Character recognition method, character recognition system, and program

Abstract

To provide a character recognition method, a character recognition system, and a program for accurately recognizing an irregular character, such as a handwritten character.SOLUTION: A character recognition method for recognizing characters constituting a mark put on an identification target includes: an acquisition step of imaging the mark on the identification target, the mark on the identification target being a character string having a predetermined character string rule, to obtain captured image data; an extraction step of extracting a character region 21 of the mark from the captured image data; a character recognition step of recognizing characters from the extracted character region 21; a first determination step of determining whether the character string composed of the recognized characters satisfies the character string rule registered in advance on a dictionary; and a character correction step of extracting characters that do not satisfy the character string rule, regarding the character string determined to be negative in the first determination step, and correcting the extracted characters so as to satisfy the character string rule.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to a character recognition method, a character recognition system, and a program. [Background technology]

[0002] Traditionally, in the manufacturing industry, in order to identify and manage identification objects such as final products and intermediate products, identification strings such as identification numbers have been assigned to the objects by handwriting, engraving, or printing at the production site. In the steel industry in particular, for example, the identification numbers of the objects were assigned by handwriting to the surfaces of the objects, and the identification numbers assigned to the objects were then visually read and then visually compared against a database in which information about the objects for each identification number was stored. Because this process imposed a heavy workload on operators and could result in identification errors, efforts have been made to develop a system for the process from reading the identification numbers of the objects to comparing the information about the objects.

[0003] For example, Patent Document 1 discloses a method for comparing the notation of each display item on a product label marked on a steel product, which is read and recognized, with product information and manufacturing history information extracted from a database based on the notation of the production number among the notation.

[0004] Patent Document 2 also discloses a slab matching method in which the actual slab number marking location on an actual slab is imaged, the actual slab number is read from the image data, character recognition is performed using a dictionary containing multiple marking fonts, and the determined actual slab number is matched with the slab number in the rolling instruction data for the next process. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2010-61561 A [Patent Document 2] JP 2018-58114 A Summary of the Invention [Problem to be solved by the invention]

[0006] In the steel industry, when materials to be used in the next process are extracted from intermediate products (objects to be identified) in the manufacturing process of steel products, the extraction position may not be consistent. In such cases, it is not possible to apply a mark (identification mark) to identify the object by online spraying or other methods. While there is a method of attaching a label bearing an identification mark to the object to be identified, the label may peel off during the steel product manufacturing process, which means that the identification mark must sometimes be applied by hand directly to the object to be identified.

[0007] The method described in Patent Document 1 has a problem in that, in the case of handwritten characters, which are irregular characters, the identification mark cannot be accurately recognized due to reasons such as uneven character spacing.

[0008] Furthermore, the method described in Patent Document 2 uses a dictionary that incorporates multiple marking fonts, which improves the accuracy of character recognition, but the accuracy of character recognition for handwritten characters may still be insufficient due to reasons such as uneven character spacing.

[0009] The present disclosure has been made in consideration of the above-mentioned problems, and aims to provide a character recognition method, a character recognition system, and a program that can accurately recognize even irregular characters such as handwritten characters. [Means for solving the problem]

[0010] In order to solve the above-mentioned problems, the character recognition method of the present disclosure includes: [1] A character recognition method for recognizing characters constituting a mark attached to an object to be identified, comprising: The indication attached to the object to be identified is a character string having a predetermined character string rule, an acquisition step of acquiring captured image data of an image of the mark attached to the object to be identified; an extraction step of extracting a character region of the display from the captured image data; a character recognition step of recognizing characters in the extracted character region; a first determination step of determining whether a character string composed of recognized characters satisfies the character string rules registered in advance in a dictionary; a character correction step of extracting characters that do not satisfy the character string rules from the character string determined to be unsatisfactory in the first determination step, and correcting the extracted characters so that they satisfy the character string rules; The present invention is characterized by having the following.

[0011] In addition, the character recognition method of the present disclosure includes: [2] In the configuration described in [1] above, it is preferable that the display is an object identification string, and identification object information is associated with each object identification string and stored in a database, and that the configuration further includes a second determination step of comparing a string determined in the first determination step to satisfy the string rule, or a string corrected in the character correction step for a string determined not to satisfy the string rule in the first determination step, with the object identification string stored in the database, and determining whether a matching object identification string exists.

[0012] In addition, the character recognition method of the present disclosure includes: [3] In the configuration described in [2] above, it is preferable to further include a selection step of visually determining the character string determined to be negative in the second determination step and selecting an object identification character string from the database.

[0013] In addition, the character recognition method of the present disclosure includes: [4] In the configuration described in any one of [1] to [3] above, it is preferable that the display is a character string made up of irregular characters.

[0014] In addition, the character recognition method of the present disclosure includes: [5] In the configuration described in any one of [1] to [4] above, it is preferable that the character string rule is a rule that defines a character type for each character number that indicates the order from the beginning of each character that makes up the character string attached to the object to be identified.

[0015] In addition, the character recognition method of the present disclosure includes: [6] In the configuration described in any one of [1] to [5] above, it is preferable that the extraction of the character region is performed by detecting the center position of each character constituting the character string attached to the object to be identified, and the center position between characters.

[0016] In order to solve the above-mentioned problems, the character recognition system of the present disclosure includes: [7] A character recognition system that recognizes characters that constitute a mark attached to an object to be identified, The indication attached to the object to be identified is a character string having a predetermined character string rule, an image acquisition unit that acquires captured image data of an image of the mark attached to the object to be identified; a character area extraction unit that extracts a character area of ​​the display from the captured image data; a character recognition unit that recognizes characters in the extracted character region; a first determination unit that determines whether a character string composed of recognized characters satisfies the character string rule that has been registered in advance; a character correction unit that extracts characters that do not satisfy the character string rules from the character string determined to be unsatisfactory by the first determination unit, and corrects the extracted characters so that they satisfy the character string rules; The present invention is characterized by having the following.

[0017] In addition, the character recognition system of the present disclosure includes: [8] In the configuration described in [7] above, it is preferable that the display is an object identification string, and identification object information is associated with each object identification string and stored in a database, and that the configuration further includes a second determination unit that compares a string determined by the first determination unit to satisfy the string rule, or a string corrected by the character correction unit for a string determined by the first determination unit to not satisfy the string rule, with the object identification string stored in the database, and determines whether a matching object identification string exists.

[0018] In addition, the character recognition system of the present disclosure includes: [9] In the configuration described in [8] above, it is preferable that the configuration further comprises a selection unit that performs a visual judgment on the character string judged as negative by the second judgment unit and selects an object identification character string from a database.

[0019] In addition, the character recognition system of the present disclosure includes:

[10] In the configuration described in any one of [7] to [9] above, it is preferable that the display is a character string made up of irregular characters.

[0020] In addition, the program of the present disclosure

[11] A program for causing a computer to execute a character recognition method for recognizing characters constituting a mark attached to an object to be identified, The indication attached to the object to be identified is a character string having a predetermined character string rule, an acquisition step of acquiring captured image data of an image of the mark attached to the object to be identified; an extraction step of extracting a character region of the display from the captured image data; a character recognition step of recognizing characters in the extracted character region; a first determination step of determining whether a character string composed of recognized characters satisfies the character string rules registered in advance in a dictionary; a character correction step of extracting characters that do not satisfy the character string rule from the character string determined to be negative in the first determination step, and correcting the extracted characters so that they satisfy the character string rule; The program is characterized by executing the above. [Effects of the Invention]

[0021] According to the present disclosure, it is possible to provide a character recognition method, a character recognition system, and a program that can accurately recognize even irregular characters such as handwritten characters. [Brief explanation of the drawings]

[0022] [Figure 1] 1 is a block diagram illustrating a configuration of a character recognition system according to an embodiment of the present disclosure. [Figure 2] 1 is a flowchart illustrating a procedure for implementing a character recognition method according to an embodiment of the present disclosure. [Figure 3] (a) is an example of a marking written on an object to be identified, (b1) is an example of a character region extracted from the marking, (b2) is an example of an inter-character region extracted from the marking, and (c) is an example of an extracted character string region. [Figure 4] 1A is a diagram showing an example of a mark written on an object to be identified, and FIG. 1B is a diagram showing an example of the result of character recognition of the mark. [Figure 5] FIG. 10A is a diagram showing an example of character string rules and character recognition results for each character number, FIG. 10B is an example of correcting the number of characters to conform to the character string rules, and FIG. 10C is an example of correcting the character recognition results by applying a dictionary according to the character string rules. DETAILED DESCRIPTION OF THE INVENTION

[0023] A character recognition system 100 and a character recognition method according to an embodiment of the present disclosure will be described in detail below with reference to FIGS.

[0024] Fig. 1 is a block diagram showing the configuration of a character recognition system 100 according to this embodiment. As shown in Fig. 1, the character recognition system 100 includes an imaging device 30 (image acquisition unit) that captures an image of a mark attached to an object to be identified and acquires captured image data, a character recognition device 10 that recognizes a character string from the acquired captured image data, and a database 40 that stores an object identification character string and information about the object to be identified.

[0025] Character recognition device 10 includes an input unit 11 to which captured image data from imaging device 30 and material information from database 40 are input, an output unit 12 that outputs recognized character string data, etc., and a calculation unit 13 that performs character recognition, etc. The calculation unit 13 includes a character region extraction unit 14, a character recognition unit 15, a first determination unit 16, a character correction unit 17, and a second determination unit 18.

[0026] (imaging device) The imaging device 30 captures an image of the marking attached to the object to be identified and creates captured image data. The imaging device 30 is, for example, a tablet, smartphone, or digital camera with an imaging function, but is not limited to these as long as it is a device with the function of capturing an image of the marking attached to the object to be identified. Furthermore, when capturing an image of the marking on the object to be identified, it is preferable to fix the imaging device 30. Fixing the imaging device 30 reduces camera shake and focus shifts during imaging, thereby improving the quality of the captured image data.

[0027] The marking attached to the object to be identified may be a character string that follows a character string rule. The character string rule here refers to a rule that defines a character type for each character number that indicates the order of each character from the beginning of the character string attached to the object to be identified. The character number indicates the position of the character from the beginning of the character string (in the example of FIG. 4(a), the leftmost character "N"). Character types include, for example, numbers, letters, symbols, etc. The character string is, for example, a character string for identifying the object to be identified, such as an identification object number. The characters that make up the character string may be added by engraving, online spraying, printing, or handwriting, but the present disclosure is particularly suitable for recognizing characters with uneven character spacing or irregular shapes, such as handwritten characters.

[0028] (Input section) The input unit 11 is an input interface of the character recognition device 10, which allows the calculation unit 13 to acquire captured image data from the imaging device 30. In this embodiment, the input unit 11 acquires captured image data obtained by capturing an image of a mark attached to an object to be identified (step S101 in FIG. 2). The captured image data may be in a commonly used image data format such as JPEG, TIFF, or BMP.

[0029] Furthermore, the calculation unit 13 acquires the object identification character string and the identification object information from the database 40 via the input unit 11 .

[0030] 1, the calculation unit 13 is configured to only acquire information from the database 40 through the input unit 11, but the present invention is not limited to this configuration, and the calculation unit 13 may be configured to output and store information in the database 40. The database 40 may be provided in the same personal computer (PC) as the calculation unit 13, etc., or may be provided in an external storage device connected to the PC. The database 40 may also be provided in a storage device connected via a network, such as the cloud.

[0031] (output section) The output unit 12 is an output interface of the character recognition device 10 that outputs the pass / fail judgment made by the first judgment unit 16 and / or the second judgment unit 18 and the character string data at the time of the judgment. The output unit 12 may be an output display of the character recognition device 10, or may be a unit that outputs the pass / fail result and the character string data at the time of the judgment as data to another device or the like.

[0032] (calculation section) The calculation unit 13 performs calculations to identify the markings attached to the object to be identified as character strings. In this embodiment, the calculation unit 13 includes a character region extraction unit 14, a character recognition unit 15, a first determination unit 16, a character correction unit 17, and a second determination unit 18.

[0033] The functions of the calculation unit 13 can be realized as software processing by, for example, executing a predetermined program on a CPU (Central Processing Unit) or a DSP (Digital Signal Processor). However, without being limited to this, the functions of the calculation unit 13 may be configured to be realized as hardware processing by, for example, an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), or an FPGA (Field Programmable Gate Array). The predetermined program may be stored in, for example, a memory unit included in the character recognition device 10 or an external memory device.

[0034] (Character area extraction part) The character area extraction unit 14 extracts character areas 21 of each character constituting the character string in the marking attached to the object to be identified from the captured image data acquired from the imaging device 30 (step S102 in FIG. 2). It is preferable to extract the character areas 21 without preparing a fixed frame, but rather to use a method of detecting by recognizing, for example, the center of the characters and the spaces between the characters. FIG. 3 shows an example of the extraction of the character areas 21.

[0035] FIG. 3(a) shows captured image data acquired from the imaging device 30. The captured image data includes a character string "SG098-02T" handwritten on the object to be identified. In this embodiment, the character string is written in white in the captured image data, making it clearly distinguishable from the black color of the object to be identified. The character region extraction unit 14 of the calculation unit 13 recognizes the center position of a character region 21 and the center position of an inter-character region 22 between characters from the captured image data through image processing. In FIG. 3(b1), the black portion in the center of the approximately circular character region 21 is an area that the character region extraction unit 14 has determined to be highly likely to be the center position of a character. In FIG. 3(b2), the black portion in the center of the approximately circular inter-character region 22 is an area that the character region extraction unit 14 has determined to be highly likely to be the center position of the inter-character region 22. The character area extraction unit 14 extracts the character area 21 of each character by, for example, recognizing the separation position between characters from the center position of the inter-character area 22, and further recognizing the size, shape, etc. of each character. Note that the colors of the character string and the object to be identified are not limited to the above-mentioned combinations, and other color combinations that are easy to distinguish even with a black-and-white camera, such as yellow and red, white and blue, may be used.

[0036] As described above, character region extraction unit 14 recognizes character region 21 in which each character constituting a character string is written by recognizing the center position of a character and the center position between characters. Character region extraction unit 14 further recognizes character string region 23 in which the entire character string is written from recognized character region 21. Figure 3(c) shows an example in which character string region 23 in which the entire character string is written is extracted from character region 21 of each character extracted by character region extraction unit 14. In Figure 3(c), character string region 23 is shown surrounded by a square.

[0037] The operation of character region extraction unit 14 may be performed as part of a process in a program executed by calculation unit 13, or may be performed by another processor, or captured image data may be sent to the cloud to extract character region 21. Open source software such as CRAFT (Character Region Awareness For Text detection) may be applied to extract character region 21. By using the method shown in FIG. 3 for recognizing the center positions of characters and the positions between characters, it is possible to accurately extract character region 21 for each character and recognize the characters, even for irregular characters with uneven spacing between characters or shapes and sizes that are not uniform, such as handwritten characters.

[0038] It is preferable to apply image processing to the image data of the extracted character string region 23 (step S103 in FIG. 2). Any image processing method can be applied, such as white balance adjustment, size adjustment, or noise removal. Image processing may be performed by combining several methods. Image processing may also be applied individually to the character region 21 of each character, or image processing may be performed on the image data before the character region 21 is extracted.

[0039] (character recognition section) The character recognition unit 15 performs character recognition using image data of the character region 21 in the image-processed character string region 23 (step S104 in FIG. 2). Each character that has undergone character recognition is converted into character data, and character string data consisting of the converted characters is created. The function of the character recognition unit 15 may be, for example, optical character recognition (OCR) as part of processing within a program executed by the calculation unit 13, or processing that combines OCR with AI (artificial intelligence) technology. The above processing can also be achieved by sending captured image data to the cloud and using a cloud service. The AI ​​used for character recognition may be configured to create a trained model in advance, using combinations of character images on the object to be identified and correct character recognition results as training data, and have this trained model read the image data of the character region 21 to output the character recognition results.

[0040] The character recognition unit 15 may output a character recognition result from among candidates that match a predetermined character string rule. For example, in the character string rule of the present disclosure, the first and second characters are alphabetic characters. Therefore, when performing character recognition on the first and second characters after extracting the character area 21, the character that is most likely to match the image data of the character area 21 may be selected from among the alphabetic character candidates. This can also be achieved by performing character recognition using a learning model that has been trained using combinations of character images containing only alphabetic characters and correct character recognition results as training data.

[0041] (First judgment unit) The first determination unit 16 determines whether the character string data recognized and created by the character recognition unit 15 satisfies the character string rules registered in advance in a dictionary (step S105 in FIG. 2). In this embodiment, the character string written on the object to be identified has the character string rules that the first, second, and ninth characters are alphabetic characters, the third, fifth, and seventh, eighth characters are numbers, and the sixth character is a hyphen (see the second line in FIG. 5(a)).

[0042] Assume that character region extraction unit 14 extracts character region 21 from the display "NF185-01B" (see FIG. 4(a)) of an object to be identified that has such a character string rule, and character recognition unit 15 recognizes a character string consisting of each character in character region 21 as "NF185-0I81" (see FIG. 4(b)). As shown in FIG. 5(a), the first through seventh characters in the character string recognition result satisfy the predetermined character string rule, whereas the eighth through tenth characters do not satisfy the predetermined character string rule (the recognition results that do not satisfy the character string rule are displayed as white characters on the third line of FIG. 5(a)). When first determination unit 16 determines that the character string recognized by character recognition unit 15 does not satisfy the character string rule (No in step S105 of FIG. 2), it causes character correction unit 17 to perform character correction processing. Furthermore, when the first determination unit 16 determines that the character string recognized by the character recognition unit 15 satisfies the character string rule (Yes in step S105 of FIG. 2), it causes the second determination unit 18 to compare the recognized character string with the database 40 (step S108 of FIG. 2).

[0043] (Character correction department) If the recognized character string does not satisfy the character string rules, character correction unit 17 extracts from the character string data the eighth to tenth characters (shown as outline characters in FIG. 5) that do not satisfy the character string rules (step S106 in FIG. 2). Next, character correction unit 17 corrects the characters extracted in step S106 so that they satisfy the character string rules.

[0044] The character correction unit 17 corrects the number of characters in the character string recognized by the character recognition unit 15 so that the number of characters is equal to the number of characters specified in the predetermined character string rule (step S107 in FIG. 2). In the example shown in FIG. 5, the correction is made by deleting the 10th character in the character string recognition result, which exceeds the number of characters specified in the character string rule (the corrected character string is shown in FIG. 5(b)). However, this is not limited to this example. After associating each character in the character string recognition result with a character string rule so that as many characters as possible in the character string recognition result as satisfy the character string rule, characters to be deleted may be selected from among the characters that do not satisfy the character string rule. Alternatively, the character string recognition result may be directly compared with the object identification character string stored in the database 40, and characters that do not exist in the object identification character string may be deleted. Alternatively, a trained model may be created in advance using the character image on the identification object and the correct recognition result as training data, and the trained model may be configured to read the image data of the character area 21 and delete the recognized character with the lowest probability of being a character.

[0045] Next, the character correction unit 17 applies a dictionary according to the character string rules to the character string whose number of characters has been corrected, and corrects the character string so that it satisfies the predetermined character string rules (step S107 in FIG. 2). The character correction unit 17 can apply, for example, the dictionary listed in Table 1 below.

[0046] [Table 1]

[0047] In Table 1, the "character number" indicates the position of the character from the left in the string of characters recognized from the captured image data. The "conversion target character" and "conversion character" mean that when a "conversion target character" appears in the string of characters recognized from the captured image data, it is converted to the "conversion character" to the adjacent right. Checked boxes in Table 1 indicate that the conversion from the "conversion target character" to the "conversion character" applies only to the character with the checked "character number."

[0048] For example, the third row of Table 1 indicates that if "character to be converted: D" appears in "character number: 9," it is converted to "character after conversion: B." Since "character number: 9" does not use the character "D" in the identification string of the object to be identified in this disclosure, a dictionary is provided that converts "character number: 9" to the character "B," which has a similar external shape to the character "D," when it is recognized as the character "D."

[0049] For "character numbers: 3 to 8" in the third row of Table 1, the character string rule is "number" or "symbol (hyphen)" as shown in FIG. 5(a), so the conversion to "converted character: B" is not applied and is displayed in gray (meaning that the character string rule is not followed). Also, for "character numbers: 1 to 2," the character string rule is "alphabetic" (see FIG. 5(a)), so the conversion to "converted character: B" can be applied according to the character string rule. However, since the character "B" is not used in "character numbers: 1 to 2" in the identification character string of the object to be identified in this disclosure, the conversion from "converted character: D" to "converted character: B" is not applied to "character numbers: 1 to 2." Therefore, in Table 1, it is displayed as a white rectangle with no check mark (meaning that the character string rule is followed but such conversion will not be performed).

[0050] Furthermore, the fifth line of Table 1 indicates that if "character to be converted: i" appears in "character numbers: 3 to 5 and 7 to 8," it is converted to "character after conversion: 1." In the identification string of the object to be identified in this disclosure, "character numbers: 3 to 5 and 7 to 8" must be "numbers" according to the string rules, so a dictionary is provided that converts "character numbers: 3 to 5 and 7 to 8" into the number "1," which has a similar external shape to "i," when it is recognized as "i," which is not a "number."

[0051] It should be understood that Table 1 merely illustrates a portion of a dictionary for correcting characters that do not conform to the character string rules of the present disclosure, and that other characters that should be converted but are not included in Table 1 are also included in this dictionary.

[0052] The character correction unit 17 corrects character numbers 8 and 9 in FIG. 5(a), which do not satisfy the character string rules, using the conversion dictionary in Table 1. Table 1 registers a dictionary that converts "conversion target character: I" to "conversion target character: 1" when it appears in "character numbers 3 to 5, 7 to 8." The character correction unit 17 applies the conversion from "conversion target character: I" to "conversion target character: 1" to "character number: 8." Table 1 also registers a dictionary that converts "conversion target character: 8" to "conversion target character: B" when it appears in "character number: 9." The character correction unit 17 applies the conversion from "conversion target character: 8" to "conversion target character: B" to "character number: 9." FIG. 5(c) shows the character string after conversion using the dictionary in Table 1, and it can be seen that it matches the display on the identification object shown in FIG. 4(a).

[0053] A character string composed of characters corrected by the character correcting unit 17 is judged by the second judging unit 18.

[0054] (Second Judgment Section) The second determination unit 18 compares the character string recognized by the character recognition unit 15 and determined by the first determination unit 16 to satisfy the character string rule or the character string corrected by the character correction unit 17 with the object identification character string registered in the database 40. The second determination unit 18 determines whether the recognized character string or the corrected character string exists as an object identification character string in the database 40 (step S108 in FIG. 2). If an object identification character string corresponding to the character string recognized from the identification object or the corrected character string exists in the database 40 (Yes in step S108), the second determination unit 18 acquires identification object information corresponding to the object identification character string stored in the database 40 and outputs it from the output unit 12. On the other hand, if an object identification character string corresponding to the recognized character string or the corrected character string does not exist in the database 40, it is assumed that a problem occurred in one of the steps when recognizing the character string from the captured image data. Therefore, the calculation unit 13 returns to step S101 and acquires captured image data from the imaging device 30 again. Alternatively, an operator may visually recognize the character string displayed on the object to be identified, and obtain the corresponding object information from the database 40 .

[0055] The object identification string is a unique string set for each object to be identified, and may be an object identification number, or a combination of one or more of numbers, letters, symbols, etc. that indicate the model name of the object to be identified. The object identification information includes, for example, information on the product name, specifications, and dimensions from which the object to be identified was collected, as well as information on the collection date of the object to be identified and the number of objects collected, and is stored in database 40 in association with each object identification string.

[0056] The character recognition system 100 of the present disclosure can simultaneously capture images of labels attached to multiple objects to be identified and recognize the characters. The multiple objects to be identified may be limited to only those having the same object identification character string, or multiple objects to be identified having different object identification character strings may be simultaneously captured.

[0057] As described above, the character recognition method according to this embodiment recognizes characters constituting a marking on an object to be identified. The marking on the object to be identified is a character string having a predetermined character string rule. The method includes: an acquisition step of capturing an image of the marking on the object to be identified and acquiring captured image data; an extraction step of extracting a character region 21 from the captured image data; a character recognition step of recognizing characters in the extracted character region 21; a first determination step of determining whether a character string composed of the recognized characters satisfies a character string rule pre-registered in a dictionary; and a character correction step of extracting characters that do not satisfy the character string rule from a character string determined not to satisfy the character string rule in the first determination step and correcting the extracted characters so that they satisfy the character string rule. By adopting this configuration, character region 21 of each character constituting the character string is extracted from the captured image data of the marking on the object to be identified and character recognition is performed. This enables accurate recognition of even irregular characters, such as handwritten characters. Furthermore, by correcting the character recognition results so that they satisfy the predetermined character string rule, character recognition errors can be efficiently corrected, improving the accuracy of character recognition.

[0058] Furthermore, in this embodiment, the display is an object identification string, and identification object information is associated with each object identification string and stored in database 40, and the system is further configured to include a second determination step of comparing a string determined in the first determination step to satisfy the string rule, or a string corrected in a character correction step for a string determined not to satisfy the string rule in the first determination step, with the object identification string stored in database 40 to determine whether a matching object identification string exists. By employing such a configuration, it is possible to efficiently obtain identification object information associated with the object identification string in database 40 from the recognized object identification string.

[0059] Furthermore, this embodiment is configured to further include a selection step of visually determining the character string determined to be unacceptable in the second determination step and selecting an object identification character string from the database 40. By employing such a configuration, it is possible to quickly obtain identification object information for an exceptional object identification character string that could not be automatically recognized, without having to re-photograph the character string.

[0060] In this embodiment, the marking is configured as a character string consisting of irregular characters. By adopting such a configuration, problems such as peeling off of a label bearing an identification mark when it is affixed to an object to be identified during the manufacturing process of a steel product can be prevented by writing the handwritten characters.

[0061] In this embodiment, the character string rules are configured to define character types for each character number indicating the order from the beginning of each character that makes up the character string attached to the object to be identified. By adopting such a configuration, it is possible to optimize the correction dictionary to be applied for each character number of the recognized character string, thereby improving the accuracy of correcting the recognized character string.

[0062] In this embodiment, extraction of the character region 21 is performed by detecting the center position of each character that constitutes the character string attached to the object to be identified, and the center position of the space between characters. By adopting this configuration, it is possible to recognize the separation positions between characters from the center position of the space between characters 22, and further recognize the size, shape, etc. of each character, thereby accurately extracting the character region 21 of each character.

[0063] Furthermore, this embodiment is a character recognition system 100 that recognizes characters constituting a marking on an object to be identified, the marking on the object to be identified being a character string having a predetermined character string rule, and is configured to include an image acquisition unit that captures an image of the marking on the object to be identified and acquires captured image data, a character area extraction unit 14 that extracts a character area 21 of the marking from the captured image data, a character recognition unit 15 that recognizes characters in the extracted character area 21, a first determination unit 16 that determines whether a character string composed of the recognized characters satisfies a pre-registered character string rule, and a character correction unit 17 that extracts characters that do not satisfy the character string rule from a character string determined as not satisfying the character string rule by the first determination unit 16 and corrects the extracted characters so that they satisfy the character string rule. By adopting such a configuration, character area 21 of each character constituting the character string is extracted from the captured image data of the marking on the object to be identified and character recognition is performed, so that even irregular characters such as handwritten characters can be recognized with high accuracy. Furthermore, by correcting the character recognition results so that they satisfy predetermined character string rules, errors in character recognition can be corrected efficiently, thereby improving the accuracy of character recognition.

[0064] This embodiment also provides a program for causing a computer to execute a character recognition method for recognizing characters constituting a marking on an object to be identified. The program includes the following steps: capturing an image of the marking on the object to be identified and acquiring captured image data; extracting a character region 21 from the captured image data; recognizing characters in the extracted character region 21; determining whether a character string composed of the recognized characters satisfies a character string rule pre-registered in a dictionary; and extracting characters that do not satisfy the character string rule from a character string determined not to satisfy the character string rule in the first determination step and correcting the extracted characters so that they satisfy the character string rule. This configuration allows character recognition to be performed by extracting the character region 21 of each character constituting the character string from the captured image data of the marking on the object to be identified, thereby enabling accurate recognition of even irregular characters such as handwritten characters. Furthermore, correcting the character recognition results to satisfy the predetermined character string rule efficiently corrects character recognition errors, improving the accuracy of character recognition.

[0065] Although the present disclosure has been described based on various drawings and examples, it should be noted that those skilled in the art can easily make various modifications and alterations based on the present disclosure. Therefore, it should be noted that these modifications and alterations are included in the scope of the present invention. For example, the functions included in each component can be rearranged so as not to cause logical inconsistencies, and multiple components can be combined into one or divided. It should be understood that these modifications and alterations are also included in the scope of the present invention.

[0066] For example, in the present embodiment, character recognition system 100 has been described as including imaging device 30 for capturing an image of a mark attached to an object to be identified, but is not limited to this. Character recognition system 100 may not include imaging device 30, but may instead include only an image acquisition unit that acquires captured image data captured outside character recognition system 100. In this case, input unit 11 in FIG. 1 serves as the image acquisition unit. [Explanation of symbols]

[0067] 10 Character recognition device 11 Input section 12 Output section 13 Arithmetic section 14 Character area extraction part 15 Character recognition section 16 First Judgment Section 17 Character correction section 18 Second Judgment Section 21 Character area 22 Inter-character area 23 String area 30 Imaging device (image acquisition unit) 40 databases 100 Character Recognition System

Claims

1. A character recognition method for recognizing characters constituting a mark attached to an object to be identified, comprising: The indication attached to the object to be identified is a character string having a predetermined character string rule, an acquisition step of acquiring captured image data of an image of the mark attached to the object to be identified; an extraction step of extracting a character region of the display from the captured image data; a character recognition step of recognizing characters in the extracted character region; a first determination step of determining whether a character string composed of recognized characters satisfies the character string rules registered in advance in a dictionary; a character correction step of extracting characters that do not satisfy the character string rules from the character string determined to be unsatisfactory in the first determination step, and correcting the extracted characters so that they satisfy the character string rules; and A character recognition method in which the display is a character string composed of characters with an irregular shape.

2. The display is an object identification character string, and identification object information is associated with each object identification character string and stored in a database; 2. The character recognition method according to claim 1, further comprising a second determination step of comparing a character string determined in the first determination step to satisfy the character string rule or a character string corrected in the character correction step for a character string determined in the first determination step to not satisfy the character string rule with object identification character strings stored in the database to determine whether a matching object identification character string exists.

3. 3. The character recognition method according to claim 2, further comprising a selection step of visually determining the character string determined to be unrecognizable in said second determination step and selecting an object-identifying character string from said database.

4. 4. The character recognition method according to claim 1, wherein the character string rule is a rule that defines a character type for each character number that indicates the order from the beginning of each character that constitutes the character string attached to the object to be identified.

5. The character recognition method according to claim 1 , wherein the extraction of the character region is performed by detecting a center position of each character constituting the character string attached to the object to be identified and a center position between characters.

6. A character recognition system that recognizes characters that constitute a mark attached to an object to be identified, The indication attached to the object to be identified is a character string having a predetermined character string rule, an image acquisition unit that acquires captured image data of an image of the mark attached to the object to be identified; a character area extraction unit that extracts a character area of ​​the display from the captured image data; a character recognition unit that recognizes characters in the extracted character region; a first determination unit that determines whether a character string formed from recognized characters satisfies the character string rule that has been registered in advance; a character correction unit that extracts characters that do not satisfy the character string rules from the character string determined to be unsatisfactory by the first determination unit, and corrects the extracted characters so that they satisfy the character string rules; and A character recognition system, wherein the display is a string of characters consisting of irregular characters.

7. The display is an object identification character string, and identification object information is associated with each object identification character string and stored in a database; 7. The character recognition system according to claim 6, further comprising a second determination unit that compares a character string determined by the first determination unit to satisfy the character string rule or a character string corrected by the character correction unit for a character string determined by the first determination unit to not satisfy the character string rule with object identification character strings stored in the database, and determines whether a matching object identification character string exists.

8. 8. The character recognition system according to claim 7, further comprising a selection unit that performs a visual judgment on the character string judged as unsuitable by the second judgment unit and selects an object-identifying character string from a database.

9. A program for causing a computer to execute a character recognition method for recognizing characters constituting a mark attached to an object to be identified, The indication attached to the object to be identified is a character string having a predetermined character string rule, an acquisition step of acquiring captured image data of an image of the mark attached to the object to be identified; an extraction step of extracting a character region of the display from the captured image data; a character recognition step of recognizing characters in the extracted character region; a first determination step of determining whether a character string composed of recognized characters satisfies the character string rules registered in advance in a dictionary; a character correction step of extracting characters that do not satisfy the character string rule from the character string determined to be negative in the first determination step, and correcting the extracted characters so that they satisfy the character string rule; Execute The display is a string of characters consisting of irregular characters.

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