KR20200065685A - Auto design generation method and apparatus for online electronic commerce shopping mall - Google Patents

Abstract

According to an aspect to the present invention, disclosed is a method for automatically generating a design associated with an online shopping mall. The method of the present invention comprises the steps of: preparing a canvas grid for inserting at least one image associated with a shopping mall, wherein the canvas grid refers to a grid structure on a canvas, which is a space into which the image is inserted; and generating a final design by inserting the image and a text interworking with the image into the prepared canvas grid. The step of preparing the canvas grid includes the steps of: generating a plurality of reference lines for multi-dividing a canvas region at the golden ratio based on the Fibonacci sequence, on the canvas grid in horizontal and vertical directions; and generating points for determining an arrangement of the image on at least some of contact points formed by the generated reference lines. According to the present invention, general shopping operators who do not professionally learn a design can even produce a design with high completeness.

Description

Method and device for automatic design of online e-commerce shopping mall {AUTO DESIGN GENERATION METHOD AND APPARATUS FOR ONLINE ELECTRONIC COMMERCE SHOPPING MALL}

The present invention relates to a method for generating a design, and more particularly, to a method for automatically generating a design related to an online shopping mall.

In the course of operating online e-commerce (which can be called a shopping mall), promoting the shopping mall is an indispensable activity to increase the awareness of the shopping mall and increase sales. The publicity activities of these shopping malls are often referred to as "promotions", which can be understood as "a variety of publicity activities conducted on a single subject."

Shopping mall operators use a variety of promotional means to increase the effectiveness of promotions. Among them, activities to display designs related to various shopping malls, including banners and banners showing concise and impact of promotion concepts and related information, It can be said to be the heart of public relations.

Therefore, the performance of the promotion has become an important factor to be influenced by the quality of the shopping mall design, but creating a shopping mall design with a high degree of completion is an area of experts who specialize in design, and ordinary people who lack experience in this field can pay a lot of money. The reality is that you are entrusting the production to an expert.

Accordingly, there is a need for an application for efficiently designing a shopping mall without relying on experts.

An object according to an aspect of the present invention for solving the above-described problem is to process an image and text in a form optimized for a user's intended purpose by using the image and text only when the user inputs only the image and text to create a design related to the shopping mall. And a method, apparatus, and system for automatically generating a design associated with a shopping mall by merging processed images and texts appropriately.

In order to achieve the above object, a method for automatically generating a design associated with an online shopping mall according to an aspect of the present invention includes preparing a canvas grid for inserting at least one image associated with a shopping mall (where the canvas grid is And generating a final design by inserting the at least one image and text interlocked with the image into the prepared canvas grid, and the grid structure on the canvas, which is the space in which the at least one image is inserted. The preparing of the canvas grid may include generating a plurality of reference lines on the canvas grid for multiple division of the area of the canvas with a golden ratio based on a Fibonacci sequence in the horizontal and vertical directions; and And generating points determining the arrangement of the at least one image on at least some of the contact points formed by the plurality of reference lines.

The step of generating points determining the arrangement of the at least one image includes: i) an image center point for centering the at least one image, and ii) between components inputting text interlocked with the image. It may include the step of generating an interaction point for controlling the linkage action and iii) a control point for controlling the input start point and the input end point of the text.

The center point of the image may be disposed on three quadrant reference lines that divide the canvas evenly in the vertical direction.

The image center point is composed of a plurality, but at least a part of the plurality of image center points, the first image center point existing in the center of the canvas and the second and second spaced apart from the first image center point A third image center point may be included.

The center points of the second and third images may be present at a contact point between two longest diagonal lines connecting two vertices in the diagonal direction of the canvas and two quadrant reference lines excluding the center one of the quadrant reference lines.

The first image center point is on a central quadrant reference line that crosses the center of the canvas, and the first image center point is, in the vertical direction, the same height as a straight line connecting the second and third image center points. Or it may be present on the top of the straight line.

When the at least one image is inserted into the canvas grid, the object in the inserted image is analyzed, so that the position of the face is in the center region of the canvas, whether it is in the center region, or is it from the center region to the left, and the center region The face of the image may be placed at one of the first to third image center points, depending on whether it is on the right side from.

The interaction points are composed of a plurality, and at least some of the plurality of interaction points may be disposed on at least a portion of an evenly divided reference line dividing the canvas evenly in the vertical direction and two longest diagonal points of the canvas. .

At least some of the plurality of interaction points are: i) 4 contact points of the leftmost and rightmost 8-partitioning reference lines and the diagonal line among the 7 8-partitioning reference lines that divide the canvas evenly 8 vertically; ii) the 4 Two of the four corners forming a virtual square block created by connecting the contact points and two contact points of the straight line dividing the canvas evenly in the horizontal direction may be disposed on the center point of the canvas iii).

The plurality of reference lines may include a plurality of straight lines such that at least one of a horizontal split ratio, ii) vertical split ratio, and iii) horizontal and vertical ratio is a golden ratio.

The plurality of reference lines include a dividing reference line dividing the canvas evenly in the horizontal and vertical directions, a dividing reference line including at least a portion of the dividing reference lines and the 8 dividing reference lines, and the canvas It may include a diagonal reference line that arbitrarily connects at least a portion of two end points of the four vertices and the evenly divided reference lines.

An apparatus for automatically generating a design associated with an online shopping mall according to another aspect of the present invention for achieving the above object, receives a request for automatic design generation from a user terminal and corresponds to a communication unit that provides the final design generated and the design automatic generation request Thus, a canvas grid for inserting at least one image associated with a shopping mall (canvas grid) means a grid structure on a canvas, which is a space into which the at least one image is inserted, and prepares the at least one image And a processor that inserts text interlocked with the image into the prepared canvas grid to generate a final design, wherein the processor, in the horizontal and vertical directions, has a golden ratio based on a Fibonacci sequence. A plurality of reference lines for multi-dividing a region of the image may be generated on the canvas grid, and points that determine the arrangement of the at least one image may be generated on at least some of the contacts formed by the plurality of reference lines. have.

A design automatic generation system associated with an online shopping mall according to another aspect of the present invention for achieving the above object transmits a design automatic generation request and receives a final design corresponding to the request, and a design from the user terminal and the user terminal Prepare a canvas grid for inserting at least one image associated with a shopping mall in response to an automatic generation request, wherein the canvas grid means a grid structure on the canvas, which is a space in which the at least one image is inserted, And a shopping mall design auto-generation device that generates a final design by inserting the at least one image and text interlocked with the image into the prepared canvas grid, wherein the shopping mall design auto-generation device comprises: The fibonacci sequence-based golden ratio generates a plurality of reference lines for multiple division of the canvas area on the canvas grid, and the at least some of the contacts formed by the plurality of reference lines Points that determine the placement of an image can be generated.

According to a method and apparatus for automatically generating a design and a system associated with a shopping mall of the present invention, a general shopping mall operator who has not studied design professionally by automating a shopping mall-related design production process relying only on human intuition and experience using artificial intelligence They can also produce designs with high degree of maturity, thereby improving the competitiveness of small shopping mall operators.

1 is a block diagram showing a system to which a method for automatically generating a shopping mall design according to an embodiment of the present invention is applied;
2 is a flowchart illustrating a method for automatically generating a shopping mall design according to an embodiment of the present invention,
3 is a diagram showing an interface for selecting an image and text to be used for shopping mall design in a user terminal;
Figure 4 is a conceptual diagram showing a canvas grid (canvas grid) that is a space where images and text are inserted to create a shopping mall design,
5 is a flowchart illustrating an image insertion method according to an embodiment of the present invention,
6 is a conceptual diagram for explaining a method of placing an image on an image center point,
7A is a conceptual diagram illustrating a method of deriving the shape of an image through image visualization analysis and matching it with a visualization pattern grid type;
7B is an exemplary view showing various embodiments of a visualization pattern grid that matches the shape of an image by the method of FIG. 7A;
8 is a conceptual diagram for explaining a method of determining the location of a component through margin analysis;
9 is a conceptual diagram for explaining a method for determining the arrangement of a component by matching the determined location of the component with the canvas grid;
10 is a flowchart illustrating a method of relocating components by analyzing the complexity of each component,
11 is a view showing the final design of the image and text is inserted into the canvas grid and data,
12 is a flowchart illustrating a method for determining a property value of text through image analysis,
13A to 13B are exemplary views for explaining a process of matching attribute values of text and information obtained from an embedded image,
14 is a matching diagram for matching emotional vocabulary and image color in a method of automatically generating a shopping mall design according to an embodiment of the present invention;
15 is a table exemplarily showing a result of matching attribute values of text based on emotion information and complexity information extracted from an image in a shopping mall design automatic generation method according to an embodiment of the present invention,
16 is a conceptual diagram conceptually summarizing the process of deriving the final result through the image/text merging process from the first input image through the automatic shopping mall design method according to an embodiment of the present invention;
17 exemplarily shows a plurality of final design candidates,
18 is a view showing a breakpoint of a canvas grid system used in a method of automatically generating a shopping mall design according to an embodiment of the present invention;
19 is a conceptual diagram for explaining a single grid and a single control point of a canvas grid system used in a method for automatically generating a shopping mall design according to an embodiment of the present invention;
20 is a view showing a configuration of a control point on a canvas in 1200 grid mode;
21 is a view showing a control center (central reference plane) and a component area in a 120 x 74 grid mode;
22A to 22C are conceptual views illustrating features having different grid sizes according to device breakpoints in the horizontal direction;
23 is a view showing a device breakpoint in the vertical direction,
24 is a diagram showing a layout configuration in which a ratio based on a Fibonacci sequence is added to a grid system;
25 is an exemplary view showing a two-part layout in a horizontal direction and a three-part layout in a horizontal direction;
FIG. 26 is an exemplary view showing an exemplary appearance of a shopping mall design completed by inserting images and text into the two-part layout and the three-part layout of FIG. 25;
27 is a detailed flowchart illustrating a design insertion process according to the size of a divided layout section of a method for automatically generating a shopping mall design according to an embodiment of the present invention.
28 is a production size table that is standardized in the form of a design of a specified size when the design of a shopping mall is utilized in a specific channel such as advertisement/SNS in the visual element of the method for automatically generating a shopping mall design,
29 is a block diagram showing a shopping mall design automatic generation device according to an embodiment of the present invention.

The present invention can be applied to various changes and can have various embodiments, and specific embodiments will be illustrated in the drawings and described in detail.

However, this is not intended to limit the present invention to specific embodiments, and should be understood to include all modifications, equivalents, and substitutes included in the spirit and scope of the present invention.

Terms such as first and second may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from other components. For example, the first component may be referred to as a second component without departing from the scope of the present invention, and similarly, the second component may be referred to as a first component. The term and/or includes a combination of a plurality of related described items or any one of a plurality of related described items.

When an element is said to be "connected" or "connected" to another component, it is understood that other components may be directly connected to or connected to the other component, but there may be other components in between. It should be. On the other hand, when a component is said to be "directly connected" or "directly connected" to another component, it should be understood that no other component exists in the middle.

The terms used in this application are only used to describe specific embodiments, and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this application, terms such as “include” or “have” are intended to indicate the presence of features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, one or more other features. It should be understood that the existence or addition possibilities of fields or numbers, steps, operations, components, parts or combinations thereof are not excluded in advance.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by a person skilled in the art to which the present invention pertains. Terms such as those defined in a commonly used dictionary should be interpreted as having meanings consistent with meanings in the context of related technologies, and should not be interpreted as ideal or excessively formal meanings unless explicitly defined in the present application. Does not.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In order to facilitate the overall understanding in describing the present invention, the same reference numerals are used for the same components in the drawings, and duplicate descriptions for the same components are omitted.

Shopping mall design automatic generation system

1 is a block diagram showing a system to which a method for automatically generating a shopping mall design according to an embodiment of the present invention is applied. As shown in FIG. 1, the design auto-generation system according to an embodiment of the present invention may include a shopping mall 110-1 to 110-N, a network 120, and a shopping mall design automatic generation device 130. .

Referring to FIG. 1, shopping malls 110-1 to 110 to N are online shopping malls selling products and/or services through the Internet. The shopping malls 110-1 to 110 to N sell products to visitors to a corresponding address on the Internet with a specific URL. The shopping mall operator operates the shopping mall by obtaining at least a part of the amount of the product sold through his account associated with the shopping mall.

In FIG. 1, the shopping malls 110-1 to 110 to N are implemented as a web page of a specific address (for example, a URL) on the Internet, a server handling information related to a shopping mall, or a terminal of an operator of a shopping mall. Can be. The terminal may include a computing device such as a smart phone or a PC.

According to an embodiment of the present invention, a plurality of shopping malls 110-1 to 110-N may interwork with the shopping mall design automatic generation device 130 through the network 120. Shopping mall (110-1 ~ 110-N) may be implemented as a device for requesting the creation of a design (which may include a banner design) for product display of their own shopping mall, promotion of events in a shopping mall, and the like. The related design generation may be requested to the shopping mall design automatic generation device 130. At this time, the operator of the shopping malls 110-1 to 110-N may provide information about an image and/or text to be inserted into the design to the shopping mall design automatic generation device 130. Since not all images desired by the operator can be used as a design, the image information and/or text information can be viewed as candidate images and/or text to be applied to the design. Here, the text includes letters (including English, Korean, Korean, ..., etc.), numbers, symbols, formulas, etc., and may include all languages in a form that can be processed by a computing device. The image may include images in various formats such as JPG, PNG, BMP, GIF, JPEG, PDF, JPE, and TIFF. However, since the GIF file is a moving image file including multiple frames, it may be desirable to extract each frame and convert it to a JPG file.

According to another embodiment of the present invention, the shopping mall 110-1 to 110-N operator may request only text to be included in the design. The device may receive a request containing only text and directly analyze the meaning of the text, and the device may select an image that best matches the meaning of the text to generate a design in which the image and the text are merged.

According to an embodiment of the present invention, the shopping malls 110-1 to 110-N provide promotional purposes, publicity targets, promotional topics, event-related information, and/or seasonal information to a shopping mall design creation request that includes images and text. Inclusion may be provided to the shopping mall design automatic generation device 130. The additional information may be used to perform a function of extracting key words from text in the shopping mall design automatic generation device 130 and a function of selecting a target image. Promotional topics can be largely classified as one of discount/sale, new product/season, brand/category, free gift/point, SNS/member, anniversary/official and free delivery.

The network 120 is a communication network connecting the shopping malls 110-1 to 110-N and the shopping mall design automatic generation device 130, and may include a wired network and/or a wireless network (internet).

The shopping mall design automatic generation device 130 receives and receives a design generation request (which may include image and/or text information) from at least one of the shopping malls 110-1 to 110-N through the network 120. It is a device that automatically creates a design associated with a shopping mall based on an image and/or text. The shopping mall design automatic generation device 130 may be implemented as a computing device. The computer device referred to herein can be implemented as a server-class computer terminal. The computer device may include an input device, a display device, a networking device, a hard disk, a memory for storing a program, and a processor for executing a program stored in the memory. However, it is not necessarily implemented as a server-class computer terminal.

The shopping mall design automatic generation device 130 may be a server that distributes and manages a platform for opening and operating a shopping mall or a server interworking with the server. Therefore, the shopping mall design automatic generation device 130 not only handles information related to one shopping mall 110-1, but also handles information related to multiple shopping malls 110-1 to 110-N and handles big data. Based on this, various information can be analyzed and learned. In addition, in order to generate a design most appropriate to the user's request, optimal information is derived from information of a plurality of shopping malls 110-1 to 110-N and used in design creation.

In response to a request from a shopping mall operator, the shopping mall design automatic generation device 130 determines whether the received image is suitable for insertion into the design. Then, the image is placed on a canvas grid, and the image requested by the operator is appropriately merged with the image by analyzing the image for each specific unit area on the placed canvas grid. Then, it returns to the operator of the shopping malls 110-1 to 110-N (hereinafter referred to as "users") that requested the generated design.

The shopping malls 110-1 to 110-N may receive a design generated by the shopping mall design automatic generation device 130 and determine whether to upload to the shopping malls 110-1 to 110-N or other channels according to the operator's judgment. have. The design generated according to the determination may be utilized in web pages, applications, and/or SNS associated with shopping malls 110-1 to 110-N.

According to another embodiment of the present invention, the terminals associated with the shopping malls 110-1 to 110-N may download the application provided by the shopping mall design automatic generation device 130 and perform automatic generation through the application. That is, the user terminal associated with the shopping malls 110-1 to 110-N may perform a process of automatically generating a shopping mall design from an input image and/or input text in the terminal. If a processor (not shown) of the terminal executes the downloaded application without a separate server device, it is possible to generate an optimal shopping mall design through image analysis and/or text analysis.

Shopping mall design automatic creation method

2 is a flowchart illustrating a method for automatically generating a shopping mall design according to an embodiment of the present invention.

Referring to FIG. 2, a shopping mall design automatic generation device (which may be called a server or a device) requests a design generation including an image and text from a user terminal (a shopping mall operator terminal or a user's terminal requesting a design associated with a shopping mall). It is received (S210). The design creation request may be made by inputting an image and text in a web page for automatically generating a shopping mall design provided by the device. This will be described in more detail through FIG. 3 below.

3 is a diagram showing an interface for selecting an image and text to be used in a shopping mall design at a user terminal.

Referring to FIG. 3, when accessing a web page for automatic generation of a design provided by the device, an item for selecting an image to be used for design and an item for selecting text may be displayed. With regard to the selection of the image, the user can load the image stored in his terminal through the "Load" icon. Alternatively, a specific image of a shopping mall operated by the user may be selected so that the selected photo becomes the background of the design.

In some cases, it is also possible to click the "automatic image generation" icon to have the device directly obtain the optimal image associated with the text. At this time, the device may acquire an image corresponding to the meaning of the text in a range of various images associated with the corresponding shopping mall or other shopping malls through semantic analysis and image analysis of the text.

Furthermore, a design can be generated by selecting and separating images by using the “set image category” icon. For example, it may be set to use only images corresponding to a specific category, such as "upper body cut", "lower body cut", "coat", "underwear", "summer clothes", and "winter clothes".

Additionally, the user can select multiple images for automatic design creation. That is, a plurality of images can be generated in one design.

Next, the user can directly input text to be inserted into the design in the text input part. The text can be divided into the main text (which can be called "red line") to determine the most important image of the design, and the sub text (which can be called "subcopy") of lower importance than the main text. . In addition, ③ sub texts (which may be referred to as "secondary copies") of lower importance than sub texts can be input separately.

The device can analyze the key words of the main text and use it to analyze the overall mood and emotion of the image. In particular, since it is desirable to emphasize the key words of the main text, it is preferred to place the main text in the first component where the text can be most emphasized in the canvas. Then, considering the relevance to the first component in which the main text is placed, the subtext is placed in the second component having the highest association with the first component. The device may correspond to the number of components based on the number of texts.

In particular, the device may receive information on the following parts as additional input information in a user interface related to automatic creation of a shopping mall design. The device distinguishes whether it is a part for inputting whether it is purpose information (planning, product exhibition, site production, etc.) related to the promotion and a part for inputting data for the season (season), promotion benefit information, and yearly event data. You can provide a part for entering information. The user may input information corresponding to an input field related to promotions and events in the provided interface. The device may be configured to prepare a template corresponding to the purpose, season, benefit, and peculiarity according to the inputted information, and output the prepared template as a final design in response to user input data.

According to an embodiment of the present invention, even if only additional information is input without inputting an image and text, the optimal image and text corresponding to the additional information are stored in a server or searched and obtained from other storage devices associated with the server can do. When acquiring images and texts, artificial intelligence based on machine learning may be used.

In addition, the user interface of FIG. 3 may provide a portion for inputting the size of the design to be generated in order to determine the size of the design to be produced and the size of the canvas grid system corresponding thereto. At this time, it is possible to provide a part for selecting a place to use the corresponding design. For example, whether the design will be used for a shopping mall brand, for advertising purposes (in this case, it may be further subdivided into whether it is a Facebook advertisement, a Google DA, etc.), direct mail, or SNS (in this case, Facebook) , It can be subdivided into Instagram, line, etc.) It provides an interface to decide whether to use for uploading.

Returning to FIG. 2 again, when input of an image and text is completed at the user terminal, the device prepares a canvas grid (S220). The canvas grid is a basic grid system for creating the final result of shopping mall design, and refers to a physical and/or logical space in which images and text are inserted. The canvas grid is basically designed considering the golden ratio (1: 1.618) (which can be referred to as "fibonacci sequence based ratio") in the horizontal and vertical directions. Based on the golden ratio, a reference line for dividing the area into multiples is arranged, and a number of points are generated for controlling the design at the contact point of the reference line. And, it is possible to control the image and text based on the generated points. The canvas grid will be described in more detail with reference to FIG. 4 below.

When the canvas grid is ready, the device inserts an image into the canvas grid (S230). In image insertion, the device determines the suitability of design insertion. The judgment factor is mostly related to the analysis of the image (eg, including a face recognition algorithm). The device performs analysis on whether a face exists in the image, what state the object in the image is (eg, what gesture is being performed in the case of a person), whether the image is an upper body cut, a full body cut, and the like. It will be apparent that a part specifically described in the "face" in this specification may be replaced with a specific object (product, other part of the human body, etc.) other than the face even if it is another image that does not include a face or an image that includes a face. .

The device determines that the face is present, the face is displayed at a size equal to or greater than a reference value, and the pixel size and image size of the canvas are considered to be an image suitable for inserting an image in the allowable size range into the design. For example, it may be determined that an image having a size of 200 pixels is not included in an allowable size range on a canvas having a size of 1000 pixels, and the image may be discarded. However, images within the allowable size range are inserted into the canvas by matching the canvas grid.

After inserting the image, the device derives the shape associated with the image (S240). This is done by analyzing the objects in the image. The shape of the image is derived based on the four vertices where the object meets an arbitrary rectangle surrounding the object. Then, the visualization pattern grid type (which may be referred to as a pattern grid type) corresponding to the derived shape is matched (S250 ). According to an embodiment of the present invention, the visualization pattern grid type largely includes triangle type, diamond type and cross type. That is, the shape of the derived image is matched to one of the above three types. Then, the apparatus determines the arrangement of components in consideration of the matched type and the margin portion of the image (S260). Margin analysis includes analysis on which areas in the image have a lot of margins, how complex the margins are, and which contours separate the objects from the margins. Here, the component means an arbitrary area in the canvas for inputting text. The component is basically formed in the form of a rectangle, and its size and arrangement primarily take into account the type of the matched pattern grid, and may be changed depending on the analysis of the placement and insertion of objects in the image. At this time, the analysis content of the text largely includes the analysis content of the information amount of the text, the number of morphemes, the meaning of the key word, and the like.

After determining the arrangement for the component, the device inputs text into the component area (S270). Through the above process, the device can generate examples of the placement of components and attribute values of text inserted into the components according to the number of various cases, and these various exemplary designs are sequentially ordered from the ones having the best aesthetics. It is possible to create something that has a lower aesthetic. At this time, the device may display the top N designs (the N may be a set value) from the best design to the user. Then, it can wait for the user's selection.

2 is a general description of a method for creating an overall shopping mall design, each step (S220, S230, S240, S250, S260, and S270) will be described in more detail with reference to FIGS. 4 to 11 below.

Canvas grid system basics

4 is a conceptual diagram showing a canvas grid, which is a space in which a shopping mall design is generated by inserting images and text.

Referring to FIG. 4, the canvas grid has a rectangular shape and controls all design elements. In addition, it is designed to derive an optimized response to the environment of any type of user terminal.

In the canvas grid, points for control are generated at the contact points between the reference lines based on various reference lines. Therefore, the reference line is a factor that determines the position of the broad control point. First, the baseline includes straight lines that allow the Fibonacci sequence-based golden ratio to be maintained in the horizontal and vertical directions. Since the horizontal and vertical ratios of the canvas grid have a golden ratio of 1: 1.618, an area surrounded by a reference line in the form of dividing it in half may also have a golden ratio. Therefore, by dividing the canvas in half in the horizontal and vertical directions, a reference line is generated so that one canvas area is divided into several to several tens of divided areas.

In this way, reference lines for dividing into horizontal and vertical regions, reference lines for dividing (410-1, 410-2, 410-3) and reference lines for dividing by 8 are generated. Then, a diagonal is generated by pairing two of the four vertices of the canvas, and the diagonals between the four divided reference lines 410-1, 410-2, and 410-3 and the eight divided reference lines are also generated. In addition, diagonal lines are also generated in the quadrangle blocks generated by the four-division reference lines 410-1, 410-2, and 410-3. Then, in the vertical direction, vertical margin lines are generated in the left and right regions of the outermost 8-division reference lines 420-1 and 420-2. The margin line is an area in which no text is input, and an area in which components are not arranged. Margin lines in the horizontal direction are also created in the upper and lower regions of the outermost 8-segment reference line.

After creating the reference line as above, various points for text and component control are created on the contact points between the reference lines.

According to an embodiment of the present invention, the canvas grid may include three different points of concept. The point may be a single point, that is, a pixel, or may be a grid because it is a grid system. The concept of the grid will be described in more detail in FIGS. 18 to 22 below.

1) One of three different concept points is an image center point into which an object (eg, face, product, etc.) that is the center of the image is inserted. As the center point of the image, the center of the object is inserted, and the image usually has one object, so it can be regarded as the centering point of the image. Three image center points may be arranged in the canvas grid. The three image center points are respectively disposed on the vertical quadrant reference lines 410-1, 410-2, and 410-3. The two image center points of both sides are generated on the contact point between the left and right quadrant reference lines 410-1 and 410-3 and the horizontal quadrant reference lines 415. In addition, the quadrant of the rest of the center portion is disposed slightly above the two image center points of both sides, and the contact point where the center quadrant of the center 410-2 and the uppermost 8-division reference line of the horizontal direction meets 425-1. It is produced on. However, the center image center point is not necessarily disposed above the image center points on both sides, and may be arranged on the same line. This is an element that can be arbitrarily changed through user setting.

2) Next, the point of the second concept is an interaction point. This is the point that defines the component, controls the shape and arrangement of the component, and is the basis for calculating the complexity of the component. The interaction point serves as a standard for component relocation (work based on the association of components) in consideration of the organic relationship according to the semantic analysis of text. The apparatus may obtain a correlation between two or more components in consideration of the size and arrangement relationship of the generated component based on the interaction point. Since the interaction points are generated in a diagonal shape, components in the diagonal direction or in both ends of the evenly divided reference line may have high correlation. In addition, components connected in the horizontal and vertical directions may also have high correlation.

"자 형태로 배치된다. 즉, 캔버스 내의 가장 긴 두 개의 대각선(430)과 세로방향 사분할기준선(410-1, 410-2, 410-3)과의 접점 상에 배치된다. A total of seven interaction points can be arranged. However, it is not necessarily limited thereto. Interaction points follow diagonal direction"

"It is arranged in the shape of a ruler. That is, it is disposed on the contact point between the two longest diagonal lines 430 in the canvas and the vertical quadrant reference lines 410-1, 410-2, and 410-3.

In other words, in the vertical direction, three are arranged on the left 8-division reference line 420-1, and three are arranged on the right 8-division reference line 420-2. Then, one is arranged at the center point.

When viewed in the horizontal direction, three are generated, one at the contact point that meets the dividing reference line 440, and two at the contact point that meets the top and bottom 8 division reference lines 425-1 and 425-2. Then, one interaction point is generated at the center point where the longest diagonal line in the canvas block meets.

However, it is not necessary to have only seven interaction points, and may be arbitrarily arranged at a part of the contact points of the horizontal and vertical quadrants and 8-segmented baselines.

3) Third, there is a consultation control point. The control point of the negotiation is the point that controls the start and end of the text. The negotiated control point controls the input start point and input end point of the text when the text is input after the component arrangement is completed. Control points are used to determine the placement of text, and the device controls the start and end points of the text, taking into account the relationship with specific objects in the image. For example, if a rectangular block including a face in an image is included in a range from the first reference line to the second reference line, input text cannot be inserted in a range up to a specific reference line corresponding to the first and second reference lines. You can enter text based on rules. The device determines the position of the text optimally by controlling the control point based on the rules related to the input of objects and text in the predefined image.

According to an embodiment of the present invention, the control point may be disposed at the contact point of the vertically divided quadrant reference line and the horizontally divided 8 reference line. In the present embodiment, five are arranged at the contact point between the third 8-segmented reference line in the horizontal direction from the top and the 5 8-segmented reference lines in the center in the vertical direction, and the third horizontally divided reference line 410-2 and the third in the horizontal direction from the top. It is described that 5 control points are arranged at the contact point with the 7th 8-segment reference line, and a total of 9 control points are arranged by subtracting the number of overlapping points. However, control points do not have to be present.

According to another embodiment of the present invention, it may be disposed on all the contacts except the margin region among at least some of the contact points of the horizontal and vertical directions of the quadrilateral reference line and the 8 division reference line.

5 is a flowchart illustrating an image insertion method according to an embodiment of the present invention.

Referring to FIG. 5, the device prepares a canvas grid according to the method of FIG. 4, and then inserts an image into the canvas grid. When the device inserts an image, the validity of the image insertion is first verified. Validation determines whether a model exists in an image or an object (eg, a product) corresponding to a specific text.

Then, the display screen information of the terminal is obtained from the user terminal, and a canvas grid corresponding to the screen of the terminal is generated, and then the total pixel size of the generated canvas grid and the size of the inserted image are compared. Then, if the image exceeds the allowable range with respect to the size, it is discarded. In addition, it is determined whether text exists in the image, and if the text exists, it is discarded.

In more detail, the determination of validity may be performed based on whether all eyes, nose, and mouth of the model are visible. Whether or not pre-stored components (eye, nose, and mouth) in the model's face are present in the image may be achieved through a face tracking technique, and as an image related to a shopping mall based on the coordinate values of the component. Judge the availability of Without one of the eyes, nose and mouth, the image can be discarded.

Next, the device extracts information related to the face size of the model and compares it with a reference value. The device identifies the contours of the face and calculates the area formed by the identified contours. The apparatus compares the extracted face size information with a preset face size reference value, and determines that an image having a reference value or more is usable, and discards the image that is not. Then, the device extracts information related to the face direction of the model. The extracted data is data related to the face angle, and may include Roll degree, Pan degree, and Tilt information. That is, it includes left and right directionality of the face, head tilt information, and neck turning information. Then, it is determined whether or not the extracted left and right directional information of the face, the upside down tilt and the neck turning information are included in the set reference values, respectively. For example, if one side of the face does not come out, or if the head is turned too far or the head is turned too much, it may be determined that it is not valid. Discard images that are not valid.

Furthermore, it is determined whether the image belongs to the image category requested by the user (eg, upper body cut). This can be done through object analysis. That is, it is determined by determining the association between the object in the image and the category requested by the user. For example, if the user selects the upper body cut image category, images made of the lower body cut may be discarded when validating. The above validation process is excluded from this flow chart.

After the verification process, the target image to be inserted (hereinafter referred to as “target image” or “inserted image”) is adjusted in size to match the size of the canvas grid corresponding to the size of the display screen of the user terminal, and then to the canvas grid. It is inserted (S510). The size adjustment is performed by matching the size of the corresponding direction of the image to the size of at least one of the horizontal and vertical directions of the canvas. If the size fits only in one direction and the other does not fit, the optimal background is added through object and/or color analysis of the part.

Thereafter, the device determines the position of the face in the target image (S520). This can be done using an object recognition algorithm, especially a face tracking algorithm. The apparatus may select an image center point to be inserted by determining how far the face is from the center line of the image.

For example, it is determined whether the face is in the center (S530), and if it is in the center, the face is placed at the center point of the center image (S535). If it is not in the center, it is determined whether it is on the left side from the center (S540), and if left, a face is placed at the center point of the left image (S545), and if it is right, a face is placed at the center point of the right image (S555). With the placement of the faces, the position of the image is adjusted to fit the canvas grid. This will be described in more detail through FIG. 6.

6 is a conceptual diagram illustrating a method of placing an image on an image center point.

Referring to FIG. 6, in inserting an image in a canvas grid, the device locates a face in the image. Then, the device generates a square block 610 including a face based on object information related to the face in the image, so that the center point of the block corresponds to any one of the three image center points. Adjust it.

In the embodiment of FIG. 6, since it is determined that the face exists in the center of three areas including the left, center, and right areas of the image, the square block associated with the face at the center image center point 620 Adjust the position so that the center point of 610 fits.

As described above, if the ratio of the image does not exactly match the ratio of the canvas, even if scale-up or scale-down, the image may not fit on the canvas. At this time, the image is inserted into the canvas in consideration of the center point of the image, and an appropriate image is inserted into the surface of the blank portion in the canvas that the image cannot cover. At this time, the surface of the corresponding color can be appropriately inserted into the margin part by using the sensitivity of the image.

In addition, as described above, in the embodiment of FIG. 6, the center of the image is described as a face, but the face does not necessarily have to be the center of the image, but other objects (specific parts of the model (hands, feet, legs, etc.) ), a product, or a specific building) may also be the center of the image will be apparent to those skilled in the art to which the present invention pertains.

7A is a conceptual diagram for explaining a method of deriving the shape of an image through image visualization analysis and matching it with a visualization pattern grid type.

Referring to FIG. 7A, after inserting an image into a canvas grid, the apparatus detects an outline of all objects including faces in the image using an object recognition algorithm. As in the embodiment of FIG. 7A, the device can view the object as a whole body of the model and detect the contour. In other embodiments, the entire object does not necessarily correspond to the model whole body, but may also correspond to the half body of the model, the overall shape of other products, the shape of the building, and the like.

After detecting the contour of the object, the device generates a rectangular block 710 surrounding the object, and generates a point at which the contour of the object contacts the block 710. As in the embodiment of FIG. 7A, the contact point of the block 710 in which the contour of the object surrounds the object may be indicated by points of A, B, C and D. A is a top portion, B is a left side, C is a bottom portion, and D is a right portion of the square block 710 that is in contact with the dot. Then, A, B, C, and D are connected by lines to derive the shape of the corresponding image. In FIG. 7A, the hatched shape may be defined as a shape derived from an image. At this time, it is possible to determine the image shape in more detail in consideration of the length relationship of the A-B, B-C, C-D and D-A straight lines.

When the shape of the image is derived, the device calls a grid suitable for the shape of the image through object visualization. That is, the device matches the previously stored visualization pattern grid type with the derived shape. The pre-stored visualization pattern grid type can be roughly divided into three types. It can be divided into a cross shape, a diamond shape, and a triangle shape. The cross is a diagonal grid, a pattern grid that has the shape of a parallelogram. The diamond is a grid in the form of a rhombus, and the triangle is a grid in the form of a triangle.

The above three types are the division into the primary class, and in the classification of the sub-class, the secondary class type is selected according to the details of the image shape based on the length of the AB straight line, BC straight line, CD straight line and DA straight line. do. In the secondary class type of the pattern grid, even within the rhombus pattern, it is more precisely distinguished which part is an asymmetric rhombus or a long rhombus. Alternatively, the triangle may be matched by distinguishing whether it is an equilateral triangle, an isosceles triangle, or an inverted triangle.

This more subdivided classification is a cross, rhombus, and various forms of diagonals based on the diagonal and quadrant based on the vertical dividing reference line at the bottom of FIG. And/or triangle types.

7B is an exemplary view illustrating various embodiments of a visualization pattern grid that matches the shape of an image by the method of FIG. 7A.

Referring to FIG. 7B, although the device is classified as the same visualization pattern grid type in the type classification of the primary class, the type of the visualization pattern grid can be classified in various forms in the type classification of the secondary class. That is, based on the length relationship between the A-B line, B-C line, C-D line, and D-A line of FIG. 7A, the shape of the image may be matched to a detailed pattern grid type corresponding to a plurality of reference lines at the bottom of FIG. 7A.

8 is a conceptual diagram illustrating a method of determining a component location through margin analysis.

Referring to FIG. 8, the device determines the size and arrangement of components based on the matched pattern grid type. At this time, the object analysis technology is used to measure the margin data excluding the object part of the image. In the margin analysis part, the device declares the area of the margin analysis based on four points (A, B, C, and D points) that the object contacts the square block 710 including the object of FIG. 7A.

Then, the device defines a plurality of margin areas based on the square block (see 610 of FIG. 6) including the four points and the face area. The margin is basically set to comb the range of the square block 610 associated with the face region while allowing at least one point of A, B, C, and D to be included. In particular, since there is a high possibility that objects are connected to the vertical and/or horizontal portions of the square block 610, the region portion on the vertical and/or horizontal extension line is also excluded from the margin region. A plurality of blank areas can be defined based on such a margin setting rule. In the embodiment of FIG. 8, four margin regions may be generated: a margin region 1, a margin region 2, a margin region 3, and a margin region 4.

9 is a conceptual diagram illustrating a method of determining a component arrangement by matching a determined component location with a canvas grid.

Referring to FIG. 9, the apparatus determines the size and arrangement of components based on the margin area. At this time, components are declared in the margin region, except for the outer portion of the margin region of the canvas grid. Then, the device generates a smaller sized square block 920 in which a real face in the square block 910 including the face region exists, and declares a component based on this.

That is, since components 1 and 3 are directly in contact with the face region, a component can be defined based on the large sized face region square block 910 and the margin region 1 and margin region 3. In addition, since components 2 and 4 are not directly in contact with the face region, a component may be defined to correspond to the rectangular block 920 of a small size and the predefined margin region 2 and margin region 4.

After the basic arrangement of components is determined as described above, the role of each component is assigned by analyzing the size and/or complexity of the component. This will be described in more detail through FIG. 10 below.

10 is a flowchart illustrating a method of relocating components by analyzing the complexity of each component.

Referring to FIG. 10, the device analyzes the size of the component (S1010), and gives a role of the component (S1012). For example, it may be determined that the main text, i.e., the headline, is located in the largest component. The device prioritizes text input in priority based on the size of the component. For example, the priority is determined such that a component of the first size becomes the first order of text input, a component of the second size is ranked second, and a component of the third size is ranked third. At this time, the larger size may be given priority, and the smaller size may be given priority. Furthermore, the device may not only quantitatively analyze the size of the component, but also determine the position of the headline based on the width and length of the component. Components having the most appropriate aspect ratios may be assigned priority. Suitable here may be defined as a ratio of 1:1, 1:2, 1:3, 1:4 or 4:1, 3:1, 2:1 or close to the golden ratio. The main text (headline) may be input to the first-rank component, and the sub-text may be input to the next-rank component.

Next, the device analyzes the complexity of the image in the component region through the image analysis module (S1014). At this time, the interaction point may be a reference point for calculating the complexity of the corresponding region. The apparatus determines the suitability of inputting text based on the result of the complexity analysis. In this case, the reference value of the complexity for determining the input suitability of the headline (main text) and the subtext may be set differently. It is possible to prevent the main text from entering a highly complex component. For example, the main text may be set so that it cannot be input to a component having a complexity of 50 or more, while the subtext may be set so that it cannot be input to a component having a complexity of 100 or more. In this case, the component of the complexity of 75 cannot input the main text, but the input of the sub text may be possible. Text input may not be possible for components of 150 complexity. In the same manner as above, the device may perform rearrangement for the position of the headline based on the result of the complexity analysis (S1024).

Repositioning components not only changes the correspondence between components and input text, but also changes the size and/or position of components.

In addition, the image analysis result is not the only function for relocating the text input component.

According to an embodiment of the present invention, the device analyzes the input text in a morpheme unit through a text analysis module (S1020). That is, in order to derive an optimized design type according to the amount of morpheme data among user input data, component arrangement may be different (S1024). For example, based on the amount of information in the morpheme of the headline, a single morpheme (eg, word-like text such as "SALE") partially ignores the region of the divided component and does not invade the face region at the center of the object. Can be inserted. Or, it allows text to be inserted across two or more component regions. For example, "SA" may be inserted into Component 1 and "LE" may be inserted into Component 2 over the regions of Component 1 and Component 2. In this way, the device may reposition the component in consideration of the quantitative relationship between the component and the inserted text. In particular, since such a word text often needs to emphasize a concept to be expressed, the device can increase the possibility of ignoring the arrangement relation of a predefined component through the above process.

In addition, in the case of a combination morpheme (text in the form of a combined word), the arrangement of predefined components may be different through image analysis according to the amount of the combined text. Further, in the case of multiple morphemes (for example, sentence-type text), the sentence is divided for each morpheme and divided into suitable components, or if it can fit into one component, the appropriate component considering the relationship between the amount of text and the size of the component Components can be repositioned so that they can be input to.

" 형태로 캔버스 그리드 내에 인터랙션 포인트가 배치되어 있기 때문에, 인터랙션 포인트들은 대각방향의 포인트들 간, 가로방향 포인트들 간, 및 세로 방향 포인트들 간 중 적어도 하나 사이에서, 유기적인 관계를 갖는다. 따라서, 둘 이상의 컴포넌트에 텍스트를 분할 배치하는 경우, 인터랙션 포인트 간의 유기적인 관계를 고려하여 텍스트를 입력할 수 있다. 예컨대, "Winter Sale"과 "Discount 70%"라는 두 개의 텍스트(메인텍스트와 서브텍스트)가 컴포넌트에 배치될 때, 대각방향이 주는 심미성을 고려하여, 컴포넌트 1에 "Winter Sale"이 컴포넌트 4에 "Discount 70%"라는 텍스트가 각각 배치될 수 있도록 컴포넌트를 재배치할 수 있다.In addition to quantitative analysis of morphemes, components can be rearranged through semantic analysis of text (S1022) (S1024). That is, when the main text and the sub-text are combined to have a meaningful meaning, the components are rearranged in consideration of the aesthetic part of the two texts and the mutual organic relationship. At this time, the reference point of the organic relationship of the components may also be an interaction point. "

Since the interaction points are arranged in the canvas grid in the form, the interaction points have an organic relationship between at least one of diagonal points, horizontal points, and vertical points. When text is divided into two or more components, text can be entered in consideration of an organic relationship between interaction points, for example, two texts (main text and sub text) of "Winter Sale" and "Discount 70%". When is placed on the component, the component may be repositioned so that the text “Winter Sale” on component 1 and “Discount 70%” on component 4 are respectively placed in consideration of the aesthetics of the diagonal direction.

According to another embodiment of the present invention, a variation of text input by a user may be inserted into a component. Again, the interaction point is used. For example, when a user requests "50% SALE" as input text, the device recognizes that the meaning of "50% SALE" sells products at half price and directly generates a similar term or a term related thereto, thereby generating an arbitrary Can be placed in a component. For example, a variation of “50% SALE” called “half price sale” may be generated, and the phrase “half price sale” may be input to component 4 arranged in a diagonal direction of component 1 to which “50% SALE” is input. The text analysis module of the device may generate the similar or emphasized words as described above.

FIG. 11 is a diagram showing the final design of the image and text inserted into the canvas grid and dataized.

Referring to FIG. 11, the device forms a final design by properly arranging main text and sub text within a component. In particular, the device may place at least one of the pre-stored decorative shapes on one of the components based on the semantic analysis of the text. The decorative shape does not necessarily have to be placed full on the component, and can be appropriately disposed on at least a part of the component in a line maintaining the golden ratio.

In the embodiment of FIG. 11, the device may place a circular shape 1100, “NEW ARRIVALS”, as a decoration on component 2 in the lower left. At this time, the device is placed in the component by modifying the size of the decorative shape 1100 so that the component 2 can maintain the golden ratio of 1:1.618 in the horizontal direction.

According to an embodiment of the present invention, the shapes arranged in the decorative form may include various shapes such as a circle, a rectangle, a square, a triangle, a diamond, a leaf, an asterisk, a question mark, an exclamation mark, and other polygons. The device selects a decoration shape corresponding to the image based on the image analysis result, the result of semantic analysis of the input text, data related to the purpose of the promotion, season data, promotion benefit data and/or year-round event data, etc. You can insert For example, in the case of a "Christmas sale", a "Christmas tree" decoration may be inserted into the design.

The selected decorative shape is placed in a predetermined space in consideration of aesthetics within the component. The decorative shape does not necessarily have to be disposed only within the component, but may be disposed over two or more components, or over the entire image area. For example, as a result of image analysis, when the sensitivity of the image is analyzed as "warmness," a decoration shape is selected as "circular" to control the control so that any one of a plurality of pre-stored ornaments formed in a circle is properly disposed in the image. Can be.

Through the method described above, the validity of the image is verified, the image is inserted into the canvas grid, the object of the inserted image is analyzed to derive the corresponding shape, and the component is generated through the analysis of the derived shape and the margin within the image. By inserting text and decorations into the generated component, the device creates the best design corresponding to the text and image input by the user.

Hereinafter, in inserting text into a component, attribute values related to text should be defined, and the relevant part will be described in detail. That is, the method of determining the attribute value of the text and inserting it into the component according to the result of the image analysis will be described in detail.

How to insert text according to image analysis

According to an embodiment of the present invention, the device may derive the emotion corresponding to the corresponding image through color analysis from the inserted image. Based on this, the style and font of the text corresponding to the derived emotion may be determined, and the decorative shape of FIG. 11 (see reference numeral 1100) and the shape of the adjunct may be determined. For example, a text style and a decorative shape associated with a circle may be used for a “soft” emotion, and a text style and a decorative shape associated with a rectangle may be used for a emotion corresponding to a “strong” emotion.

12 is a flowchart illustrating a method of determining an attribute value of text through image analysis.

Referring to FIG. 12, the device acquires an image recognized as valid in validation (S1210), and analyzes the acquired target image. At this time, emotion information of the target image may be extracted (S1220). According to an embodiment of the present invention, emotion information obtainable from an image may be obtained from a facial expression, a behavior of a model, and/or a color of all or part of an image.

Basically, emotions can be extracted based on facial recognition data. It can be largely divided into emotion factors of anger, contempt, disgust, fear, happiness, neutrality, sadness, and surprise. have. Each image may have scores for at least some of these eight emotion factors. Scores can be given from 0 to 1.0. The emotion information extraction algorithm for extracting the emotion factor can be evolved by matching the object or color in the image with the corresponding emotion score value to learn the machine. For example, it can be learned by generating (object-related information, emotion scores for each emotion factor) as learning data and inputting it into a deep learning model. The device may previously store text attribute values corresponding to the obtained emotional scores. For example, the primary classification of the font and the emotion data can be matched. To this end, an emotional matrix in the form of a regular polygon, which is generated by placing at least one emotion factor in one of up, down, left, and right directions, may be used.

According to an embodiment of the present invention, the first mode for defining the emotion factor that is the most exposed among the eight emotion factors as the emotion of the corresponding image, and the second mode for calculating the overall emotional value by combining the eight emotion factors Can be used. As a result of calculating the emotion value, when the emotion value is 0.5 or less, it can be regarded as not including emotion. Here, when the emotion values for the plurality of emotion factors are the same, emotions may be classified by smile values.

Then, a text style corresponding to the extracted emotion information is determined (S1225). The style can be basically divided into the style of Serifs and Sans Serif. Sans serif is a style in which the thickness does not change from the start to the end of the horizontal/vertical stroke. Serif is a style with a decorative serif at the end of the stroke. That is, the emotion value and the text style according to a specific emotion factor may be matched in advance. For example, when the emotion factor of happiness and surprise is determined as the emotion of the corresponding image by 0.5 or more, the style may be determined as "serif", and when sorrow and expressionlessness dominate, "sans serif".

Additionally, in one embodiment of the present invention, the device secondaryly matches the adjective image scale data to the matching result of the text's basic style (serif, sans serif) and emotion data (e.g., happiness, sadness, no expression, surprise, etc.) By matching the emotion and color of the image model, the text font can be matched. That is, a plurality of fonts may exist in the serif, and at this time, the plurality of fonts are assigned to the adjective group of the image scale, and included in the adjectives (eg, cute, neat, stylish, ..., etc.) corresponding to the image. The style and font of the text can be determined by the fonts.

Next, when the text style is determined, complexity information of the image or component is extracted (S1230), and the thickness attribute value of the corresponding text is matched (S1235). The higher the complexity of the image, the more highly readable text should be used, so if the complexity is high, bold text can be applied and if the complexity is low, thin text can be applied. That is, the complexity is divided into upper/middle/lower, and if "upper", "Bold", "mid", "Regular font", and "lower", "thin font" is applied. .

According to an embodiment of the present invention, the font of the text may be determined using complexity. For example, if the complexity of the component is high, a font with high readability can be controlled to use a font with high readability when the complexity of the component is low. Readability refers to the degree to which text is easily read, and readability refers to the degree to which the text is prominent in identifying and recognizing the shape of the font.

With regard to the method for calculating complexity, the device extracts tags (eg, related words) associated with objects included in the corresponding image, and calculates complexity based on the number of extracted tags. For example, if there are tags (including colors and adjectives) related to many related objects such as airplanes, clouds, buildings, people, mobile phones, heads, necks, arms, and legs, complexity increases. This can be done through a complexity extraction algorithm. In addition, a value related to the presence or absence of text included in an image, the number of objects included in the image, and the like may also be considered as a complexity calculation factor.

When the complexity is 26-30, it can be classified as "upper", 15-25 as "middle", and 14 or less as "lower". The criteria for classifying scores may vary depending on user settings. Then, among the plurality of fonts included in the previously determined text style, a font corresponding to each divided complexity may be determined as a font to be applied to the corresponding text.

As described above, the complexity calculated in this way can also be used to arrange components and determine whether text is inserted into components.

After calculating the complexity, the main color information of the image or component is extracted (S1240), and the corresponding text font attribute value is matched (S1245). The apparatus extracts the primary colors arranged in the image through color ratio calculation of color spectrum data extraction color distribution data of the image analysis module (not shown). Then, the extracted primary color can be used to determine the color and type of the text by matching the image sensitivity. At this time, it may be desirable to use the main color of the image as the main color of the shopping mall design. That is, although color may directly match font attribute values, it can be used to extract image emotion based on color theory, and can be used to indirectly select fonts by melting in sensitivity and tag complexity.

Next, the device extracts the brightness information of the image or component (S1250), and matches the color attribute value of the text (S1255). Brightness represents the light and dark degree of color. This brightness can affect the color of the text. Accordingly, the device may determine the color of the text based on the text color attribute value table corresponding to the pre-stored image brightness value. If the brightness is high, the image is in a bright state, so the color of the text may be a dark color corresponding to it. When the brightness is low, since the image is dark, it is preferable to use a noticeable color (eg, red color) for the text.

Then, the device may extract complementary color information of the image or component (S1260), and match the text highlight color attribute value (S1265). The device is capable of obtaining complementary color information based on the data of the primary color code values (information including hex codes, RGB values, and percentages) in the image analysis module, and using the complementary color information, emphasis on a screen displaying a shopping mall design It can be used for elements that you want to interact with. Complementary color is calculated through │(H value of main color + 180°)-360°│ based on the main color data. Using the complementary color information, the color of the highlighted area of the text can be determined. In particular, if the background color of the corresponding image is the main color, the highlighting part of the text is made white or black so that it can be emphasized. The highlighted part of the text can be extracted through morphological analysis and semantic analysis.

In addition, in a method using a color spectrum, similar content may be used to represent related content or information centering on an area using a primary color. For example, it can be used as a main/sub color of the final design. In addition, by using a complementary color (split complementary color) it can be a combination with the complementary color, it can be a color match to the portion where the complementary color is utilized. With respect to the shade color tone, in order to secure readability between the background and the text, the shade color of the background and the text may be determined based on a reference contrast value between the colors. Shading color transformation is a color spectrum that adds white/black/gray to the main color, and can be used to create various levels of brightness without changing the color based on the main color. In particular, when it is necessary to increase the color contrast with the text color when used as a background color, a set value may be used. An alternative highlight color can be considered a combination of dark shades and light shades.

The shaded gradient is used to secure text readability by applying a gradient effect to the text area to protect the text on the image. For example, by using the reference value of the shaded color as an example, a reference point of a contrast value between the background and the text is determined to give a text area a gradient effect based on the primary color to ensure readability of the text. In this case, the dark end of the gradient may be defined to have a opacity value according to the situation, the center point of the gradient may be defined as a position 3/10 closer to the dark end, and the end of the gradient may be defined to have zero opacity.

13A to 13B are exemplary views for explaining a process of matching attribute values of text and information obtained from an embedded image.

13A, the device may match a text style corresponding to the information extracted from the image. In the extracted information, since the neutral is highest at 0.619 and represents an emotion value higher than 0.5, the emotion of the image can be defined as expressionless, and in this case, the style of the text is defined as the sans serif corresponding to the expressionless expression. can do.

13B, the device can extract various tag information from an image. According to the embodiment of FIG. 13B, the device can extract about 30 tag information such as “outdoor”, “persoon”, and “wearing”, and since it is more than 30, it can be determined that the complexity is “up”. have. In this case, the Bold body corresponding to the complexity “upper” may be determined as the thickness attribute value of the text.

14 is a matching diagram for matching emotional vocabulary and image color in a method of automatically generating a shopping mall design according to an embodiment of the present invention.

Referring to FIG. 14, as described above, the device performs matching on two styles of sans serif and serif in one step and matching on an adjective image scale in two steps according to the emotion information of the image. Can be. At this time, the color distribution of the image may be used for the second-level emotion information.

The matching system of the color spectrum and the image scale of FIG. 14 may be used for matching for the two-step adjective image scale. Image scale is high by classifying adjectives into multiple depths. 1depth can be categorized as "soft", "static/cold", "dynamic/warm", "hard", in which 2depth is "cute", "neat", "stable", "natural" Etc. can be classified. 1depth and 2depth are related. For example, 1 depth of "soft" may include "cute", "neat", "natural", and 1depth of "hard" may include "heavy", "chic", "luxurious", and the like. In this way, if even deeper emotion information is extracted according to the depth relationship of emotion, the device determines the font of the text as one of the fonts corresponding to the emotion information of the corresponding depth.

15 is a table exemplarily showing a result of matching an attribute value of text based on emotion information and complexity information extracted from an image in a method for automatically generating a shopping mall design according to an embodiment of the present invention.

Referring to FIG. 15, the device extracts emotion data from an image or component using a face recognition data extraction algorithm. In this embodiment, since "happiness" is the highest at 0.992, it can be determined that "happiness" is the emotion of the corresponding image or component. The complexity is extracted through an image analysis tag data extraction algorithm, and the image can be determined to have 17 tags and a complexity of "medium".

Thus, in the embodiment of Fig. 15, the device determines the serif corresponding to happiness as the style of the text, and the complexity "medium" corresponds to the font with high readability, so the font with high readability is determined as the font of the text. Can be. In addition, the thickness of the text can be determined as "Regular" so as to correspond to the complexity "medium".

FIG. 16 is a conceptual diagram conceptually arranging a process of deriving the final result through an image/text merging process from an initial input image through a shopping mall design automatic generation method according to an embodiment of the present invention.

Referring to FIG. 16, an automatic image growth value of a shopping mall design may receive an original image 1610 and text information for work.

Then, based on the information related to the model of the image, the shopping mall design determines the validity, and if it is judged to be valid, inserts the image into the canvas grid, analyzes the object of the inserted image, derives the corresponding shape, and derives it. The component is created through the analysis of the margins in the created shape and image, and text and decoration are inserted into the created component.

At this time, the emotion information from the image can be extracted primarily based on the facial expression of the model. Then, the style of the text is determined by matching the text style information corresponding to the emotion (eg, sans serif). Then, the complexity of the image is extracted, and the thickness of the text is determined using the corresponding text thickness value.

In addition, the device may acquire secondary emotion information through color information (eg, primary color information) of the image. At this time, secondary emotion information (which corresponds to adjective emotion information using an adjective image scale) can be obtained, and the font of the text can be determined by combining it with complexity information. Additionally, the basic color value of the text may be determined based on the brightness information of the image, and the complementary color corresponding to the main color of the image may be extracted from the color spectrum to determine the highlight color of the text.

Then, the final design 1620 may be completed by converting text based on each determined text attribute value and inserting the converted text into the image 1610.

17 exemplarily shows a plurality of final design candidates.

Referring to FIG. 17, the device may generate a plurality of final design candidates and provide them to the user terminal. The final design candidates are designs implemented with different component arrangements and different attribute values of text in the component. The device provides a user terminal with a plurality of final design candidates rather than one, so that the user can make a selection according to preference.

Canvas grid system application

The canvas grid consists of a golden ratio layout considering the ratio based on the Fibonacci sequence. The golden ratio of the present invention is 1:1.618, which does not necessarily have to exactly match the ratio, and it may be desirable in that the ratio is adjusted to about 1:1.6 to 1:1.7. Then, a banner design is generated by inserting an image and text according to the determined layout.

As described above, according to an embodiment of the present invention, with respect to a grid system used in a device, the device is a breakpoint that adjusts space at different screen sizes of a user device and a control point based on a baseline grid Create a design based on (control point). In the following description of the canvas grid application part, "control point" is a broad control point, which is a reference point for controlling the grid system, and is understood as a concept including an image center point, an interaction point, and a consultation control point. It is preferred. Unless otherwise specified, it is preferable that the control points shown below are regarded as broad control points, not narrow control points, which control the start and end of the input of text in FIG. 4. These broad control points can exist in the same number in different modes of the grid system. The web grids that the device can use can create visual consistency between layouts in the design, where the number of grids can vary depending on the breakpoint scheme.

18 is a view showing a breakpoint of a canvas grid system used in a method for automatically generating a shopping mall design according to an embodiment of the present invention.

Referring to FIG. 18, the device uses a 6 grid canvas grid system for a display screen of 600 px or less (a display size of a user terminal, an object that should correspond to the canvas grid system), and a display screen of 600 px or more, 12 grid canvas grid system can be used. For example, a 6-grid system may be applied to 480px and 600px, and 12 grid systems may be applied to 840px, 960px, 1280px, 1440px, and 1920px. The 6 grid system represents a system that divides the screen into 6 columns to form a grid, and the 12 grid system represents a system that divides the screen into 12 columns to form a grid.

In addition, according to one embodiment of the present invention, all components are adjusted to a square baseline grid for mobile, tablet, and desktop. Here, the baseline grid may be changed according to the production environment. In the case of a 1200px production environment, a unit of 1 grid may be defined as 10px X 10px. In addition, a broad control point can be generated at the contact portion of the baseline grid, which can be defined as an area of 5 grids horizontally and 3 grids vertically. It is desirable to have a margin of 2 grids between control points.

19 is a conceptual diagram illustrating a single grid and a single control point of a canvas grid system used in a method for automatically generating a shopping mall design according to an embodiment of the present invention.

Referring to FIG. 19, the module grid is a sub-concept of the web grid, and based on 1200px, 1G may have a size of 10px X 10px. It can be variable depending on the horizontal and vertical size. 10 X 10 is also possible, but on devices with large vertical sizes, 8 X 12 is also possible.

On one screen, the number of broad control points can be defined constant. One control point may have a width of 5G and a height of 3G (where G represents a grid). Basically, if a control point of a fixed number is placed on a grid array that can have a variable size, a basic grid system is created.

According to an embodiment of the present invention, as the most basic canvas grid system, the entire screen is composed of 120G X 74G, and a system in which 10px X 10px constitutes one grid can be used.

20 is a view showing the configuration of a control point on a canvas in 1200 grid mode.

Referring to FIG. 20, the device may generate a grid system such that there is a preset number of broad control points on the canvas. Here, the canvas may arrange control points such that 224 control points exist. One control point is 5G X 3G, and there is a margin of 2G in the horizontal and vertical directions between each control point. On the herpes of these control points, as described in FIG. 4 above, a small number of control points (eg, 3 image center points, 7 interaction points, and 9 consultation control points) may be disposed rather than 224.

21 is a view showing a control center (central reference plane) and a component area in a 120 x 74 grid mode.

Referring to FIG. 21, the component area may basically mean an area in which text and/or decorative shapes are arranged. According to an embodiment of the present invention, a grid mode of 120G X 74G may be applied to 1200px X 740px, and as described above, 224 of 16 horizontal and 14 vertical control points may be disposed. At this time, the central reference plane is preferably an area in which four control points in the center are present, and the component region is preferably set to be an area excluding the outermost margin and excluding the central reference plane. However, it is not necessary to exclude margins.

At this time, there may be two component areas, one on the center surface and two on the left and right sides (total of three), wherein the left and/or right component areas are horizontal 5 located inside, excluding the outermost control point. It can be an area defined by 12 control points.

22A to 22C are conceptual views illustrating features having different grid sizes according to device breakpoints in the horizontal direction.

Referring to FIG. 22A, in the canvas grid system according to an embodiment of the present invention, the horizontal size of one grid may have a size of “control breakpoint/120”. For example, a device with a width of 1200px is preferably a system based on a grid having a horizontal size of "1200/120=10px". Therefore, the size of the horizontal direction changes at 1080px, 960px, 840px, ... 240px, 120px.

The endpoint of the device may differ slightly from the control endpoint. That is, the end point of the device is a value associated with the size of the display screen of the device, divided into units of about 100 to 110px, the first section is 1200 to 1100px, the second section has a range of 1099px to 990px, and the third section is 989 It can have a value of ~880px.

The table is as follows.

Control breakpoint Horizontal (1 GRID) device Control breakpoint Horizontal (1 GRID) device width 1200px 10px ~1100px width 600px 5px 659px~550px width 1080px 9px 1099px~990px width 480px 4px 549px~440px width 960px 8px 989px~880px width 360px 3px 439px~330px width 840px 7px 879px~770px width 240px 2px 329px~220px width 720px 6px 769px~660px width 120px 1px Minimum unit

The pixel size can be converted according to the breakpoint of the device. According to the embodiment of FIG. 22A, it is stipulated that a grid system based on a grid of 10 px horizontally is introduced with 100 px as a variable value in a section of 1100 to 1200 px based on 1100 (see FIG. 22B). However, in the case of 1099px, it may be desirable to introduce a grid system based on 9px (see FIG. 22C). In this way, in addition to the basic grid system defined by the control breakpoint, the grid system applied based on the device breakpoint may be different. At this time, based on the existence of 120 grids based on a width of 1200px, grids before and after the breakpoint The number of is variable. However, even at this time, as described above, the number of broad control points does not change. That is, the number of control points is fixed, and only the number of grids is variable. In addition, the grid system may be operated in a manner of maintaining a grid of 1200px when it is 1201px or more, and extending a margin area in a 1200px-based grid.

Moreover, after belonging to the corresponding breakpoint, if the area of the entire control point is aligned to the center and falls odd, it is desirable to process the remaining pixel values with a right margin.

23 is a view showing a device breakpoint in the vertical direction.

The grid size in the vertical direction is calculated through "1G = control break point/74", unlike the grid size calculation in the horizontal direction of FIGS. 22A to 22C. Control breakpoints can be assigned to 1184px, 1110px, 1036px, 962px, 888px, ... 148px, 74px. The following table shows the control breakpoint and 1 grid pixel value per device.

Control breakpoint Vertical
(1 GRID) device Control breakpoint Vertical
(1 GRID) device height 1184px 16px ~1088px height 592px 8px 611px~544px height 1100px 15px 1087px~1020px height 518px 7px 543px~476px height 1036px 14px 1087px~952px height 444px 6px 475px~408px height 962px 13px 951px~884px height 370x 5px 407px~340px height 888px 12px 951px~816px height 296px 4px 339px~272px height 814px 11px 815px~748px height 222px 3px 271px~204px height 740px 10px 747px~680px height 148px 2px 203px~136px height 666px 9px 679px~612px height 74px 1px Minimum unit

Referring to FIG. 23, since 680px is a device breakpoint, a device having a height of 680 to 740px has a height of one grid in 74G mode of 10px. However, in a device having a height of 679px, it is preferable to apply a grid system having a grid size smaller in the form of a height of 9px in one grid in 74G mode. In other words, according to the variable height value of the broad control point, the number of grids varies before and after the breakpoint. In addition, the height of the control point may also be varied according to the size of the variable grid. In addition, after belonging to the corresponding breakpoint, it is desirable to center the entire control point area and, if it falls odd, the remaining pixel values are treated as a bottom margin so that the image is not affected.

Multi-segment layout for inserting multiple images

FIG. 24 is a diagram showing a layout configuration in which a ratio based on Fibonacci sequence is combined with a grid system.

Referring to FIG. 24, the device utilizes a golden ratio layout in which the concept of a Fibonacci sequence and a 120G x 74G system defined as a basic canvas grid system are combined. In other words, in the layout, the principle of balance and ratio is applied.

The device, after constructing the canvas, applies a grid system within the canvas. At this time, it is preferable to determine the size of the grid system and the grid corresponding to the screen size of the device in consideration of the device end point.

Then, each section is divided by considering the golden ratio based on the Fibonacci sequence in the applied grid system. At this time, the division and division type of the section may be determined in consideration of the number of input images. For example, if there are two input images, a two-part layout, and three, a three-part layout can be used. The layout defines an arrangement of sections to which individual images are applied, and the defined sections may be applied with a Fibonacci sequence based golden ratio for at least one of the horizontal and vertical directions. The creation of a component and the insertion of text within a section are similar to the process described above.

In addition, after the section is divided, one section may be divided into a plurality of subsections, and individual images may be independently inserted into the divided subsections. For Fibonacci sequence based ratio, ie 1:1.618 can be applied. In some cases, a 1:1 ratio may also be applied.

25 is an exemplary view showing a two-part layout in the horizontal direction and a three-part layout in the horizontal direction.

Referring to FIG. 25, the device determines a 2-part layout and a 3-part layout according to the Fibonacci sequence based golden ratio. The two-part layout may consider the form of dividing the A section and the B section in a ratio of 1:1.618 in the horizontal direction. In addition, the form of dividing the A section and the B section in a ratio of 1:1.618 in the vertical direction may be considered, but in the normal case, since the device is a long rectangular shape in the horizontal direction, the number of considerations for dividing in the vertical direction is less Can be. This is adaptively determined according to the environment of the device.

In the case of the three-part layout, the section A having the largest area has a horizontal size of 1:1.618 in the horizontal direction and a ratio corresponding to 1.618, but may have a square shape having horizontal and vertical lengths. Then, it is preferable to divide the area corresponding to the remaining 1 into two sections (the section having the larger area is the C section, and the section having the smaller area is the D section) in consideration of the 1:1.618 ratio in the vertical direction.

According to an embodiment of the present invention, a section A of a square may be divided into 1:1 in a horizontal direction to generate an E section, and may be arranged side by side with the B section. At this time, it is possible to consider placing two E sections together on the left side of the B section, and considering placing two E sections together on the right side of the B section, centering the B section, and having two E on each side. You may also consider arranging sections.

The apparatus may generate a multi-partition layout that is 4 to more severe by applying a golden ratio to the above-described two-part layout and three-part layout. The determination of the division layout may be set by the user how many division layouts to be used, or may be selected in consideration of the number of division sections automatically according to the number of input images to be selected. Or, by collecting data on the input image and the resulting layout of the final shopping mall design and inputting and learning it into a deep learning model, a more advanced layout can be derived.

With regard to the area of the divided layout, the device can be arranged alphabetically from the area having the largest width (width x height) (A section, B section, ..., Z section). The ratio of the number of grids in the horizontal and vertical directions of each section may represent the golden ratio. For example, in the case of sections A and B of the two-part layout on the upper left of FIG. 25, the horizontal size of the A section represents 74G, and the horizontal ratio of the B section represents 46G. This represents a ratio of 1.618:1. In addition, in the layout consisting of the A, C, and D sections at the upper left of the three-part layout, the ratio of the horizontal size of the A and C or A and D sections is also 74G to 46G, representing the golden ratio, and the C and D sections Also, the ratio of the vertical size of C is 46G for the C section and 28G for the D section, maintaining a ratio of 1.618:1.

FIG. 26 is an exemplary view showing an exemplary appearance of a shopping mall design completed by inserting images and text into the two-part layout and the three-part layout of FIG. 25.

As shown in FIG. 26, the device may insert individual images in each section or subsection in the determined divided layout, and also insert text.

At this time, the insertion of the text is inserted into the image after being inserted onto the individual images, and after the insertion of the individual images into the section is completed, the text is inserted independently, and the text is inserted in a form that spans multiple images. It can be performed by one of the methods. This can be considered in various ways depending on the user setting. In this case, it is possible to control the text to be inserted beyond the image in consideration of the central reference plane of the canvas grid system and the eye position information of the multiple models in the multiple images.

27 is a detailed flowchart illustrating a design insertion process according to the size of a divided layout section of a method for automatically generating a shopping mall design according to an embodiment of the present invention.

Referring to Figure 27, the device generates a canvas (S2710). Then, the size information of the canvas (proportional to the screen size of the device) is extracted. Then, the device determines a division layout by determining a section suitable for the number and shape of divisions (S2720). In this case, there may be a preset layout, otherwise, the number of sections and the arrangement of sections may be determined adaptively according to the number of selected images.

According to another embodiment of the present invention, when a plurality of results are listed, a divided layout corresponding to a predetermined ratio may be applied according to a theme of the promotion. For example, a probability that a two-part layout is applied to a promotional topic related to a discount/sale may be set to 30%. The applicability of the 2-part layout is considered 60% for promotional topics related to new products/seasons, 70% for brands/categories, 5% for free gifts/points, 5% for SNS/members, anniversaries/officials In relation to the event, it may be set to apply 20% and 5% for free shipping. In addition, for the first type (A+C+D) of the three-part layout, 50% for discount/sale, 25% for new products/season, 13% for brand/category promotions, etc. And public relations topics have a connection, and corresponding applicability may be pre-set. Another applicability of the second form (B+E+E) may be considered. The degree of applicability of the divisional layout for each promotion subject input through the user interface of FIG. 2 may be arbitrarily changed through user setting. Fibonacci sequence-based ratios may be considered in the arrangement of sections belonging to the split layout determined in this way.

After determining the split layout, the device calls the canvas grid system by the device breakpoint.

Then, the size information (horizontal and vertical size) of the canvas extracted in the previous process is compared with the size information of the called canvas grid system grid (S2730). If the difference between the horizontal size of the grid system and the horizontal size of the device screen is divided by the number of divisions based on the horizontal section of the corresponding section, the number related to the horizontal zoom is displayed. When the remaining value occurs, it is preferable to enlarge/reduce the quotient value from the right value to the left by 1px by the horizontal value after expanding/reducing the quotient by the divided area. For example, in the case of size comparison for section A, if the horizontal size (SGw) of the grid system is 960, the horizontal size (Cw) of the canvas is 968, and the number of divisions is 2, (SGw-Cw)/fraction = ( 960-968)/2 results in "-4". At this time, the negative number means enlargement, so it is preferable to enlarge the horizontal direction of the A section by 4 pixels.

When the size comparison in the horizontal and vertical directions of the grid system and the device screen size is completed through the above process, the apparatus calculates each section size information based on the grid system to be applied to the device screen size. For example, when the size of the grid is 8px in the horizontal and vertical directions, the A section results in (Gw*74)(Gh*74)=592px*592px. Then, based on the previous comparison result, substituting the zoom value for each section, in the case of section A, the horizontal size of 596px is 592px + 4px. If you obtain the vertical size in the same way, 600px may appear. When the size of each section is determined, an individual image corresponding to each section is inserted (S2750).

With regard to the insertion of images per section, the device considers priorities in the image insertion order to put more important images in a large area section. In the foregoing, relative scores for each selection factor when selecting an input image may be comprehensively considered, or an image that satisfies a specific promotional topic and/or purpose may be preferentially selected. For example, in relation to a new product/season, an image containing the product may be preferentially selected and inserted into the A section. Then, the device extracts and recognizes objects in the image through the object recognition algorithm, and if a product related to publicity among the recognized objects is included in the image, the image may be placed in priority. At this time, if there are multiple images containing the product related to the promotion, the image that discloses the product more clearly and more clearly may have a relative priority. If the product is not included, the overall score according to the factors related to the input image selection may be considered secondary.

With respect to the insertion of text, the text may be implemented in the layout in a form that is first inserted into a specific image (ie, the image and text are pre-merged), or may be implemented independently in the layout separately from the embedded image. At this time, if the key word of the input text and the result of object recognition in a specific image match, the corresponding text can be arranged on the matched image. At this time, if the semantic analysis results of the key words of the plurality of images and the input text are the same, the text may be displayed over the plurality of images, and the text may be controlled to be displayed only in the image having a higher priority.

Prior to the insertion of the image, in the relationship between the image and the canvas, if the image size is smaller than the canvas, zoom in, and conversely, if the image size is larger than the canvas, zoom out. At this time, an image sharpening effect is applied in order to prevent quality degradation due to image enlargement. In addition, it can be controlled so that the margin can be solved by inverting left and right. Also, it may be considered to extract the cross-sectional color of the image. In addition, the primary color among image analysis data may be used to designate the background color of the entire canvas.

Create a design considering the optimal size for various web pages

FIG. 28 is a production size table that is standardized in the form of a design of a specified size when a shopping mall design is utilized in a specific channel such as advertisement/SNS in the visual element of the method for automatically generating a shopping mall design.

Referring to FIG. 28, the apparatus applies a grid system suitable for manufacturing size. That is, a standardized production size may be required to apply a suitable grid system. In order to generate a design for uploading to a specific shopping mall, it is desirable to create a design based on data input by a user according to the purpose of the brand site. That is, depending on whether the design is used for planning, banner, pop-up screen, detailed page, or representative image, the user can enter a size corresponding to the design and create a design.

For other advertising purposes, Google DA (Google Display Network Advertisement) may be considered as an example. The device is used to create a design for upload of Google DA, pre-stored 120*600, 160*600, 200*200, 240*400, 250*250, 300*50, 300*250, 300*600, 320* Define selectable size items up to 50, 320*100, 336*280, 468*60, 728*90, 970*250, and 970*90, and design appropriately in response to the user's selection among the defined size items Can generate

In the case of Direct Mail (DM), a size of "640*free" can be defined and a design can be created.

If you want to create a shopping mall design for uploading to SNS, you can upload it to Facebook, Instagram, Line, etc., and you can upload designs of different sizes for each SNS platform. In particular, Facebook and Instagram can be defined as one of the sizes 600*600, 1080*1080, 1200*444, 1200*628, 1200*900, 1920*1080. In the case of a line, it may be defined as a size of 1040*1040 or 1200*628.

As described above, in the case of a design utilized in a specific channel, a designated size and a design form may be standardized, and an optimal shopping mall design size may be determined by correlating with a previously stored size standard only with a production purpose specified by a user. Then, the device can predict the result of each platform in advance through the size information, and select a grid and a layout type of the design suitable for the design generation process.

Shopping mall design automatic generation device

29 is a block diagram showing a shopping mall design automatic generation device according to an embodiment of the present invention. As illustrated in FIG. 29, the apparatus may include a communication unit 2910, a processor 2920, a memory 2930, and an input/output module 2940.

Referring to FIG. 29, the communication unit 2910 is a component for exchanging information with a user terminal through the network 120 of FIG. 1. The communication unit 2910 includes a communication device associated with a wired or wireless network. The communication unit 2910 may include an antenna.

The processor 2920 is a component for obtaining a design generation request received from a user terminal through the communication unit 2910 and other information related to design generation, and generating a design according to programming. The processor 2920 executes a program stored in the memory 2930. The processor 2920 includes an image analysis module (not shown) that performs image-related processing such as object analysis, margin analysis, and face tracking in an image, and a module (not shown) for morpheme analysis and semantic analysis of text. As described above, the processor 2920 verifies the validity of the image to be inserted, which is obtained from the user terminal, and inserts the image into the canvas grid. Then, the processor 2920 analyzes an object of the inserted image to derive a corresponding shape, and generates a component in the canvas through analysis of the derived shape and margins in the image. The processor 2920 inserts text and decorations into the generated component, thereby creating the best design.

The memory 2930 stores instructions associated with programs to be performed by the processor 2920 and is a storage device that stores various data required by the processor 2920. The memory 2930 may be implemented as a local memory inside the device or a large database outside.

The input/output module 2940 includes information input means such as a keyboard and a mouse, and information output means such as a monitor, a TV, and a touch screen. The input/output module 2940 is used to change various setting values related to design creation and display related contents.

The system or device described above may be implemented with hardware components, software components, and/or combinations of hardware components and software components. For example, the systems, devices, and components described in the embodiments include, for example, processors, controllers, arithmetic logic units (ALUs), digital signal processors (micro signal processors), microcomputers, and field programmable arrays (FPAs). ), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions, may be implemented using one or more general purpose computers or special purpose computers. The processing device may run an operating system (OS) and one or more software applications running on the operating system. In addition, the processing device may access, store, manipulate, process, and generate data in response to the execution of the software. For convenience of understanding, a processing device may be described as one being used, but a person having ordinary skill in the art, the processing device may include a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that may include. For example, the processing device may include a plurality of processors or a processor and a controller. In addition, other processing configurations, such as parallel processors, are possible.

The software may include a computer program, code, instruction, or a combination of one or more of these, and configure the processing device to operate as desired, or process independently or collectively You can command the device. Software and/or data may be interpreted by a processing device, or to provide instructions or data to a processing device, of any type of machine, component, physical device, virtual equipment, computer storage medium or device. , Or may be permanently or temporarily embodied in the transmitted signal wave. The software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored in one or more computer-readable recording media.

The method according to the embodiments may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer readable medium. The computer-readable medium may include program instructions, data files, data structures, or the like alone or in combination. The program instructions recorded in the medium may be specially designed and configured for the embodiments or may be known and usable by those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs, DVDs, and magnetic media such as floptical disks. -Hardware devices specifically configured to store and execute program instructions such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language code that can be executed by a computer using an interpreter, etc., as well as machine language codes produced by a compiler. The hardware device described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

As described above, although the embodiments have been described by a limited embodiment and drawings, those skilled in the art can make various modifications and variations from the above description. For example, the described techniques are performed in a different order than the described method, and/or the components of the described system, structure, device, circuit, etc. are combined or combined in a different form from the described method, or other components Alternatively, even if replaced or substituted by equivalents, appropriate results can be achieved.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (13)

In the method for automatically generating a design associated with an online shopping mall,
Preparing a canvas grid for inserting at least one image associated with a shopping mall, wherein the canvas grid refers to a grid structure on the canvas which is a space into which the at least one image is inserted; And
And generating a final design by inserting the at least one image and text interlocked with the image into the prepared canvas grid,
The step of preparing the canvas grid,
Generating in the horizontal and vertical directions a plurality of reference lines for multi-dividing the area of the canvas with a golden ratio based on a Fibonacci sequence on the canvas grid; And
And generating points for determining an arrangement of the at least one image on at least some of the contact points formed by the plurality of reference lines. The method of claim 1, wherein generating the points determining the placement of the at least one image comprises:
i) an image center point for centering the at least one image, ii) an interaction point for controlling linkage between components to which text associated with the image is input, and iii) the text And generating a control point for controlling an input start point and an input end point of the design. According to claim 2,
The image center point is a method for automatically generating a design associated with a shopping mall that is disposed on three quadrant reference lines that divide the canvas evenly in the vertical direction. The method of claim 3,
The image center point is composed of a plurality,
At least some of the plurality of image center points include a shopping mall including a first image center point present in the center of the canvas and second and third image center points spaced apart from both sides of the first image center point; How to automatically generate related designs. The method of claim 4,
The center points of the second and third images are a shopping mall existing at a contact point between two longest diagonal lines connecting two vertices in the diagonal direction of the canvas and two quadrant reference lines except the center one of the quadrant reference lines. How to automatically generate related designs. The method of claim 4,
The first image center point is on a central quadrant baseline crossing the center of the canvas,
The first image center point, in the vertical direction, the second and third image center point, the same height as a straight line or a design automatic generation method associated with a shopping mall existing above the straight line. The method of claim 6,
When inserting the at least one image into the canvas grid,
By analyzing the object in the image to be inserted, the first to the first, depending on whether the position of the face exists in the center area, in the center area, on the left side from the center area, or on the right side from the center area, in the vertical direction of the canvas. 3 A method for automatically generating a design associated with a shopping mall that places the face of the image at one of the image center points. The method of claim 3,
The interaction point is composed of a plurality,
At least some of the plurality of interaction points,
A method for automatically generating a design associated with a shopping mall that is disposed on at least a portion of an evenly divided reference line that divides the canvas evenly in the vertical direction and two longest diagonal lines of the canvas. The method of claim 8, wherein at least some of the plurality of interaction points,
i) 4 contact points of the left and right 8-division reference lines and the diagonal line among the 7 8-division reference lines that divide the canvas evenly in the vertical direction;
ii) two of the four corners forming a virtual square block created by connecting the four contacts, and two contacts where a straight line dividing the canvas evenly in the horizontal direction meets; And
iii) A method for automatically creating a design associated with a shopping mall placed on the center point of a canvas. According to claim 1,
The plurality of reference lines is a method for automatically generating a design related to a shopping mall including a plurality of straight lines such that at least one of a horizontal split ratio, ii) vertical split ratio, and iii) horizontal and vertical ratio is a golden ratio. The method of claim 1, wherein the plurality of reference lines,
An equally divided reference line comprising at least a portion of a dividing reference line dividing the canvas evenly in the horizontal and vertical directions, a dividing reference line dividing the canvas, and an 8 dividing reference line dividing the canvas; And
A method for automatically generating a design associated with a shopping mall including a diagonal reference line randomly connecting at least a portion of two end points each of the four vertices of the canvas and the evenly divided reference lines. In the design automatic generation device associated with the online shopping mall,
A communication unit that receives a request for automatically generating a design from a user terminal and provides the generated final design; And
Prepare a canvas grid for inserting at least one image associated with a shopping mall in response to the design auto-generation request, wherein the canvas grid means a grid structure on the canvas, which is a space in which the at least one image is inserted. And a processor for inserting the at least one image and text interlocked with the image into the prepared canvas grid to generate a final design,
The processor,
In the horizontal and vertical directions, generating a plurality of reference lines for multi-dividing the area of the canvas with a golden ratio based on a Fibonacci sequence on the canvas grid; And
An apparatus for automatically designing a shopping mall associated with a shopping mall that generates points determining at least a portion of the at least one image on at least some of the contact points formed by the plurality of reference lines. In the design automatic generation system associated with the online shopping mall,
A user terminal that transmits a request for automatically generating a design and receives a final design corresponding to the request; and
In response to a request for automatically generating a design from the user terminal, a canvas grid for inserting at least one image associated with a shopping mall-a canvas grid means a grid structure on a canvas that is a space in which the at least one image is inserted. Including-a shopping mall design automatic generation device for preparing the final design by inserting the at least one image and text interlocked with the image into the prepared canvas grid,
The shopping mall design automatic generation device,
In the horizontal and vertical directions, generating a plurality of reference lines for multi-dividing the area of the canvas with a golden ratio based on a Fibonacci sequence on the canvas grid; And
An automatic design generation system associated with a shopping mall that generates points that determine the placement of the at least one image on at least some of the contact points formed by the plurality of reference lines.

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