by the character recognition unit 203 and the characters in the boxes placed in the candidate area 14, and the attributes defined for the boxes.

[0086] (Operation of drawing processing device 2B) Fig. 12 is a flowchart showing an example of the operation (drawing processing method) of drawing processing device 2B according to the second embodiment. Note that, since the steps having the same step numbers as those in the flowchart shown in Fig. 8 are the same as those in the first embodiment, the following description will mainly focus on the parts that are different from the first embodiment.

[0087] First, in step S100 (drawing reception process), the drawing reception unit 202 receives new drawing data D10, and in step S110 (character recognition process), the character recognition unit 203 recognizes the characters contained in the drawing data D10 received in step S100.

[0088] Next, in step S121 (drawing processing step), the drawing processing unit 204B inputs new drawing data D10 into the first learning model 220A, thereby performing a table area identification process to identify the table area 15A included in the drawing area 10 of the drawing data D10.

[0089] Next, in step S122, the drawing processing unit 204B inputs new drawing data D10 into the second learning model 220B, thereby performing a feature region identification process to identify the feature region 15B included in the drawing region 10 of the drawing data D10.

[0090] Next, in step S123, the drawing processing unit 204B performs a candidate area identification process to identify, as a candidate area 14, an area where the table area 15A identified in step S121 and the feature area 15B identified in step S122 overlap.

[0091] Then, in step S130, the drawing processing unit 204B performs a table information acquisition process to acquire table information of the parts table 13 based on the characters in the boxes placed in the candidate area 14 of the parts table 13 from among the characters recognized in step S110 and the attributes defined for the boxes.

[0092] Next, in step S140 (database management step), the database management unit 205 registers the table information acquired as a result of the processing of steps S120 and S130 as supplementary information D12 in the drawing database 210. Then, in step S141, the database management unit 205 transmits display information for displaying the processing results of steps S120 and S130 to the user terminal device 3.

[0093] As described above, according to the drawing processing device 2B and drawing processing method of this embodiment, the drawing processing unit 204B identifies the candidate area 14 in which the table to be detected is located, and obtains table information from the identified candidate area 14. Therefore, even if the position of the table relative to the drawing area 10 of the drawing data D10, the number of rows and columns of the table, the attributes of each box that makes up the table, and the like differ depending on the drawing data D10, it is possible to obtain the information written in the table included in the drawing data D10 as table information.

[0094] In this case, the drawing processing unit 204B uses a first learning model 220A that has learned the correlation between the drawing data D10 and the table area 15A, and a second learning model 220B that has learned the correlation between the drawing data D10 and the feature area 15B, thereby being able to identify the candidate area 14 and obtain table information without performing complex image processing.

[0095] (Other Embodiments) The present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the spirit and scope of the present invention, all of which are included in the technical concept of the present invention.

[0096] In the above embodiment, the drawing processing devices 2A and 2B are described as being configured as a single device, but they may be configured as multiple devices. For example, by distributing the units 200 to 205 of the drawing processing devices 2A and 2B across multiple devices, the drawing management system 1 may be configured, in addition to the drawing processing devices 2A and 2B, with a character recognition device that includes a character recognition unit 203 and performs a character recognition process, and a machine learning device that includes learning model generation units 201A and 201B and performs a machine learning process. In this case, each unit (each process) of each of the above devices may be realized by a program executable on the computer 900.

[0097] In the above embodiment, the drawing processing devices 2A, 2B receive new drawing data D10 from the user terminal device 3 and acquire table information related to tables included in the drawing data D10. Alternatively, the user terminal device 3 may function as the drawing processing devices 2A, 2B.

[0098] In the above embodiment, the drawing processing devices 2A, 2B are described as including the character recognition unit 203 in addition to the drawing processing units 204A, 204B. However, the drawing processing units 204A, 204B may also realize a function of recognizing characters included in the drawing data D10, similar to the character recognition unit 203. For example, the learning models 220, 220A, 220B may include a function of recognizing characters included in the drawing data D10. In this case, the drawing processing units 204A, 204B may input new drawing data D10 into the learning models 220, 220A, 220B to recognize characters included in the drawing data D10.

[0099] 1...Drawing management system, 2A, 2B...Drawing processing device, 3...User terminal device, 10...Drawing area, 11...Shape area, 12...Title block, 13...Bill of materials, 14...Candidate area, 15A...Table area, 15B...Feature area, 20...Control unit, 21...Data storage unit, 22...Learned model storage unit, 23...Communication unit, 24...Input unit, 25...Output unit, 200...Transmission / reception control unit, 201A, 201B...Learning model generation unit, 202...Drawing reception unit, 203...Character recognition unit, 204A, 204B...Drawing processing unit, 205...Database management unit, 210...Drawing database, 211A, 211B...Information processing program, 220...Learning model, 220A...First learning model, 220B...Second learning model

Claims

1. A drawing processing device comprising: a drawing reception unit that receives drawing data in which characters are written in boxes separated by lines and the boxes contain one or more tables in which attributes of the characters are defined; and a drawing processing unit that acquires table information related to the table to be detected from a candidate area in the drawing area of ​​the drawing data received by the drawing reception unit in which the table to be detected, the candidate area having the feature to be detected, is located; wherein the drawing processing unit performs a table area identification process that identifies a table area in the drawing area in which the table is located; a feature area identification process that identifies a feature area in the drawing area in which the box of the table to be detected is located; a candidate area identification process that identifies the candidate area based on the table area identified in the table area identification process and the feature area identified in the feature area identification process; and a table information acquisition process that acquires the table information from the candidate area identified in the candidate area identification process.

2. The drawing processing device of claim 1, wherein the drawing processing unit performs the table area identification process of identifying the table area included in the drawing area of ​​the drawing data by inputting the drawing data into a first learning model, and performs the feature area identification process of identifying the feature area included in the drawing area of ​​the drawing data by inputting the drawing data into a second learning model, the first learning model having learned by machine learning the correlation between the drawing data and the table area surrounding the table included in the drawing data, and the second learning model having learned by machine learning the correlation between the drawing data and the feature area surrounding the box of the table to be detected included in the drawing data.

3. A drawing processing device as described in claim 1 or claim 2, comprising a character recognition unit that recognizes the characters contained in the drawing area, and the drawing processing unit performs the table information acquisition process to acquire the table information based on the characters in the box placed in the candidate area from among the characters recognized by the character recognition unit and the attributes defined for the box.

4. A drawing processing method executed by a computer, comprising: a drawing receiving step of receiving drawing data in which characters are written in boxes separated by ruled lines and the boxes contain one or more tables in which attributes of the characters are defined; and a drawing processing step of acquiring table information related to the table to be detected from a candidate area in the drawing area of ​​the drawing data received by the drawing receiving step in which the table to be detected, which has a feature to be detected, is located, wherein the drawing processing step performs: a table area identification step of identifying a table area in the drawing area in which the table is located; a feature area identification step of identifying a feature area in the drawing area in which the box of the table to be detected is located; a candidate area identification step of identifying the candidate area based on the table area identified in the table area identification step and the feature area identified in the feature area identification step; and a table information acquisition step of acquiring the table information from the candidate area identified in the candidate area identification step.

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