Electronic device for providing an image to a digital picture frame and operating method thereof

Abstract

An electronic device for providing an image to a digital photo frame and a method of operating the same are disclosed. The method of operating the electronic device may include: receiving input information related to an image to be output through a digital photo frame from a user; determining a training data set composed of at least one search image based on a keyword regarding the space where the digital photo frame is located among the received input information and a category regarding the type of image to be output through the digital photo frame; acquiring an image to be output through the digital photo frame based on an image of the surrounding environment regarding the space where the digital photo frame is located among the received input information and the determined training data set; and transmitting the acquired image to the digital photo frame.

Description

Technology Field

[0001] Embodiments of the present invention relate to an electronic device that provides an image to a digital picture frame and a method of operating the same. Background Technology

[0002] Digital photo frames are electronic devices that display images desired by the user, primarily used for interior decoration in places that frequently change images, such as art museums, galleries, or cafes. Digital photo frames can display images pre-stored in the device's internal storage or images transmitted from an external source. While such digital photo frames allow for the easy changing and display of various types of images, there was a problem involving the inconvenience of users having to manually search for images that match the surrounding environment.

[0003] The information described above may be provided as related art for the purpose of aiding understanding of the present disclosure. No claim or determination is made as to whether any of the foregoing may be applied as prior art related to the present disclosure. The problem to be solved

[0004] The present invention can provide a device and method for outputting an image that matches the surrounding environment through a digital picture frame.

[0005] The present invention can provide a device and method for recognizing the surrounding environment through an artificial intelligence model and recommending or generating an image to be output through a digital picture frame.

[0006] However, technical challenges are not limited to the technical challenges described above, and other technical challenges may exist. means of solving the problem

[0007] According to one embodiment of the present invention, an electronic device comprises one or more processors; and one or more memories for storing instructions executable by the one or more processors. When at least some of the instructions stored in the one or more memories are executed by the one or more processors, the at least some of the instructions executed can be controlled to perform the following operations: receiving input information related to an image to be output through a digital picture frame from a user; determining a training data set composed of at least one search image based on a keyword regarding the space where the digital picture frame is located and a category regarding the type of image to be output through the digital picture frame among the received input information; acquiring an image to be output through the digital picture frame based on an image of the surrounding environment regarding the space where the digital picture frame is located among the received input information and the determined training data set; and transmitting the acquired image to the digital picture frame.

[0008] The operation of determining the above training data set may include the operation of collecting search images including frames based on keywords for the space and categories for the types of images.

[0009] The operation of acquiring the above image may include: an operation of measuring a first similarity between the encoding result of search images constituting the training data set converted into a latent space using a pre-trained autoencoder and the encoding result of the surrounding environment image; an operation of measuring a second similarity between a histogram of RGB values ​​of search images constituting the training data set and a histogram of RGB values ​​of the surrounding environment image; an operation of measuring a third similarity between the number of objects of search images constituting the training data set and the number of objects of the surrounding environment image; and an operation of selecting the search image with the highest similarity to the surrounding environment image as a recommended image using the measured first similarity, second similarity, and third similarity.

[0010] The operation of acquiring the above image may further include an operation of determining whether to re-select the recommended image based on the histogram difference for RGB values ​​between the selected recommended image and the surrounding environment image or the number of objects included in the surrounding environment image.

[0011] The operation of determining whether to re-select the recommended image may include the operation of re-selecting the recommended image when the correlation coefficient between the histogram of the RGB values ​​of the selected recommended image and the histogram of the RGB values ​​of the surrounding environment image is less than a preset threshold.

[0012] The operation of determining whether to re-select the recommended image may include an operation of re-selecting the recommended image based on the number of objects included in the surrounding environment image and a preset threshold.

[0013] The operation of acquiring the above image may include an operation of modifying the selected recommended image using weather information or seasonal information.

[0014] The operation of acquiring the above image may include: an operation of acquiring keywords related to the atmosphere of the surrounding environment image of the space where the digital picture frame is located among the received input information; and an operation of generating an image to be output through the digital picture frame in response to inputting keywords related to the atmosphere of the surrounding environment image, keywords regarding the space where the digital picture frame is located, and categories regarding the type of image to be output through the digital picture frame into a generative AI model.

[0015] The operation of acquiring the above image may include: an operation of extracting the color tone of an image of the surrounding environment for the space where the digital picture frame is located among the received input information; an operation of searching for a specific image based on the extracted color tone; an operation of configuring a palette according to the ratio of the extracted color tone; an operation of receiving a drawing image drawn using the configured palette; and an operation of generating an image to be output through the digital picture frame in response to inputting the searched specific image and the received drawing image into a generative AI model.

[0016] The digital photo frame described above includes a display for outputting the acquired image and a frame that is detachable from the display, and the acquired image can be displayed through the display by adjusting its size according to the size of the frame.

[0017] The digital photo frame includes an illuminance sensor and can adjust the brightness of the display based on ambient brightness information measured through the illuminance sensor.

[0018] The digital photo frame includes a human body detection sensor and can determine whether to operate the display in power-saving mode based on whether a user is present, as measured by the human body detection sensor.

[0019] A method of operation of an electronic device according to an embodiment of the present invention may include: receiving input information related to an image to be output through a digital picture frame from a user; determining a training data set composed of at least one search image based on a keyword regarding the space where the digital picture frame is located and a category regarding the type of image to be output through the digital picture frame among the received input information; acquiring an image to be output through the digital picture frame based on an image of the surrounding environment regarding the space where the digital picture frame is located among the received input information and the determined training data set; and transmitting the acquired image to the digital picture frame.

[0020] The operation of determining the above training data set may include the operation of collecting search images including frames based on keywords for the space and categories for the types of images.

[0021] The operation of acquiring the above image may include: an operation of measuring a first similarity between the encoding result of search images constituting the training data set converted into a latent space using a pre-trained autoencoder and the encoding result of the surrounding environment image; an operation of measuring a second similarity between a histogram of RGB values ​​of search images constituting the training data set and a histogram of RGB values ​​of the surrounding environment image; an operation of measuring a third similarity between the number of objects of search images constituting the training data set and the number of objects of the surrounding environment image; and an operation of selecting the search image with the highest similarity to the surrounding environment image as a recommended image using the measured first similarity, second similarity, and third similarity.

[0022] The operation of acquiring the above image may further include an operation of determining whether to re-select the recommended image based on the histogram difference for RGB values ​​or the difference in the number of objects between the selected recommended image and the surrounding environment image.

[0023] The operation of acquiring the above image may include an operation of modifying the selected recommended image using weather information or seasonal information.

[0024] The operation of acquiring the above image may include: an operation of acquiring keywords related to the atmosphere of the surrounding environment image of the space where the digital picture frame is located among the received input information; and an operation of generating an image to be output through the digital picture frame in response to inputting keywords related to the atmosphere of the surrounding environment image, keywords regarding the space where the digital picture frame is located, and categories regarding the type of image to be output through the digital picture frame into a generative AI model.

[0025] The operation of acquiring the above image may include: an operation of extracting the color tone of an image of the surrounding environment for the space where the digital picture frame is located among the received input information; an operation of searching for a specific image based on the extracted color tone; an operation of configuring a palette according to the ratio of the extracted color tone; an operation of receiving a drawing image drawn using the configured palette; and an operation of generating an image to be output through the digital picture frame in response to inputting the searched specific image and the received drawing image into a generative AI model. Effects of the invention

[0026] According to one embodiment of the present invention, by recommending or generating an image that matches the surrounding environment based on an artificial intelligence model, the inconvenience of the user having to find an image to be displayed through a digital photo frame can be reduced.

[0027] According to one embodiment of the present invention, by providing an image to be output through a digital picture frame based on an artificial intelligence model, the user can increase the opportunity to encounter diverse and fresh images. Brief explanation of the drawing

[0028] In relation to the description of the drawings, the same or similar reference numerals may be used for identical or similar components. FIG. 1 is a schematic diagram of a digital photo frame providing system according to an embodiment of the present invention. FIG. 2 is a diagram illustrating the configuration of an electronic device according to an embodiment of the present invention. FIG. 3 is a flowchart illustrating the detailed operation of an electronic device that provides an image to a digital picture frame according to an embodiment of the present invention. FIG. 4 is a diagram illustrating a data collection method for a training data set according to an embodiment of the present invention. FIG. 5 is a diagram showing the structure of a digital picture frame according to an embodiment of the present invention. FIG. 6 is a flowchart illustrating the search image recommendation operation of an electronic device that provides an image to a digital picture frame according to an embodiment of the present invention. FIG. 7 is a diagram illustrating a first similarity determination method for search images constituting a training data set according to an embodiment of the present invention. FIG. 8 is a diagram illustrating a second similarity determination method for search images constituting a training data set according to an embodiment of the present invention. FIG. 9 is a diagram illustrating a third similarity determination method for search images constituting a training data set according to an embodiment of the present invention. FIG. 10 is a flowchart illustrating an image generation operation using a recommended image of an electronic device that provides an image to a digital picture frame according to an embodiment of the present invention. FIG. 11 is a flowchart illustrating an image generation operation using the atmosphere of the surrounding environment of an electronic device that provides an image to a digital picture frame according to an embodiment of the present invention. FIG. 12 is a flowchart illustrating an image generation operation based on the ambient color tone of an electronic device that provides an image to a digital picture frame according to an embodiment of the present invention. Specific details for implementing the invention

[0029] Specific structural or functional descriptions of the embodiments are disclosed for illustrative purposes only and may be modified and implemented in various forms. Accordingly, actual implementations are not limited to the specific embodiments disclosed, and the scope of this specification includes modifications, equivalents, or substitutions included in the technical concept described by the embodiments.

[0030] Terms such as "first" or "second" may be used to describe various components, but these terms should be interpreted solely for the purpose of distinguishing one component from another. For example, the first component may be named the second component, and similarly, the second component may be named the first component.

[0031] When it is stated that a component is "connected" to another component, it should be understood that it may be directly connected to or coupled with that other component, or that there may be other components in between.

[0032] Singular expressions include plural expressions unless the context clearly indicates otherwise. In this document, phrases such as “A or B,” “at least one of A and B,” “at least one of A or B,” “A, B or C,” “at least one of A, B and C,” and “at least one of A, B, or C” may each include any one of the items listed together with the corresponding phrase, or all possible combinations thereof. In this specification, terms such as “comprising” or “having” are intended to designate the existence of the described feature, number, step, action, component, part, or combination thereof, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0033] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in this specification.

[0034] Hereinafter, embodiments will be described in detail with reference to the attached drawings. In the description with reference to the attached drawings, identical components are given the same reference numeral regardless of the drawing number, and redundant descriptions thereof will be omitted.

[0036] FIG. 1 is a schematic diagram of a digital photo frame providing system according to an embodiment of the present invention.

[0037] Referring to FIG. 1, a digital photo frame providing system (100) may be composed of a digital photo frame (110) and an electronic device (120) that provides an image to be output through the digital photo frame (110). More specifically, the electronic device (120) may recognize the surrounding environment of the space where the digital photo frame (110) is to be located and may obtain an image suitable for the space based on the recognized surrounding environment. For example, the electronic device (120) may recommend one of a plurality of search images searched in relation to the space through an artificial intelligence model, or generate an image suitable for the space.

[0038] The electronic device (120) can transmit the image obtained in this way to a digital picture frame (110), and the digital picture frame (110) can output the image transmitted from the electronic device (120) after adjusting the size based on the frame size.

[0039] Meanwhile, in the above example, a configuration is provided in which an electronic device (120) acquires an image to be output through a digital photo frame (110), but this is merely one example and is not limited to the above example. For example, the digital photo frame providing system (100) may further include a separate server (130). In this case, the server (130) can receive input information related to an image to be output through the digital photo frame (110) from the electronic device (120), and can acquire an image suitable for the space where the digital photo frame (110) is to be located based on the received input information. For example, the server (130) can recommend one of a plurality of search images searched in relation to the space through an artificial intelligence model, or generate an image suitable for the space.

[0040] The server (130) can transmit the image obtained in this way to the digital picture frame (110) through the electronic device (120), and the digital picture frame (110) can output the image transmitted through the electronic device (120) after adjusting the size based on the frame size.

[0042] FIG. 2 is a diagram illustrating the configuration of an electronic device according to an embodiment of the present invention. The electronic device (200) shown in FIG. 2 may correspond to the electronic device shown in FIG. 1 (e.g., the electronic device (120) of FIG. 1).

[0043] As illustrated in FIG. 2, the electronic device (200) may include one or more processors (210) and a memory (220) that loads or stores a program (230) executed by the processor (210). The components included in the electronic device (200) of FIG. 2 are merely examples, and a person skilled in the art to which the present invention pertains will know that other general-purpose components may be included in addition to the components shown in FIG. 2.

[0044] The processor (210) controls the overall operation of each component of the electronic device (200). The processor (210) may be configured to include at least one of a CPU (Central Processing Unit), MPU (Micro Processor Unit), MCU (Micro Controller Unit), GPU (Graphic Processing Unit), NPU (Neural Processing Unit), DSP (Digital Signal Processor), or any form of processor well known in the art of the present invention. Additionally, the processor (210) may perform operations for at least one application or program for executing a method / operation according to various embodiments of the present invention. The electronic device (200) may have one or more processors.

[0045] The memory (220) stores one or more combinations of various data, instructions, and information used by a component (e.g., processor (210)) included in the electronic device (200). The memory (220) may include volatile memory and / or non-volatile memory.

[0046] The program (230) may include one or more actions in which methods / actions according to various embodiments of the present invention are implemented, and may be stored in memory (220) in the form of software. Here, the action corresponds to an instruction realized in the program (230). For example, the program (230) may include instructions to perform the following actions: receiving input information related to an image to be output through a digital picture frame from a user; determining a training data set composed of at least one search image based on a keyword regarding the space where the digital picture frame is located among the received input information and a category regarding the type of image to be output through the digital picture frame; acquiring an image to be output through the digital picture frame based on a surrounding environment image regarding the space where the digital picture frame is located among the received input information and the determined training data set; and transmitting the acquired image to the digital picture frame.

[0047] When the program (230) is loaded into memory (220), the processor (210) can perform methods / operations according to various embodiments of the present invention by executing a plurality of operations to implement the program (230).

[0048] The execution screen of the program (230) can be displayed through the display (240). In the case of FIG. 1, the display (240) is depicted as a separate device connected to the electronic device (200), but in the case of an electronic device (200) such as a terminal that a user can carry, such as a smartphone or tablet, the display (240) can be a component of the electronic device (200). The screen displayed on the display (240) may be the result of the execution of the program or before information is input into the program.

[0050] FIG. 3 is a flowchart illustrating the detailed operation of an electronic device that provides an image to a digital picture frame according to an embodiment of the present invention. In an embodiment, at least one of the operations of FIG. 3 may be performed simultaneously or in parallel with other operations, and the order of the operations may be changed. Additionally, at least one of the operations may be omitted, and other operations may be performed additionally. The operations illustrated in FIG. 3 may be performed by at least one component of an electronic device (e.g., the electronic device (200) of FIG. 2).

[0051] In operation (310), the electronic device may receive input information from the user regarding an image to be output through the digital picture frame. More specifically, the input information may include at least one of a keyword regarding the space where the digital picture frame is located, a category regarding the type of image to be output through the digital picture frame, and an image of the surrounding environment regarding the space where the digital picture frame is located.

[0052] First, keywords regarding the space where the digital photo frame is located may be related to the use of the space, and for example, may include at least one of a bedroom, living room, kitchen, bathroom, or study. However, the types of keywords regarding such spaces are merely examples and are not limited to the examples mentioned above.

[0053] In addition, the category for the type of image to be output through the digital photo frame may be related to the photographic type of the image, and, for example, may include at least one of landscape photography, portrait photography, food photography, art photography, wildlife photography, fashion photography, architectural photography, and travel photography. However, the types of photographic types for such images are merely examples and are not limited to the examples mentioned above.

[0054] In operation (320), the electronic device may determine a training data set consisting of at least one search image based on a keyword regarding the space where the digital picture frame is located among the received input information and a category regarding the type of image to be output through the digital picture frame. More specifically, the electronic device may collect search images for the training data set by crawling at least one search image including a picture frame based on a keyword regarding the space and a category regarding the type of image among the input information received through an internet search. However, such a method of collecting search images is merely one example and is not limited to the above example.

[0055] Subsequently, the electronic device can extract a frame from a crawled search image as shown in Fig. 4 and process the position of the extracted frame as 0, thereby dividing the crawled search image into a search image with the frame processed as 0 and a frame.

[0056] In operation (330), the electronic device can obtain an image to be output through the digital picture frame based on the surrounding environment image of the space where the digital picture frame is located and the determined training data set among the received input information. More specifically, the electronic device can recommend one of the search images constituting the training data set through an artificial intelligence model, or generate an image that matches the space. A more detailed method for obtaining an image to be output through the digital picture frame will be explained in detail through the drawings later.

[0057] In operation (340), the electronic device can transmit the acquired image to a digital picture frame. At this time, the digital picture frame can output the image transmitted from the electronic device after adjusting its size based on the frame size.

[0058] For example, FIG. 5 is a diagram showing the structure of a digital picture frame according to an embodiment of the present invention. Referring to FIG. 5, the digital picture frame (500) may be composed of a display (510) for outputting an image transmitted from an electronic device and a frame (520) that is detachable from the display (510). At this time, the frame (520) may include size information of the image that can be output. For example, an NFC tag containing size information of the image that can be output may be placed on the frame (520). The display (510) receives size information of the image that can be output from the NFC tag of the frame (520) through an NFC reader, and can output the image transmitted from the electronic device after adjusting the size based on the received size information of the image.

[0059] Additionally, the digital photo frame (500) may include an illuminance sensor (530). Such an illuminance sensor (530) may be placed in a specific area of ​​the display (510), and the digital photo frame (500) may adjust the brightness of the display (510) based on ambient brightness information measured through the illuminance sensor (530).

[0060] Additionally, the digital photo frame (500) may include a human body detection sensor (540). Such a human body detection sensor (540) may also be placed in a specific area of ​​the display (510), and the digital photo frame (500) may determine whether the display (510) operates in power-saving mode based on whether a user is present, as measured by the human body detection sensor (540). For example, the digital photo frame (500) may detect the movement of a user within the monitoring area using a passive infrared (PIR) sensor. However, since a problem may occur where the digital photo frame (500) operates in power-saving mode when there is no movement of the user despite their presence, the digital photo frame (500) may use a thermal imaging camera to determine the presence of the user more accurately.

[0062] FIG. 6 is a flowchart illustrating the search image recommendation operation of an electronic device that provides an image to a digital picture frame according to an embodiment of the present invention. In an embodiment, at least one of the operations of FIG. 6 may be performed simultaneously or in parallel with other operations, and the order between the operations may be changed. Additionally, at least one of the operations may be omitted, and other operations may be performed additionally. The operations illustrated in FIG. 6 may be performed by at least one component of an electronic device (e.g., the electronic device (200) of FIG. 2).

[0063] In operation (610), the electronic device can identify input information related to an image to be output through a digital picture frame, which is received from the user. More specifically, the input information may include at least one of a keyword for the space where the digital picture frame is located, a category for the type of image to be output through the digital picture frame, and an image of the surrounding environment for the space where the digital picture frame is located.

[0064] In operation (620), the electronic device can determine a training data set consisting of at least one search image based on a keyword for the space where the digital picture frame is located among the received input information and a category for the type of image to be output through the digital picture frame.

[0065] In operation (630), the electronic device can measure a first similarity between the encoding result of search images constituting a training data set converted into a latent space using a pre-trained autoencoder and the encoding result of an surrounding environment image for the space where the digital picture frame is located. For example, as shown in FIG. 7, the electronic device can convert the encoding result obtained by inputting search images (710–740) constituting a training data set into a pre-trained autoencoder into a high-dimensional latent space through principal component analysis (PCA).

[0066] And the electronic device can convert the encoding result obtained by inputting the surrounding environment image (750) of the space where the digital picture frame is located into a pre-trained autoencoder into a high-dimensional latent space through principal component analysis. The electronic device can measure a first similarity by measuring the vector distance between the encoding result of each of the search images (710–740) converted into a latent space and the encoding result of the surrounding environment image (750).

[0067] In operation (640), the electronic device can measure a second similarity between a histogram of RGB values ​​of search images constituting the training data set and a histogram of RGB values ​​of an environment image of the space where the digital picture frame is located. More specifically, the electronic device can identify information such as atmosphere by determining the similarity of color information between the search images constituting the training data set and the environment image. For example, the electronic device can obtain a histogram of RGB values ​​for each of the search images constituting the training data set as shown in FIG. 8. Additionally, the electronic device can obtain a histogram of RGB values ​​for the environment image as well. The electronic device can measure the second similarity by analyzing the correlation between the histogram of each of the search images obtained in this way and the histogram of the environment image.

[0068] In operation (650), the electronic device can measure a third similarity between the number of objects in the search images constituting the training data set and the number of objects in the surrounding environment image of the space where the digital picture frame is located. For example, as shown in FIG. 9, the electronic device can detect objects in the surrounding environment image through an object detection model (e.g., YOLO or R-CNN) and identify the number of detected objects. The electronic device can also detect objects in each of the search images constituting the training data set through an object detection model and identify the number of detected objects. Thus, the electronic device can measure the third similarity by using the number of objects identified in each of the search images and the number of objects identified in the surrounding environment image.

[0069] In operation (660), the electronic device can select the search image that has the highest similarity to the surrounding environment image among the search images constituting the training data set using the measured first similarity, second similarity, and third similarity as the recommended image.

[0070] In operation (670), the electronic device may determine whether to re-select the selected recommended image based on the difference in histograms for RGB values ​​between the selected recommended image and the surrounding environment image or the number of objects included in the surrounding environment image. More specifically, the electronic device may derive a correlation coefficient by analyzing the correlation between the histogram for RGB values ​​of the selected recommended image and the histogram for RGB values ​​of the surrounding environment image. If the derived correlation coefficient is less than a preset threshold, the electronic device may decide to re-select the selected recommended image.

[0071] Alternatively, the electronic device may detect objects in an environment image through an object detection model such as YOLO or R-CNN, and determine whether to re-select a selected recommended image based on the number of detected objects and a preset threshold. For example, if the number of objects detected in the environment image is greater than or equal to a preset first threshold, the electronic device may decide to re-select a recommended image containing fewer objects. Alternatively, if the number of objects detected in the environment image is less than a preset second threshold, the electronic device may decide to re-select a recommended image containing more objects.

[0073] FIG. 10 is a flowchart illustrating an image generation operation using a recommended image of an electronic device that provides an image to a digital picture frame according to an embodiment of the present invention. In an embodiment, at least one of the operations of FIG. 10 may be performed simultaneously or in parallel with other operations, and the order between the operations may be changed. Additionally, at least one of the operations may be omitted, and other operations may be performed additionally. The operations illustrated in FIG. 10 may be performed by at least one component of an electronic device (e.g., the electronic device (200) of FIG. 2).

[0074] In operation (1010), the electronic device can identify a recommended image selected based on the similarity between the search images constituting the training data set and the surrounding environment image. The recommended image identified may be a result selected based on (i) a first similarity between the encoding result of the search images constituting the training data set converted into a latent space using a pre-trained autoencoder and the encoding result of the surrounding environment image for the space where the digital picture frame is located, (ii) a second similarity between the histogram of the RGB values ​​of the search images constituting the training data set and the histogram of the RGB values ​​of the surrounding environment image for the space where the digital picture frame is located, and a third similarity between the number of objects in the search images constituting the training data set and the number of objects in the surrounding environment image for the space where the digital picture frame is located.

[0075] In operation (1020), the electronic device can generate an image to be output through a digital picture frame by transforming an identified recommended image through an artificial intelligence model (e.g., a generative AI model). More specifically, the electronic device can receive weather information or seasonal information regarding the space where the digital picture frame is located, and can transform the recommended image according to the weather information or seasonal information by applying the received weather information or seasonal information to an artificial intelligence model. For example, let's assume that the identified recommended image is a sunny summer landscape photo. If seasonal information that it is winter and weather information that it is snow is received, the electronic device can transform the sunny summer landscape photo into a snowy winter landscape photo through an artificial intelligence model.

[0077] FIG. 11 is a flowchart illustrating an image generation operation using the atmosphere of the surrounding environment of an electronic device that provides an image to a digital picture frame according to an embodiment of the present invention. In an embodiment, at least one of the operations of FIG. 11 may be performed simultaneously or in parallel with other operations, and the order between the operations may be changed. Additionally, at least one of the operations may be omitted, and other operations may be performed additionally. The operations illustrated in FIG. 11 may be performed by at least one component of an electronic device (e.g., the electronic device (200) of FIG. 2).

[0078] In operation (1110), the electronic device may obtain keywords related to the atmosphere of the surrounding environment image of the space where the digital picture frame is located, among the input information related to the image to be output through the digital picture frame received from the user. At this time, the keywords related to the atmosphere may be determined based on the color ratio, object type, and space type constituting the surrounding environment image.

[0079] In operation (1120), the electronic device can generate an image to be output through the digital picture frame by inputting keywords related to the atmosphere of the acquired surrounding environment image, keywords regarding the space where the digital picture frame is located among the input information, and categories regarding the type of image to be output through the digital picture frame into the artificial intelligence model.

[0080] For example, the electronic device can generate a warm-feeling spring mountain suitable for a bedroom as an image to be displayed through the digital picture frame by inputting keywords related to the atmosphere of the surrounding environment image, such as coziness, keywords related to the space where the digital picture frame is located, such as a bedroom, and a category related to the type of image, such as a landscape photo, into the artificial intelligence model.

[0082] FIG. 12 is a flowchart illustrating an image generation operation based on the ambient color tone of an electronic device that provides an image to a digital picture frame according to an embodiment of the present invention. In an embodiment, at least one of the operations of FIG. 12 may be performed simultaneously or in parallel with other operations, and the order between the operations may be changed. Additionally, at least one of the operations may be omitted, and other operations may be performed additionally. The operations illustrated in FIG. 12 may be performed by at least one component of an electronic device (e.g., the electronic device (200) of FIG. 2).

[0083] In operation (1210), the electronic device can extract the color tone of the surrounding environment image of the space where the digital picture frame is located from among the input information related to the image to be output through the digital picture frame received from the user.

[0084] In operation (1220), the electronic device can search for a specific image containing the color based on the color of the extracted surrounding environment image.

[0085] In operation (1230), the electronic device can configure a palette according to the color ratio of the extracted ambient environment image.

[0086] In operation (1240), the electronic device can receive a drawing image drawn using a configured palette.

[0087] In operation (1250), the electronic device can generate an image to be output through a digital picture frame in response to inputting a specific image found and a received drawing image into an artificial intelligence model.

[0089] The embodiments described above may be implemented as hardware components, software components, and / or combinations of hardware and software components. For example, the devices, methods, and components described in the embodiments may be implemented using a general-purpose computer or a special-purpose computer, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing unit may execute an operating system (OS) and software applications executed on said operating system. Additionally, the processing unit may access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing unit may be described as being used as a single unit, but those skilled in the art will understand that the processing unit may include multiple processing elements and / or multiple types of processing elements. For example, the processing unit may include multiple processors or one processor and one controller. In addition, other processing configurations, such as parallel processors, are also possible.

[0090] Software may include computer programs, code, instructions, or a combination of one or more of these, and may configure a processing unit to operate as desired or instruct the processing unit independently or collectively. Software and / or data may be stored on any type of machine, component, physical device, virtual equipment, computer storage medium, or device so as to be interpreted by the processing unit or to provide instructions or data to the processing unit. Software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored on computer-readable recording media.

[0091] The method according to the embodiment 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 store program instructions, data files, data structures, etc., either individually or in combination, and the program instructions recorded on the medium may be those specifically designed and configured for the embodiment or those known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc.

[0092] The hardware device described above may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

[0093] Although the embodiments have been described above with reference to the limited drawings, those skilled in the art can apply various technical modifications and variations based thereon. For example, suitable results may be achieved even if the described techniques are performed in a different order than described, and / or if the components of the described system, structure, device, circuit, etc. are combined or assembled in a form different from described, or replaced or substituted by other components or equivalents.

[0094] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims set forth below. Explanation of the symbols

[0096] 200: Electronic devices 210 : Processor 220 : Memory 230 : Program 240 : Display

Claims

Claim 1 In an electronic device, at least one processor; The electronic device comprises a memory including one or more storage media for storing instructions, wherein the instructions, when executed individually or collectively by the at least one processor, cause the electronic device to receive input information from a user regarding a keyword for a space where a digital photo frame is located, a category for a type of image to be output through the digital photo frame, and an image of the surrounding environment for the space where the digital photo frame is located; an operation of determining a training data set composed of at least one search image based on the keyword and the category; an operation of measuring a first similarity based on the vector distance between the result of the search images included in the training data set being converted into a latent space through a pre-trained autoencoder and the result of the image of the surrounding environment for the space where the digital photo frame is located being converted into a latent space through the autoencoder; an operation of measuring a second similarity based on the correlation between a histogram of the RGB values ​​of the search images and a histogram of the RGB values ​​of the surrounding environment image; and a third similarity between the number of objects detected in each of the search images and the number of objects detected in the surrounding environment image. An electronic device that controls the operation of: obtaining a recommended image to be output through the digital picture frame using the first similarity, the second similarity, and the third similarity; and transmitting the obtained recommended image to the digital picture frame. Claim 2 An electronic device according to claim 1, wherein the operation of determining the training data set includes the operation of collecting search images including frames based on keywords for the space and categories for the types of images. Claim 3 delete Claim 4 An electronic device according to claim 1, wherein the operation of acquiring the recommended image further includes the operation of determining whether to re-select the recommended image based on the histogram difference for RGB values ​​between the acquired recommended image and the surrounding environment image or the number of objects included in the surrounding environment image. Claim 5 An electronic device according to claim 4, wherein the operation of determining whether to re-select the recommended image includes the operation of re-selecting the recommended image when the correlation coefficient between the histogram of the RGB values ​​of the selected recommended image and the histogram of the RGB values ​​of the surrounding environment image is less than a preset threshold. Claim 6 An electronic device according to claim 4, wherein the operation of determining whether to re-select the recommended image includes the operation of re-selecting the recommended image based on the number of objects included in the surrounding environment image and a preset threshold. Claim 7 An electronic device according to claim 1, wherein the operation of acquiring the recommended image includes the operation of modifying the acquired recommended image using weather information or seasonal information. Claim 8 An electronic device according to claim 1, wherein the operation of acquiring the recommended image comprises: acquiring keywords related to the atmosphere of the surrounding environment image for the space where the digital photo frame is located; and generating a recommended image to be output through the digital photo frame in response to inputting keywords related to the atmosphere of the surrounding environment image, keywords for the space where the digital photo frame is located, and categories for the type of image to be output through the digital photo frame into a generative AI model. Claim 9 An electronic device according to claim 1, wherein the operation of acquiring the recommended image comprises: an operation of extracting the color tone of an image of the surrounding environment for the space where the digital picture frame is located; an operation of searching for a specific image based on the extracted color tone; an operation of configuring a palette according to the ratio of the extracted color tone; an operation of receiving a drawing image drawn using the configured palette; and an operation of generating a recommended image to be output through the digital picture frame in response to inputting the searched specific image and the received drawing image into a generative AI model. Claim 10 An electronic device according to claim 1, wherein the digital photo frame comprises a display for outputting the acquired recommended image and a frame detachable from the display, and displays the acquired recommended image through the display by adjusting its size according to the size of the frame. Claim 11 In claim 10, the digital photo frame comprises an illuminance sensor and is an electronic device that adjusts the brightness of the display based on ambient brightness information measured through the illuminance sensor. Claim 12 In claim 10, the digital photo frame comprises a human body detection sensor and is an electronic device that determines whether to operate the display in a power-saving mode based on whether a user is present, measured through the human body detection sensor. Claim 13 A method of operating an electronic device comprises: receiving input information from a user regarding a keyword for a space where a digital photo frame is located, a category for the type of image to be output through the digital photo frame, and an image of the surrounding environment for the space where the digital photo frame is located; determining a training data set composed of at least one search image based on the keyword and the category; measuring a first similarity based on the vector distance between the result of the search images included in the training data set being converted into a latent space through a pre-trained autoencoder and the result of the image of the surrounding environment for the space where the digital photo frame is located being converted into a latent space through the autoencoder; measuring a second similarity based on the correlation between a histogram of the RGB values ​​of the search images and a histogram of the RGB values ​​of the surrounding environment image; measuring a third similarity between the number of objects detected in each of the search images and the number of objects detected in the surrounding environment image; and obtaining a recommended image to be output through the digital photo frame using the first similarity, the second similarity, and the third similarity. A method of operation comprising the operation of transmitting the acquired recommended image to the digital photo frame. Claim 14 In claim 13, the operation of determining the training data set comprises the operation of collecting search images including frames based on keywords for the space and categories for the types of images. Claim 15 delete Claim 16 A method of operation according to claim 13, wherein the operation of acquiring the recommended image further includes the operation of determining whether to re-select the recommended image based on the histogram difference for RGB values ​​between the acquired recommended image and the surrounding environment image or the number of objects included in the surrounding environment image. Claim 17 In claim 13, the operation of obtaining the recommended image includes the operation of modifying the obtained recommended image using weather information or seasonal information. Claim 18 A method of operation according to claim 13, wherein the operation of obtaining the recommended image comprises: an operation of obtaining keywords related to the atmosphere of the surrounding environment image for the space where the digital picture frame is located; and an operation of generating a recommended image to be output through the digital picture frame in response to inputting the keywords related to the atmosphere of the surrounding environment image, the keywords for the space where the digital picture frame is located, and a category for the type of image to be output through the digital picture frame into a generative AI model. Claim 19 In claim 13, the operation of obtaining the recommended image comprises: an operation of extracting the color tone of an image of the surrounding environment for the space where the digital picture frame is located; an operation of searching for a specific image based on the extracted color tone; an operation of configuring a palette according to the ratio of the extracted color tone; an operation of receiving a drawing image drawn using the configured palette; and an operation of generating a recommended image to be output through the digital picture frame in response to inputting the searched specific image and the received drawing image into a generative AI model.

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