JP7348446B2 - Method and system for providing handwritten font generation service - Google Patents

Description

The following description relates to techniques for providing font generation services.

A font is a type of character library in which pre-designed characters of various styles and sizes are stored, and includes all letters, numbers, and special symbols necessary for typesetting.

In order for such fonts to be displayed or printed through a computer, the form of the characters must be expressed as data of 0's and 1's. If a font can be expressed as digital data consisting of 0's and 1's, a computer can store and process this data and output it from an external output device. Therefore, a font can be said to be a collection of character shape data expressed in digital form.

For example, Patent Document 1 (registration date: September 5, 2017) discloses a font generation technology that allows various style changes to be used on a character-by-character basis in real time without placement work.

Korean Registered Patent No. 10-1777521

To provide a service model that can generate a font file with handwritten characters written by a user.

Provides a custom tuning function that allows users to inspect font generation results.

A handwritten font generation method performed by a computer device, the computer device including at least one processor configured to execute computer readable instructions contained in a memory, the handwritten font generation method comprising: at least one processor preprocessing a handwritten character image including a user's handwritten characters into an image file in a learnable format; A handwritten font generation method is provided, comprising: learning a font style to generate a handwritten font; and the at least one processor post-processing a size ratio of the handwritten font.

According to one aspect, the preprocessing step includes providing a template including a given character set, receiving as an input image a template in which the character set is created with handwritten characters, and converting the input image into characters. The method may include the step of dividing each character image into units and processing each character image into an image file in a learnable format.

According to another aspect, the step of preprocessing may include the step of generating, as learning data, an image pair consisting of an image of a given character and a handwritten character image for the given character.

According to another aspect, in the handwritten font generation method, the at least one processor generates a preprocessing result of the preprocessing step, a font generation result of the generating step, and a postprocessing result of the postprocessing step. The method may further include providing a user inspection interface for the user to inspect at least one of the items.

According to another aspect, the handwritten font generation method further includes the step of the at least one processor providing a preprocessing inspection interface for the user to inspect the preprocessing result of the preprocessing step. The pre-processing acceptance inspection interface may include a function for checking characters for which pre-processing has been completed on a character-by-character basis, and a function for correcting handwritten characters on a character-by-character basis.

According to another aspect, the handwritten font generation method further includes the step of the at least one processor providing a font acceptance inspection interface for the user to inspect the font generation result of the generation step, The font acceptance inspection interface includes a function for checking the font generation result, and a function for replacing the font generation result character by character with the generation result of another model or re-inputting handwritten characters. good.

According to another aspect, the font acceptance inspection interface includes, as a function for confirming the font generation result, a function of providing a font generation result of a default model among the plurality of models; The function may include any one of a function of providing a font generation result of a model with the highest quality score, and a function of providing a font generation result of a combination of models with the highest quality score for each character.

According to another aspect, the handwritten font generation method further includes the step of the at least one processor providing a post-processing inspection interface for the user to inspect the post-processing result of the post-processing step. The post-processing acceptance inspection interface may include a function for checking fonts for which post-processing has been completed, and a function for adjusting a character size ratio in a text of the handwritten font.

According to another aspect, the post-processing acceptance inspection interface may include a function for adjusting the handwritten font to a font size determined by a preset or a custom setting of the user.

According to another aspect, the handwritten font generation method further includes the step of packaging the post-processed font and registering it as a file in a font format applicable to web content or documents. may be included.

A computer program for causing the computer device to execute the handwritten font generation method is provided.

A computing device including at least one processor configured to execute computer-readable instructions contained in a memory, the at least one processor generating a handwriting image including handwriting of a user. The present invention is characterized by pre-processing an image file in a learnable format, using the image file to learn the font style of the handwritten characters to generate a handwritten font, and post-processing the size ratio of the handwritten font. Provide computer equipment for

According to an embodiment of the present invention, by providing a service model that generates a font file using handwritten characters written by a user, a user can freely design a font file to be applied to web content or documents in his or her own style. be able to.

According to the embodiments of the present invention, by providing a custom tuning function that allows the user to inspect the font generation results, it is possible to reflect the style desired by the user more conveniently.

According to embodiments of the present invention, service efficiency for handwritten font generation can be improved by providing a service environment in which users can evaluate, generate, and adjust the necessary information in the font generation process. Communication can be reduced.

1 is a diagram illustrating an example of a network environment in an embodiment of the present invention. FIG. 1 is a block diagram illustrating an example of a computer device in an embodiment of the present invention. FIG. 1 is a flowchart illustrating an example of a method that may be performed by a computing device in an embodiment of the invention. 7 is a flowchart illustrating a user acceptance process for custom tuning of handwritten fonts according to an embodiment of the present invention. FIG. 3 is a diagram showing an example of a user interface screen for explaining a handwritten font generation service in an embodiment of the present invention. FIG. 3 is a diagram showing an example of a user interface screen for explaining a handwritten font generation service in an embodiment of the present invention. FIG. 3 is a diagram showing an example of a user interface screen for explaining a handwritten font generation service in an embodiment of the present invention. FIG. 3 is a diagram showing an example of a user interface screen for explaining a handwritten font generation service in an embodiment of the present invention. FIG. 3 is a diagram showing an example of a user interface screen for explaining a handwritten font generation service in an embodiment of the present invention. FIG. 3 is a diagram showing an example of a user interface screen for explaining a handwritten font generation service in an embodiment of the present invention. FIG. 3 is a diagram showing an example of a user interface screen for explaining a handwritten font generation service in an embodiment of the present invention. FIG. 3 is a diagram showing an example of a user interface screen for explaining a handwritten font generation service in an embodiment of the present invention. FIG. 3 is a diagram showing an example of a user interface screen for explaining a handwritten font generation service in an embodiment of the present invention. FIG. 3 is a diagram showing an example of a user interface screen for explaining a handwritten font generation service in an embodiment of the present invention. FIG. 3 is a diagram showing an example of a user interface screen for explaining a handwritten font generation service in an embodiment of the present invention.

Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

Embodiments of the present invention relate to techniques for providing font generation services. The handwritten font generation system according to the embodiment of the present invention may be realized by at least one computer device, and the handwritten font generation method according to the embodiment of the present invention may be realized by at least one computer device included in the handwritten font generation system. May be executed. At this time, the computer program according to the embodiment of the present invention may be installed and executed in the computer device, and the computer device generates the handwritten font according to the embodiment of the present invention under the control of the executed computer program. You may carry out the method. The above-described computer program may be recorded on a computer-readable recording medium in order to be coupled to a computer device and cause the computer to execute the handwritten font generation method.

FIG. 1 is a diagram showing an example of a network environment in an embodiment of the present invention. The network environment of FIG. 1 shows an example including a plurality of electronic devices 110, 120, 130, 140, servers 150, 160, and a network 170. Such FIG. 1 is only an example for explaining the invention, and the number of electronic devices and the number of servers are not limited as shown in FIG. 1. Further, the network environment in FIG. 1 is only an example for explaining an environment applicable to this embodiment, and the environment applicable to this embodiment is not limited to the network environment in FIG. 1.

The plurality of electronic devices 110, 120, 130, and 140 may be fixed terminals or mobile terminals realized by computer devices. Examples of the plurality of electronic devices 110, 120, 130, and 140 include smartphones, mobile phones, navigation systems, PCs (personal computers), notebook PCs, digital broadcasting terminals, PDAs (personal digital assistants), and PMPs (portable multimedia platforms). ayer ), tablets, game consoles, wearable devices, IoT (Internet of Things) devices, VR (Virtual Reality) devices, AR (Augmented Reality) devices, etc. As an example, although FIG. 1 shows a smartphone as an example of the electronic device 110, in the embodiment of the present invention, the electronic device 110 may utilize a substantially wireless or wired communication method to communicate with others via the network 170. electronic devices 120, 130, 140 and/or servers 150, 160.

The communication method is not limited, and is not limited to communication methods that utilize communication networks that can be included in the network 170 (for example, mobile communication networks, wired Internet, wireless Internet, and broadcasting networks), as well as communication methods that utilize short distances between devices. Wireless communications may also be included. For example, the network 170 is a PAN (personal area network), a LAN (local area network), a CAN (campus area network), a MAN (metropolitan area network), or a WAN (wide area network). e area network), BBN (broadband network), the Internet, etc. may include any one or more of the networks. Additionally, network 170 may include any one or more of network topologies including, but not limited to, a bus network, a star network, a ring network, a mesh network, a star-bus network, a tree or a hierarchical network, and the like. It will not be done.

Each server 150, 160 is implemented by one or more computing devices that communicate with a plurality of electronic devices 110, 120, 130, 140 via a network 170 to provide instructions, code, files, content, services, etc. good. For example, the server 150 provides services (for example, a handwritten font generation service, a webtoon service, a video sharing service, a social network service, etc.) to a plurality of electronic devices 110, 120, 130, and 140 connected via the network 170. It may be a system that

FIG. 2 is a block diagram illustrating an example of a computer device in an embodiment of the present invention. Each of the plurality of electronic devices 110, 120, 130, and 140 and each of the servers 150 and 160 described above may be realized by a computer device 200 configured as shown in FIG.

Such a computing device 200 may include a memory 210, a processor 220, a communication interface 230, and an input/output interface 240, as shown in FIG. Memory 210 is a computer readable storage medium and may include permanent mass storage devices such as random access memory (RAM), read only memory (ROM), and disk drives. Here, a permanent large capacity storage device such as a ROM or a disk drive may be included in the computer device 200 as a separate permanent storage device separate from the memory 210. Additionally, an operating system and at least one program code may be recorded in the memory 210. Such software components may be loaded into memory 210 from a computer-readable storage medium separate from memory 210. Such other computer-readable recording media may include computer-readable recording media such as floppy drives, disks, tapes, DVD/CD-ROM drives, memory cards, and the like. In other embodiments, software components may be loaded into memory 210 through communication interface 230 that is not a computer-readable storage medium. For example, software components may be loaded into memory 210 of computing device 200 based on a computer program installed by a file received over network 170.

Processor 220 may be configured to process instructions of a computer program by performing basic arithmetic, logic, and input/output operations. Instructions may be provided to processor 220 by memory 210 or communication interface 230. For example, processor 220 may be configured to execute instructions received according to program code recorded on a storage device, such as memory 210.

The communication interface 230 may provide functionality for the computing device 200 to communicate with other devices (eg, the recording device described above) via the network 170. As an example, requests, instructions, data, files, etc. generated by the processor 220 of the computer device 200 according to a program code recorded in a storage device such as the memory 210 may be transmitted to others via the network 170 under the control of the communication interface 230. may be transmitted to the device. Conversely, signals, instructions, data, files, etc. from other devices may be received by the computing device 200 via the network 170 and through the communication interface 230 of the computing device 200 . Signals, instructions, data, etc. received through communication interface 230 may be communicated to processor 220 and memory 210, files, etc. may be transferred to a storage medium (such as a persistent storage device as described above) that computing device 200 may further include. May be recorded.

Input/output interface 240 may be a means for interfacing with input/output device 250. For example, input devices may include devices such as a microphone, keyboard, and mouse, and output devices may include devices such as a display and speakers. As another example, input/output interface 240 may be a means for interfacing with a device that has integrated input and output functionality, such as a touch screen. Input/output device 250 may be configured as one device with computer device 200.

Also, in other embodiments, computing device 200 may include fewer or more components than those of FIG. However, most prior art components need not be clearly illustrated. For example, computer system 200 may be implemented to include at least some of the input/output devices 250 described above, and may further include other components such as transceivers, databases, and the like.

Specific embodiments of a method and system for providing a handwritten font generation service will be described below.

FIG. 3 is a flowchart illustrating an example of a method that may be performed by a computing device in one embodiment of the invention.

The computer device 200 according to this embodiment may provide a handwritten font generation service to a client by connecting to a dedicated application installed on the client or a web/mobile site associated with the computer device 200. The computer device 200 may be configured with a computer-implemented handwritten font generation system. As an example, the handwritten font generation system may be realized in the form of a program that operates independently, or may be configured in the form of an in-app of a specific application and can operate on the specific application. It may be realized as follows.

The processor 220 of the computer device 200 may include at least one component for executing the handwritten font generation method according to FIG. 3. Depending on the embodiment, components of processor 220 may be selectively included or excluded from processor 220. Also, depending on the embodiment, components of processor 220 may be separated or combined to express the functionality of processor 220.

Such processor 220 and components of processor 220 may control computing device 200 to perform steps 310-330 included in the handwritten font generation method of FIG. For example, processor 220 and components of processor 220 may be implemented to execute instructions in accordance with operating system code and at least one program code contained in memory 210.

Here, the components of processor 220 may be representations of different functions that are performed by processor 220 according to instructions provided by program code recorded on computer device 200.

Processor 220 may read the necessary instructions from memory 210 loaded with instructions related to controlling computing device 200 . In this case, the read instructions may include instructions for controlling the processor 220 to perform steps 310-330 described below.

The steps 310-330 described below may be performed in a different order than shown in FIG. 3, and some of the steps 310-330 may be omitted or additional steps may be included. It's okay.

The processor 220 provides a service model that generates a font file using handwritten characters written by the user, for users who have font generation authority. In particular, the processor 220 provides a custom tuning function that allows the user to check and inspect intermediate results at each stage of generating a handwritten font.

Referring to FIG. 3, at step 310, processor 220 may preprocess the handwritten image into a learnable form of the image. The processor 220 receives a handwritten character image created by a user as a user input, processes the received handwritten character image into a file in an image format (e.g., pdf, png, jpeg, heif, etc.) that can be learned by the model. good. As an example, the processor 220 provides a template that allows the user to create handwritten characters for a given target character set, and inputs the template in which the handwritten characters are created for each target character. It may be received as an image. Thereafter, the processor 220 recognizes the aruco code of the template image received as an input image, separates it into characters, and processes each character image into an image file in a learnable format. A learning pair consisting of one target character image and one handwritten character image may be generated for each character.

The processor 220 may provide a pre-processing inspection interface for inspecting the pre-processing results for the handwritten character image. The user may check the preprocessed characters using the preprocessing acceptance inspection interface, and at this time, the preprocessing acceptance inspection interface may include a function for correcting handwritten characters on a character by character basis. In other words, the processor 220 may perform user acceptance of the image before preprocessing the handwritten character image and converting it into a font. The processor 220 may additionally generate templates by the user selecting error characters such as incorrectly preprocessed characters or preprocessing omissions, preprocess only the error characters again with the additional template, and You may update the learning pair for the corresponding letter.

At step 320, processor 220 may generate a fontized handwritten font by learning the font style of the user's handwriting using the preprocessed image at step 310. Processor 220 may learn handwriting styles based on the handwriting generation model using training pairs consisting of target character images and handwritten character images for each character. The processor 220 may use the target character image and the handwritten character image to learn so that the handwritten character style without error characters is stably reflected in the characters. For example, the processor 220 may learn handwritten character styles using a GAN (Generative Adversarial Network) model that includes a generator and a discriminator. The processor 220 may utilize, as one of the GAN models, a pix2pix model that learns a loss function necessary for mapping an input image and an output image. Processor 220 may learn handwriting styles for the target character set and generate a character library of the appropriate style (including all letters, numbers, and special symbols needed for typesetting). At this time, the processor 220 may generate a plurality of handwritten font candidates using a plurality of models for one handwritten character image.

The processor 220 may provide a font acceptance interface for inspecting the font generation result by handwritten fontization. The user may check the handwritten font candidates that are the font generation results using the font acceptance interface, and at this time, the font acceptance interface displays the handwritten font candidates generated based on multiple models and creates the final model. may include a function that allows selection of the Processor 220 may display multiple models and multiple stages of font generation results in parallel to provide a user-selectable interface. At the font acceptance inspection stage, acceptance inspection may be performed at the character level without considering the balance within the text or the height of the characters. In addition to inspecting the font generation results for the default character set, it is also possible to individually list and inspect the main characters depending on the service scenario. The processor 220 may display the handwritten character generation models in order of the quality scores of the font generation results using the font acceptance interface, and display the basic settings with the character of the model with the highest quality score automatically selected for each character. good. The processor 220 may suggest an optimal model to the user through a font acceptance interface, and provides an acceptance environment for selecting generation results of other models on a character-by-character basis. The font acceptance interface includes a feature that allows a user to recreate a handwritten character for a particular character if there is no appropriately generated handwritten font candidate for that character. The handwritten characters of the characters re-created during the font acceptance stage may be included in the final font for user acceptance by a method in which they are immediately replaced without any learning. The processor 220 can also sample a portion of the font generation results based on the quality score and utilize this as a learning sample for the handwritten character generation model.

In step 330, the processor 220 may post-process the font generation result that is finally selected through user acceptance. In other words, the processor 220 may post-process the handwritten font size ratios, ie, ratio balancing within the text. The processor 220 may adjust the proportion of the size of each character using baseline alignment, upper limit of character enlargement, lower limit of character enlargement, specific character reduction, etc. for proportion balancing in the text.

The processor 220 may provide a post-processing acceptance interface for inspecting post-processing results for the font generation results. The user may check the characters for which post-processing has been completed using the post-processing acceptance inspection interface. It includes a function to adjust basic alignment such as font and center alignment, and a function to display the processing result after adjusting the font size to a preset or user's custom setting. That is, the processor 220 may perform user acceptance at the text-font level as a post-processing result for the font generation result.

The processor 220 may package the post-processed font and register it as a font file that can actually be applied to web content, documents, and the like. The processor 220 may provide the post-processing result in a font format such as a true type font (TTF) or an open type font (OTF). Processor 220 may provide at least one font format for handwritten fonts and may provide an interface that allows a user to select a font format.

Processor 220 may provide a font modification interface that allows modification at the font level. For example, an SVG (vector file) existing in TTF may be loaded from the web, modified, and then updated to TTF again.

In summary, referring to FIG. 4, the processor 220 includes an image preprocessing step S310 of receiving user handwritten characters in an image file and generating learning data, and learning a handwritten character style based on the preprocessed image file. A font generation process S320 for generating a handwritten font and a font post-processing process S330 for post-processing the handwritten font are executed. In particular, processor 220 provides an interface that allows the user to inspect intermediate results of each step as a custom tuning function for handwritten fonts. In other words, the processor 220 uses a preprocessing acceptance interface for inspecting the preprocessing results in the image preprocessing step S310, a font acceptance inspection interface for inspecting the font generation results in the font generation step S320, and a font postprocessing interface. In step S330, a post-processing acceptance inspection interface may be provided for inspecting the post-processing results. In some embodiments, depending on the acceptance inspection target, a part of the pre-processing acceptance inspection interface, the font acceptance inspection interface, and the post-processing acceptance inspection interface, for example, only for post-processing acceptance inspection, the service manager may It is also possible to provide it in a participating form.

5 to 15 are diagrams showing examples of user interface screens for explaining the handwritten font generation service in one embodiment of the present invention.

FIG. 5 shows an example of a dashboard screen 510 of the handwritten font generation service.

Dashboard screen 510 includes a generate button 501 for generating a handwritten font. Depending on the user's authority, it may be possible to generate only one handwritten font, or a plurality of handwritten fonts. In the process of requesting generation of a handwritten font using the generation button 501, a popup may be displayed to select whether to allow others to use the user's handwritten font.

Dashboard screen 510 may include a user-generated handwritten font list 502. The handwritten font list 502 may include a font list that is being generated, a font list that has been generated, and the like, and may be displayed in the order of updates. A font card indicating each handwritten font included in the handwritten font list 502 includes the font name, updated date, current status (e.g., generation completed, preprocessing, generation, postprocessing), and whether generation has been completed. In the case of fonts, a font file download button, etc. may be included.

When the user inputs the generate button 501 on the dashboard screen 510, the processor 220 provides a handwritten character image input screen 620, as shown in FIG.

The handwritten character image input screen 620 may include a template download button 601 for downloading a template for writing handwritten characters, an image input button 602 for uploading a handwritten character image created in the template, and the like. The handwritten character template is a format that includes a target character set, and may be provided as a PDF file, a JPG file, or the like. The user downloads the template by inputting a template download button 601 on the handwritten character image input screen 620, and then prints the template to create handwritten characters in his or her own style using the target character set given to the template. Thereafter, the user inputs an image input button 602 on the handwritten character image input screen 620, scans or photographs the template in which the handwritten characters are created, and uploads the template in the form of an image.

When the preprocessing of the handwritten character image uploaded by the user is completed, the processor 220 provides a preprocessing acceptance screen 730 as shown in FIG. 7 . The pre-processing acceptance inspection screen 730 is a pre-processing acceptance inspection interface for allowing the user to confirm the characters for which pre-processing has been completed. Results 702 may be displayed. When the user selects a character that has not been properly preprocessed using the check box 703 on the preprocessing acceptance inspection screen 730 and then inputs the improvement button 704, the processor 220 displays a screen for rewriting and inputting the character ( (handwritten character re-creation screen). The handwritten character re-creation screen provides a template for re-creating characters that have not been properly preprocessed.

When the user inputs the acceptance inspection completion button 705 on the preprocessing acceptance inspection screen 730, the processor 220 provides a handwritten font generation screen 840, as shown in FIG. The handwritten font generation screen 840 displays the current status of handwritten font generation (for example, generation in progress or generation complete).

When the generation of the handwritten font is completed, the processor 220 provides a font acceptance screen 950 as shown in FIG. 9 . In the font acceptance process, the user inspects a character set that reflects the user's handwriting style (including letters, numbers, special symbols, etc. required for typesetting), and in the case of characters that were not properly generated in the font. corresponds to a scenario where the final font is determined by replacing characters with characters generated by other models or by re-creating the characters. As an example, the processor 220 may display the font generation result 901 of the optimal model with the highest quality score among the plurality of models on the font acceptance screen. The processor 220 can also display the font generation result of the default model among the plurality of models. If a specific character 902 is selected from the font generation results 901 of the optimal model, the processor 220 may provide font generation results 1001 for each model for the specific character 902, as shown in FIG. After checking the font generation results 1001 of each model, the user may replace specific characters 902 with the font generation results of other models and include them in the final font. In addition to determining the final font using the generation results of other models, when inputting the improvement button 903 after selecting at least one character from the font generation results 901 in FIG. As shown, a character improvement screen 1101 may be provided for rewriting handwritten characters of the selected character and reflecting them in the final font. The user may use the character improvement screen 1101 to rewrite the handwritten character of the character selected from the optimal model font generation result 901 and reflect it in the final font.

As another example, when the generation of the handwritten font is completed, the processor 220 automatically selects the font of the model with the highest quality score for each character as the final font based on the combination of models on the font acceptance screen 950 as shown in FIG. Selected font generation results 1201 may be provided. The user may check the font generation result 1201, which is a combination of quality score-based models, from the font acceptance screen 950, and may also replace specific characters with the generation results of other models and include them in the final font.

As shown in FIG. 13, the processor 220 may provide a final font result 1301 that reflects the user's acceptance details (model selection, character improvement, etc.) during the acceptance inspection process using the font acceptance inspection screen 950. The user may check the final font result 1301 that the user has inspected for the font generated with his or her own handwritten characters.

When the user inputs the acceptance inspection completion button 1304 after confirming the final font result 1301 from the font acceptance inspection screen 950 of FIG. 13, the processor 220 provides a post-processing acceptance inspection screen 1460 as shown in FIG. The post-processing acceptance inspection screen 1460 is an interface for post-processing acceptance so that the user can check the characters that have been post-processed, and displays the post-processing results 1401 in which the size ratio has been adjusted for each character in the text. You may do so.

The post-processing acceptance inspection screen 1460 may include a function 1402 to make specific specified characters particularly small, a function 1403 to select basic alignment (bottom alignment, center alignment, etc.), A post-processing result 1401 that is a font sample generated for each character size determined by the user's custom settings may be displayed.

When the user inputs the acceptance inspection completion button 1404 after confirming the post-processing result 1401 from the post-processing acceptance inspection screen 1460, the processor 220 packages the final font for which post-processing has been completed and actually uses it in web content, documents, etc. You may register with a font file that is applicable to .

FIG. 15 shows an example of a demo page screen 1570 of the handwritten font generation service.

The demo page screen 1570 is a web demo screen to which the user's handwritten font can be applied, and includes a font list 1501 generated from the user's handwritten characters, a character input field 1502 for inputting characters to be tested, A test result screen 1503 for providing a test result obtained by applying a font selected from a font list 1501 to characters input in a character input field 1502 may be included. The user can use the demo page screen 510 to actually try using a font created with his or her own handwritten characters in a text or the like.

As described above, according to embodiments of the present invention, by providing a service model that generates font files using handwritten characters written by users, users can freely create font files in their own style that can be applied to web content or documents. can be designed. In particular, according to embodiments of the present invention, by providing a custom tuning function that allows the user to inspect intermediate results during the font generation process, the style desired by the user can be reflected more conveniently. . Therefore, the present embodiment can improve service efficiency for handwritten font generation by providing a service environment in which users can evaluate, generate, and adjust themselves, which is necessary in the font generation process. Communication can be reduced.

The apparatus described above may be realized by hardware components, software components, and/or a combination of hardware and software components. For example, the devices and components described in the embodiments include a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU), a microprocessor, or may be implemented using one or more general purpose or special purpose computers, such as various devices capable of executing and responding to instructions. A processing device may execute an operating system (OS) and one or more software applications that execute on the OS. The processing device may also be responsive to execution of the software to access, record, manipulate, process, and generate data. Although for convenience of understanding, one processing device may be described as being used, those skilled in the art will appreciate that a processing device may include multiple processing elements and/or multiple types of processing elements. You will understand. For example, a processing device may include multiple processors or a processor and a controller. Other processing configurations are also possible, such as parallel processors.

Software may include computer programs, code, instructions, or a combination of one or more of these that configure a processing device or instruct a processing device, independently or collectively, to perform operations as desired. You may do so. The software and/or data may be embodied in a machine, component, physical device, computer storage medium or device of any kind for being interpreted by or providing instructions or data to a processing device. good. The software may be distributed on computer systems connected by a network, and may be recorded or executed in a distributed manner. The software and data may be recorded on one or more computer readable storage media.

Methods according to embodiments may be implemented in the form of program instructions executable by various computer means and recorded on computer-readable media. Here, the medium may be one that continuously records a computer-executable program, or one that temporarily records it for execution or download. Also, the medium may be a variety of recording or storage means in the form of a single or multiple hardware combinations, and is not limited to a medium directly connected to a computer system, but may be distributed over a network. It may also exist. Examples of media include magnetic media such as hard disks, floppy disks, and magnetic tape, optical media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, It may also include ROM, RAM, flash memory, etc., and may be configured to record program instructions. Further, other examples of the medium include an application store that distributes applications, a site that supplies or distributes various other software, and a recording medium or storage medium managed by a server.

As mentioned above, although the embodiments have been described based on limited embodiments and drawings, those skilled in the art will be able to make various modifications and variations based on the above description. For example, the techniques described may be performed in a different order than in the manner described, and/or components of the systems, structures, devices, circuits, etc. described may be performed in a different form than in the manner described. Even when combined or combined, opposed or replaced by other components or equivalents, suitable results can be achieved.

Therefore, even if the embodiments are different, if they are equivalent to the scope of the claims, they fall within the scope of the appended claims.

200: Computer device 210: Memory 220: Processor 230: Communication interface 240: Input/output interface 250: Input/output device 170: Network

Claims (18)

A handwritten font generation method executed by a computer device, the method comprising:
The computer device includes at least one processor configured to execute computer-readable instructions contained in memory;
The handwritten font generation method includes:
the at least one processor preprocessing a handwritten image containing the user's handwritten characters into an image file in a learnable format;
the at least one processor learning a font style of the handwritten characters using the image file to generate a handwritten font;
the at least one processor post-processing the handwritten font size ratio ; and
a step in which the at least one processor provides a font acceptance inspection interface for the user to inspect the font generation result of the generating step;
including ;
The font acceptance inspection interface has a function to confirm the font generation results, including a function to provide the font generation results of the default model among the plurality of models, and a function to provide the font generation results of the default model among the plurality of models. A function that provides a font generation result, a function that provides a font generation result of a combination of models with the highest quality score for each character,
How to generate handwritten fonts. The pretreatment step includes:
providing a template containing a given character set;
2. The method of claim 1, further comprising the steps of: receiving a template in which the character set is made up of handwritten characters as an input image; and dividing the input image into characters and processing each character image into an image file in a learnable format. Handwritten font generation method described in. The pretreatment step includes:
2. The handwritten font generation method according to claim 1, further comprising the step of generating, as learning data, an image pair consisting of an image of a given character and a handwritten character image for the given character. The handwritten font generation method includes:
The at least one processor provides a user acceptance interface for the user to inspect at least one of the preprocessing results of the preprocessing step and the postprocessing results of the postprocessing step. The handwritten font generation method according to any one of claims 1 to 3, further comprising the step of providing. The handwritten font generation method includes:
The at least one processor further includes a step of providing a preprocessing inspection interface for the user to inspect the preprocessing result of the preprocessing step,
Claims 1 to 3, wherein the pre-processing acceptance inspection interface includes a function for confirming characters for which pre-processing has been completed on a character-by-character basis, and a function for correcting handwritten characters on a character-by-character basis. The handwritten font generation method according to any one of the above. The font acceptance inspection interface includes a function for replacing the font generation result with the generation result of another model character by character and for re-entering handwritten characters. 3. The handwritten font generation method according to any one of 3. The handwritten font generation method includes:
The at least one processor further comprises: providing a post-processing inspection interface for the user to inspect the post-processing results of the post-processing step;
A claim characterized in that the post-processing acceptance inspection interface includes a function for confirming fonts for which post-processing has been completed and a function for adjusting a character size ratio within a text of the handwritten font. The handwritten font generation method according to any one of items 1 to 3. 8. The post-processing acceptance inspection interface includes a function for adjusting the handwritten font to a font size determined by a preset or a custom setting of the user. How to generate handwritten fonts. The handwritten font generation method includes:
Any one of claims 1 to 8 , wherein the at least one processor further comprises: packaging the post-processed font and registering it in a file in a font format applicable to the web content or document. Handwritten font generation method described in. A computer program for causing the computer device to execute the handwritten font generation method according to any one of claims 1 to 9 . A computer device,
at least one processor configured to execute computer-readable instructions contained in the memory;
The at least one processor includes:
A handwritten character image containing the user's handwritten characters is preprocessed into an image file in a learnable format,
learning a font style of the handwritten characters using the image file to generate a handwritten font;
post-processing the size ratio of the handwritten font ;
providing a font acceptance inspection interface for the user to inspect the generated font generation result;
The font acceptance inspection interface has a function to confirm the font generation results, including a function to provide the font generation results of the default model among the plurality of models, and a function to provide the font generation results of the default model among the plurality of models. Contains one of the following: a function that provides font generation results, and a function that provides font generation results of the combination of models with the highest quality score for each character.
A computer device characterized by: The at least one processor includes:
provides a template containing a given character set,
receiving a template in which the character set is created with handwritten characters as an input image;
12. The computer device according to claim 11 , wherein the input image is divided into characters, and each character image is processed into an image file in a learnable format. The at least one processor includes:
The computer device according to claim 11 , wherein an image pair consisting of an image of a given character and a handwritten character image for the given character is generated as learning data. The at least one processor includes:
Claim 11 , further comprising: further providing a user acceptance inspection interface for the user to inspect at least one of the pre- processing result of the pre-processing and the post- processing result of the post-processing. 14. The computer device according to any one of items 1 to 13 . The at least one processor includes:
providing a pre-processing acceptance inspection interface for the user to inspect the pre- processed pre-processing results;
Claims 11 to 13 , wherein the preprocessing acceptance inspection interface includes a function for confirming characters for which preprocessing has been completed on a character by character basis, and a function for correcting handwritten characters on a character by character basis. A computer device according to any one of the following. 11. The font acceptance inspection interface includes a function for replacing each character in the font generation result with the generation result of another model or re-inputting handwritten characters. 14. The computer device according to claim 13 . The at least one processor includes:
providing a post- processing inspection interface for the user to inspect the post-processing results;
A claim characterized in that the post-processing acceptance inspection interface includes a function for confirming fonts for which post-processing has been completed and a function for adjusting a character size ratio within a text of the handwritten font. 14. The computer device according to any one of items 11 to 13 . 18. The computer device according to claim 17 , wherein the post-processing acceptance inspection interface includes a function for adjusting the handwritten font to a character size determined by a pre-setting or a custom setting of the user. .

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