Electronic device, method, and non-transitory computer-readable storage medium for capturing image

Abstract

This electronic device comprises: a camera; a display; a memory for storing instructions; and at least one processor including processing circuitry. The instructions, when executed individually or collectively by the at least one processor, cause the electronic device to: provide, by means of the display, a screen including a preview image acquired by the camera; on the basis of at least one among ambient illuminance or visual complexity of the preview image, identify a recommended resolution for capturing an image among a plurality of resolutions; and when a capturing command is received, capture an image on the basis of the recommended resolution.

Description

Electronic device, method, and non-transient computer-readable storage medium for performing image capture

[0001] The present disclosure relates to an electronic device, a method for taking an image, and a non-transient computer-readable storage medium.

[0002] Recently, the distribution of various types of portable electronic devices, such as smartphones, tablet PCs, wireless earphones, and smartwatches, is expanding.

[0003] Recently, electronic devices offer a variety of functions and services. For example, an electronic device provides a feature that allows the user to shoot at their desired resolution among various resolutions.

[0004] 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.

[0005] An electronic device according to one embodiment comprises: a camera; a display; a memory for storing instructions; and at least one processor including processing circuitry; wherein, when the instructions are executed individually or collectively by the at least one processor, the electronic device provides a screen including a preview image acquired by the camera through the display, identifies a recommended resolution for capturing an image among a plurality of resolutions based on at least one of ambient illumination or the visual complexity of the preview image, and, when a shooting command is received, performs image capturing based on the recommended resolution.

[0006] An electronic device according to one embodiment comprises a camera; a display; a memory for storing instructions; and at least one processor including processing circuitry. When the instructions are executed individually or collectively by the at least one processor, the electronic device provides a screen including a preview image acquired through the camera via the display. When a shooting command is received, the electronic device acquires a plurality of captured images based on each of a plurality of resolutions and stores them in the memory. When a recommended resolution is identified based on at least one of ambient illumination or the visual complexity of the preview image, the electronic device deletes the remaining captured images from the memory, excluding the captured image corresponding to the recommended resolution among the plurality of captured images stored in the memory.

[0007] A control method for an electronic device according to one embodiment comprises: providing a screen including a preview image acquired by a camera through a display; identifying a recommended resolution for capturing an image among a plurality of resolutions based on at least one of ambient illumination or the visual complexity of the preview image; and, when a shooting command is received, performing image capture based on the recommended resolution.

[0008] A non-transient computer-readable medium storing instructions that cause the electronic device to perform an operation when executed by a processor of an electronic device according to one embodiment, wherein the operation comprises: providing a screen including a preview image acquired by a camera through a display; identifying a recommended resolution among a plurality of resolutions for capturing an image based on at least one of ambient illumination or the visual complexity of the preview image; and, when a shooting command is received, performing image capture based on the recommended resolution.

[0009] The above and other aspects, features, and advantages of specific embodiments of the present disclosure will become more apparent from the following description taken together with the accompanying drawings.

[0010] FIG. 1 is a diagram for schematically explaining the operation of an electronic device according to one embodiment.

[0011] FIG. 2 illustrates an example of a block diagram of an electronic device according to one embodiment.

[0012] FIG. 3 is a flowchart illustrating the operation of an electronic device according to one embodiment.

[0013] FIGS. 4a and 4b are drawings for explaining a method for identifying a recommended resolution corresponding to a captured image using an artificial intelligence model according to one embodiment.

[0014] FIG. 5 is a flowchart illustrating the operation of an electronic device according to one embodiment.

[0015] FIG. 6 is a flowchart illustrating the operation of an electronic device according to one embodiment.

[0016] FIG. 7 is a flowchart illustrating the operation of an electronic device according to one embodiment.

[0017] FIG. 8 is a flowchart illustrating the operation of an electronic device according to one embodiment.

[0018] FIG. 9 is a flowchart illustrating the operation of an electronic device according to one embodiment.

[0019] FIG. 10 is a diagram illustrating a generative artificial intelligence model according to one embodiment.

[0020] FIG. 11 is a drawing illustrating a method for providing a UI for resolution recommendation according to one embodiment.

[0021] FIG. 12 is a drawing illustrating a method for providing a UI for resolution recommendation according to one embodiment.

[0022] FIG. 13 is a drawing illustrating a method for providing a UI for resolution recommendation according to one embodiment.

[0023] FIG. 14 is a block diagram of an electronic device in a network environment according to various embodiments.

[0024] The present disclosure will be described in detail below with reference to the attached drawings.

[0025] The terms used in the embodiments of this disclosure have been selected to be as widely used and general as possible, taking into account their functions within this disclosure; however, these terms may vary depending on the intent of those skilled in the art, case law, or the emergence of new technologies. Additionally, in specific cases, terms have been selected at the applicant's discretion, and in such cases, their meanings will be described in detail in the description section of the disclosure. Therefore, terms used in this disclosure should be defined based on their meanings and the overall content of this disclosure, rather than merely their names (e.g., call, message, analyzed schedule).

[0026] In this specification, expressions such as “have,” “may have,” “include,” or “may include” indicate the presence of the feature (e.g., a numerical value, function, operation, or component, etc.) and do not exclude the presence of additional features.

[0027] The expression "at least one of A and / or B" should be understood as representing either "A" or "B" or "A and B".

[0028] Expressions such as "first," "second," "first," or "second" used in this specification may modify various components regardless of order and / or importance, and are used only to distinguish one component from another and do not limit said components.

[0029] Where it is stated that a component (e.g., a first component) is "(operatively or communicatively) coupled with / to" or "connected to" another component (e.g., a second component), it should be understood that the component may be directly connected to the other component or connected through the other component (e.g., a third component).

[0030] The singular expression includes the plural expression unless the context clearly indicates otherwise. In this application, terms such as “comprising” or “consisting” are intended to specify the existence of the features, numbers, actions, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, actions, actions, components, parts, or combinations thereof.

[0031] In the embodiments, a "module" or "part" performs at least one function or operation and may be implemented in hardware or software, or a combination of hardware and software. Additionally, a plurality of "modules" or a plurality of "parts" may be integrated into at least one module and implemented by at least one processor, except for a "module" or "part" that needs to be implemented in specific hardware.

[0032] In the present disclosure, the term "user" may refer to a person using an electronic device or a device using an electronic device (e.g., an artificial intelligence electronic device).

[0033] The various elements and areas in the drawings are depicted schematically. Accordingly, the technical concept of the present invention is not limited by the relative sizes or spacing depicted in the attached drawings.

[0034] Embodiments of the present disclosure will be described in more detail below with reference to the attached drawings.

[0035]

[0036] * FIG. 1 is a diagram for schematically explaining the operation of an electronic device according to one embodiment.

[0037] According to one embodiment, the electronic device (100) may be implemented as a device that provides a shooting function by having a camera. According to one example, a user may take a photo or video by running a camera application and selecting a shooting mode. For example, the user may run the camera application from the home screen or lock screen, or run the camera application from the app list.

[0038] According to one embodiment, the electronic device (100) may provide a screen including a preview image when a camera application is executed. According to one example, the screen including the preview image may be a preview screen provided so that the user can check the scene to be captured in real time through the screen before taking a photo or video.

[0039] According to one embodiment, a screen including a preview image may provide a UI area for selecting a shooting mode. For example, the shooting mode may include at least one of a photo mode, a video mode, a portrait mode, a night mode, and an AI (artificial intelligence) shooting mode. For example, the UI area for selecting a shooting mode may include an option to switch modes at the bottom or top of the screen. According to one example, the AI ​​shooting mode may be a shooting mode that performs shooting by recommending an optimal resolution for the preview image.

[0040] Hereinafter, various embodiments will be described in which, in an AI shooting mode, an electronic device (100) performs shooting based on a recommended resolution corresponding to a preview image among a plurality of resolutions capable of shooting.

[0041] FIG. 2 illustrates an example of a block diagram of an electronic device according to one embodiment.

[0042] According to various embodiments, the electronic device (100) of FIG. 2 may be at least partially similar to the electronic device (2401) of FIG. 20, or may include other embodiments of the electronic device.

[0043] In one embodiment, in terms of being owned by a user, the electronic device (100) may be referred to as a terminal (or user terminal). The terminal may include, for example, a personal computer (PC) such as a laptop and a desktop. The terminal may include, for example, a smartphone, a smartpad, and / or a tablet PC. The terminal may include smart accessories such as a smartwatch and / or a head-mounted device (HMD). According to one embodiment, the electronic device (100) may include a deformable housing. Based on the deformability, the housing of the electronic device (100) may be divided into a plurality of parts. According to one example, the electronic device (100) may be implemented as a user terminal (40) illustrated in FIG. 1.

[0044] According to one embodiment, the electronic device (100) may include at least one of a processor (110), a memory (120), a camera (130), a display (140), a sensor (150), a communication circuit (160), or a microphone (170). The processor (110), memory (120), camera (130), display (140), sensor (150), communication circuit (160), or microphone (170) may be electrically and / or operably coupled with each other by an electronic component such as a communication bus.

[0045] In one embodiment, the hardware of the electronic device (100) being operatively coupled may mean that a direct or indirect connection between the hardware is established via wired or wireless means so that the second hardware is controlled by the first hardware among the hardware. Although illustrated based on different blocks, the embodiment is not limited thereto, and some of the hardware of FIG. 2 (e.g., at least some of the processor (110), memory (120), and communication circuit (160)) may be included in a single integrated circuit, such as a system on a chip (SoC). The type and / or number of hardware included in the electronic device (100) is not limited to that shown in FIG. 2. For example, the electronic device (100) may include only some of the hardware components shown in FIG. 2.

[0046] According to one embodiment, the processor (110) of the electronic device (100) may include hardware for processing data based on one or more instructions. The hardware for processing data may include, for example, an arithmetic and logic unit (ALU), a floating point unit (FPU), a field programmable gate array (FPGA), a central processing unit (CPU), a graphic processing unit (GPU), a neural processing unit (NPU), and / or an application processor (AP). The number of processors (110) may be one or more. For example, the processor (110) may have the structure of a multi-core processor such as a dual core, a quad core, or a hexa core.

[0047] The processor (110) can control the operations of the electronic device (100) by executing instructions stored in memory (120). For example, the processor (110) may correspond to a plurality of processors that divide and collectively perform a plurality of operations among the processors.

[0048] A CPU (central processing unit) is a general-purpose processor capable of performing not only general operations but also artificial intelligence operations, and it can efficiently execute complex programs through a multi-layered cache structure. The CPU is advantageous for serial processing methods, which enable the organic linkage between previous and next calculation results through sequential computation. General-purpose processors are not limited to the examples mentioned above, except for cases specified as the aforementioned CPU.

[0049] A GPU (graphic processing unit) is a processor designed for massive computations, such as floating-point operations used in graphics processing, and can perform large-scale computations in parallel by integrating a large number of cores. In particular, GPUs may be advantageous over CPUs for parallel processing methods such as convolution operations. Additionally, GPUs can be used as co-processors to complement the functions of CPUs. Processors for massive computation are not limited to the examples mentioned above, except for cases specified as GPUs.

[0050] A Neural Processing Unit (NPU) is a processor specialized for artificial intelligence computations using artificial neural networks, and each layer constituting the neural network can be implemented in hardware (e.g., silicon). In this case, since the NPU is designed specifically according to the specifications required by the vendor, it has a lower degree of flexibility compared to CPUs or GPUs, but it can efficiently process the artificial intelligence computations required by the vendor. Meanwhile, as a processor specialized for artificial intelligence computations, the NPU can be implemented in various forms such as Tensor Processing Units (TPUs), Intelligence Processing Units (IPUs), and Vision Processing Units (VPUs). Artificial intelligence processors are not limited to the examples mentioned above, except for cases specified as the aforementioned NPU.

[0051] According to one embodiment, the memory (120) of the electronic device (100) may include a hardware component for storing data and / or instructions that are input and / or output to the processor (110). The memory (120) may include, for example, volatile memory such as random-access memory (RAM) and / or non-volatile memory such as read-only memory (ROM). Volatile memory may include, for example, at least one of dynamic RAM (DRAM), static RAM (SRAM), cache RAM, and pseudo SRAM (PSRAM). Non-volatile memory may include, for example, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), flash memory, hard disk, compact disk, solid status drive (SSD), or embedded multimedia card (eMMC).

[0052] According to one embodiment, within the memory (120) of the electronic device (100), one or more instructions (or commands) representing operations and / or operations to be performed on data by the processor (110) may be stored. A set of one or more instructions may be referred to as firmware, an operating system, a process, a routine, a sub-routine, and / or an application. For example, the electronic device (100) and / or the processor (110) may perform various operations when a set of a plurality of instructions distributed in the form of an operating system, firmware, a driver, and / or an application is executed. In the following, the statement that an application is installed on an electronic device (100) means that one or more instructions provided in the form of an application are stored in the memory (120) of the electronic device (100), and that the one or more applications are stored in an executable format (e.g., a file having an extension specified by the operating system of the electronic device (100)) that is executable by the processor (110) of the electronic device (100).

[0053] At least one processor (110) controls the processing of input data according to a predefined operation rule or artificial intelligence model stored in memory (120). The predefined operation rule or artificial intelligence model is characterized by being created through learning. Being created through learning means that a predefined operation rule or artificial intelligence model with desired characteristics is created by applying a learning algorithm to a number of learning data. Such learning may be performed on the device itself where the artificial intelligence according to the present disclosure is performed, or it may be performed through a separate server / system.

[0054] An artificial intelligence model may be composed of multiple neural network layers. At least one layer has at least one weight value and performs the layer's operation through the result of the operation of the previous layer and at least one defined operation. Examples of neural networks include convolutional neural networks (CNN), recurrent neural networks (RNN), deep neural networks (DNN), restricted Boltzmann machines (RBM), deep belief networks (DBN), bidirectional recurrent deep neural networks (BRDNN), deep Q-networks, and Transformers; however, the neural networks in this disclosure are not limited to the aforementioned examples except where specified.

[0055] A learning algorithm is a method of training a specific target device (e.g., a robot) using a number of learning data to enable the target device to make decisions or predictions on its own. Examples of learning algorithms include supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, and the learning algorithms in this disclosure are not limited to the aforementioned examples except where specified.

[0056] A camera (130) of an electronic device (100) according to one embodiment may convert a captured image into an electrical signal and generate image data based on the converted signal. For example, the camera (130) may include at least one of a general (or basic) camera, a depth camera, and an ultra-wide angle camera. For example, the camera (130) may include at least one of a pop-up camera or a rotating camera.

[0057] According to one example, the camera (130) may include at least one of a rear camera positioned on the rear of the electronic device (100) or a front camera positioned on the front of the electronic device (100). For example, the rear camera may be positioned on the top rear of the electronic device (100). For example, the front camera may be positioned on the top front of the electronic device (100). For example, the front camera may include a plurality of cameras, and the plurality of cameras may be arranged vertically, horizontally, or grouped together like an island. For example, the rear camera may include a plurality of cameras and may be positioned in at least one of a notch design, a punch-hole design, bezel placement, or under-display form.

[0058] According to one embodiment, a display (140) of an electronic device (100) can output visualized information to a user. For example, the display (140) can be controlled by a controller, such as a GPU (graphic processing unit), to output visualized information to a user. The display (140) may include an OLED (organic light emitting diodes) display, an LED (light emitting diodes), a micro LED, a mini LED, a PDP (plasma display panel), a QD (quantum dot) display, a QLED (quantum dot light-emitting diodes) and / or an e-ink display and / or an e-paper display. According to one example, the display (140) may be implemented as a flat display, a curved display, a folding and / or rolling flexible display.

[0059] A sensor (150) of an electronic device (100) according to one embodiment can sense various user information. The sensor (150) can be implemented as various types of sensors capable of user sensing. For example, the sensor (150) may include at least one sensor among a time of flight (ToF) sensor, an ultrasonic sensor, a radio detection and ranging (RADAR) sensor, a photodiode sensor, a proximity sensor, a passive infrared (PIR) sensor, a pinhole sensor, a pinhole camera, an infrared human body detection sensor, a complementary metal oxide semiconductor (CMOS) image sensor, a thermal sensor, a light sensor, and a motion sensor.

[0060] The sensor (150) may include a touch sensor that detects touch actions, having a form such as a touch film, a touch sheet, or a touch pad.

[0061] The sensor (150) may include at least one of a CO2 sensor and an atmospheric pressure sensor. The CO2 sensor is a sensor for measuring carbon dioxide concentration. The atmospheric pressure sensor is a sensor for sensing ambient pressure.

[0062] The sensor (150) may further include at least one sensor capable of sensing ambient illuminance, ambient temperature, and the direction of incidence of light. In this case, the sensor (150) may be implemented as an illuminance sensor, a temperature sensing sensor, a light intensity sensing layer, and a camera.

[0063] The sensor (150) may further include at least one of an acceleration sensor (or gravity sensor), a geomagnetic sensor, and a gyro sensor. For example, the acceleration sensor may be a 3-axis acceleration sensor. The 3-axis acceleration sensor may measure gravitational acceleration by axis and provide raw data to the processor (140). The geomagnetic sensor or the gyro sensor may be used to obtain attitude information. Here, the attitude information may include at least one of roll information, pitch information, or yaw information.

[0064] A communication circuit (160) of an electronic device (100) according to one embodiment may include hardware for supporting the transmission and / or reception of electrical signals between the electronic device (100) and an external device (e.g., a server). The communication circuit (160) may include, for example, at least one of a modem (modulator and demodulator), an antenna, and an O / E (optic / electronic) converter. The communication circuit (160) may support the transmission and / or reception of electrical signals based on various types of protocols such as Ethernet, LAN (local area network), WAN (wide area network), WiFi (wireless fidelity), NFC (near field communication), Bluetooth, BLE (bluetooth low energy), ZigBee, LTE (long term evolution), 5G NR (new radio), and / or 6G.

[0065] According to one example, the electronic device (100) may be connected to a server and to each other based on a wired network and / or a wireless network. The wired network may include a network such as the Internet, a LAN (local area network), a WAN (wide area network), Ethernet, or a combination thereof. The wireless network may include a network such as LTE (long term evolution), 5G NR (new radio), WiFi (wireless fidelity), Zigbee, NFC (near field communication), Bluetooth, BLE (bluetooth low-energy), or a combination thereof. According to one example, the electronic device (100) and the server may be connected indirectly through an intermediate node within the network.

[0066] A microphone (170) of an electronic device (100) according to one embodiment is configured to receive user voice or other sounds and convert them into audio data.

[0067] FIG. 3 is a flowchart illustrating the operation of an electronic device according to one embodiment.

[0068] In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0069] According to one embodiment, operations 305 to 325 can be understood as being performed in the processor (110) of the electronic device (100).

[0070] According to FIG. 3, in operation 305, an electronic device (100) according to one embodiment may provide a screen including a preview image obtained by a camera (130).

[0071] According to one example, the electronic device (100) can provide a screen containing a preview image when a camera application (or camera program) is executed.

[0072] According to one example, a screen containing a preview image may be a preview screen provided to allow the user to check the scene to be captured in real time through the screen before taking a photo or video.

[0073] In operation 310, the electronic device (100) according to one embodiment can identify at least one of ambient illumination or visual complexity of a preview image.

[0074] An electronic device (100) according to one embodiment can identify whether the shooting mode is an AI shooting mode. According to one example, the AI ​​shooting mode may be a shooting mode that performs shooting by recommending an optimal resolution for a preview image. According to one example, the fact that the shooting mode is an AI shooting mode may mean that the AI ​​shooting mode is activated. According to one example, the AI ​​shooting mode may be activated / deactivated through an on / off setting in a settings menu. According to one example, the AI ​​shooting mode may be activated / deactivated through a shooting mode switching option provided at the bottom or top of the screen.

[0075] According to one embodiment, if the shooting mode is an AI shooting mode, the electronic device (100) can identify at least one of ambient illumination or visual complexity of a preview image.

[0076] According to one embodiment, the electronic device (100) can identify a recommended resolution based on at least one of ambient illumination or the visual complexity of a preview image through a learned artificial intelligence model.

[0077] According to one example, the electronic device (100) can identify a recommended resolution by inputting ambient light information into a learned artificial intelligence model. For example, the learned artificial intelligence model can be trained to identify a recommended resolution when ambient light information is input.

[0078] According to one example, the electronic device (100) can identify a recommended resolution by inputting ambient light and a preview image into a trained artificial intelligence model. For example, the trained artificial intelligence model can be trained to identify a recommended resolution when ambient light information and a preview image are input.

[0079] According to one example, the electronic device (100) can identify a recommended resolution by inputting a preview image into a trained artificial intelligence model. For example, the trained artificial intelligence model can be trained to identify a recommended resolution when a preview image is input.

[0080] In operation 315, an electronic device (100) according to one embodiment can identify a recommended resolution corresponding to a preview image among a plurality of resolutions based on at least one of ambient illumination or visual complexity of the preview image. The recommended resolution is merely a term chosen for convenience of explanation and can be replaced with other terms such as resolution, optimal resolution, suitable resolution, or AI resolution.

[0081] According to one embodiment, the electronic device (100) can identify a recommended resolution based on a preview image among a plurality of available resolutions that can be captured. According to one example, the available resolutions that can be captured by the electronic device (100) may vary depending on the physical specifications and / or software of the camera (130). According to one example, the available resolutions that can be captured by the electronic device (100) may affect the quality and / or file size of photos and videos. For example, photo resolution may be displayed in megapixels (MP, 1 million pixels).

[0082] According to one example, the electronic device (100) can identify a recommended resolution among a first resolution, a second resolution, and a third resolution that can be captured based on a preview image. For example, the first resolution may be a resolution below a first threshold resolution, the second resolution may be a resolution above the first threshold resolution and below the second threshold resolution, and the third resolution may be a resolution above the second threshold resolution. For example, at least one of the first threshold resolution or the second threshold resolution may be implemented in various numerical values ​​depending on the physical specifications and / or software of the camera (130). For example, the first resolution may be 12MP, the second resolution may be 50MP, and the third resolution may be 200MP. For example, the first resolution may be 12MP, the second resolution may be 24MP (or 25MP), and the third resolution may be 100MP (or 125MP). For example, the first resolution may be 12MP, the second resolution may be 48MP, and the third resolution may be 108MP. However, the values ​​for each resolution exemplified are merely examples and may be implemented with various values ​​depending on the physical specifications and / or software of the camera (130).

[0083] According to one embodiment, the electronic device (100) can identify a recommended resolution provided in an AI shooting mode based on at least one of whether the preview image includes a preset object of interest and the dynamic range of the preview image.

[0084] According to one example, the electronic device (100) can identify the recommended resolution provided in AI shooting mode when the preview image includes a preset object of interest.

[0085] According to one example, a preset object of interest may include at least one of a person, an object, and an animal that has been photographed more than a preset frequency from the electronic device (100) to another electronic device (100). For example, a person photographed more than a preset frequency may be a person that the user of the electronic device (100) frequently photographs, such as family or friends. For example, an object photographed more than a preset frequency may be a person that the user of the electronic device (100) frequently photographs according to preference, such as food or furniture. For example, an animal photographed more than a preset frequency may be an animal that the user of the electronic device (100) frequently photographs, such as a pet.

[0086] According to one example, a pre-set object of interest may include at least one person, object, and animal associated with the user of the electronic device (100) in various ways. For example, the pre-set object of interest may include at least one person, object, and animal registered on the user's social network service (SNS) more than a pre-set number of times. For example, the pre-set object of interest may include at least one person, object, and animal photographed more than a pre-set frequency on another electronic device owned by the user of the electronic device (100). For example, the pre-set object of interest may include at least one person, object, and animal stored more than a pre-set number of times on another electronic device owned by the user of the electronic device (100).

[0087] According to one example, a pre-configured object of interest may include a landmark of a specific location. For example, a landmark may be a place or structure that is easily visible in a specific location and possesses symbolic, historical, or cultural value. For example, a landmark may include at least one of a building, natural topography, public space, and cultural heritage.

[0088] According to one example, a pre-set object of interest may include at least one of a person, object, and animal previously selected by the user. For example, a pre-set object of interest may include at least one of a person, object, and animal selected by the user through the UI in a previously captured image.

[0089] According to one embodiment, the electronic device (100) can identify a recommended resolution provided in AI shooting mode when it is identified that the dynamic range of a preview image is greater than or equal to a specific range. For example, the specific range may be set during the manufacturing of the electronic device (100) or may be set by a user. For example, the specific range may be a value that can be changed by a user. For example, the specific range may be a value that can be changed by a signal received from an external server.

[0090] According to one example, the dynamic range of a captured image can be information indicating the difference in brightness between the brightest and darkest parts of the image. For example, dynamic range can be the ratio between maximum brightness and minimum brightness (or the ratio between the brightest area and the darkest area). For example, the unit of dynamic range can be stops or decibels (dB).

[0091] According to one example, the electronic device (100) can identify a dynamic range by using at least one of pixel value analysis and histogram analysis in a preview image.

[0092] According to one example, the electronic device (100) can identify the dynamic range based on the minimum pixel value (dark area) and the maximum pixel value (bright area) of the preview image. For example, the electronic device (100) can identify the dynamic range (DR) based on the following mathematical formula 1.

[0093] [Mathematical Formula 1]

[0094]

[0095] According to one example, the electronic device (100) can identify the dynamic range based on a histogram of a preview image. The histogram may represent the distribution of brightness values ​​in the image. For example, the electronic device (100) can identify the dynamic range based on the values ​​of the two end regions (left: dark, right: bright) of the histogram.

[0096] According to one example, when the dynamic range of a captured image is greater than a certain range, a relatively higher resolution among multiple available resolutions can be identified as the recommended resolution. For example, in the case of a photograph of a high-contrast environment (e.g., a landscape photograph with a large contrast difference between the sky and the ground, or a scene photograph containing both the interior and the view outside the window), a relatively higher resolution among multiple available resolutions can be identified as the recommended resolution.

[0097] According to one example, the dynamic range of HDR images captured using the HDR function can be expanded. HDR images can be created by combining multiple images taken with different exposures. For instance, in the case of HDR images, a relatively high resolution can be identified as the recommended resolution.

[0098] According to one example, the electronic device (100) can identify a recommended resolution corresponding to the preview image based on at least one of the visual complexity of the preview image, the zoom distance with respect to the object of interest included in the captured image, and the dynamic range of the preview image.

[0099] According to one embodiment, the electronic device (100) can identify a recommended resolution provided in AI shooting mode if the visual complexity of the preview image is greater than or equal to a specific value. For example, the specific value may be set during the manufacturing of the electronic device (100) or may be set by a user. For example, the specific value may be a value that can be changed by a user. For example, the specific value may be a value that can be changed by a signal received from an external server.

[0100] According to one example, the visual complexity of a preview image may be a concept indicating how much information, detail, and / or elements the image contains visually. For example, the visual complexity of an image may be determined based on at least one of the number of components, color variety, level of detail, composition, or background complexity. For example, visual complexity may include spatial complexity, structural complexity, and / or cognitive complexity. According to one example, the visual complexity of an image may be calculated as at least one of a score or a level (e.g., numerical level, high / medium / low level).

[0101] According to one example, the electronic device (100) can identify the visual complexity of a preview image through edge density analysis. For example, the electronic device (100) can use an edge detection algorithm (e.g., Canny Edge Detection) to extract boundary lines within the image and then calculate the number of edges, and determine that the more edges there are, the higher the visual complexity.

[0102] According to one example, the electronic device (100) can identify the visual complexity of a preview image by analyzing a color histogram. For example, the electronic device (100) can determine that the visual complexity is high if the colors are evenly distributed and there are many different shades in the color histogram.

[0103] According to one example, the electronic device (100) can identify the visual complexity of a preview image through fractal dimension measurement, for example, the electronic device (100) can mathematically calculate the self-similarity and complexity of the preview image through fractal dimension analysis.

[0104] According to one example, the electronic device (100) can identify the visual complexity of a preview image through entropy calculation. For example, the electronic device (100) can quantitatively measure the visual complexity by calculating information entropy (Shannon Entropy) from the pixel value distribution of the image. For example, the electronic device (100) can determine that the higher the entropy value, the greater the variation in pixel values ​​and the higher the visual complexity.

[0105] According to one example, if the visual complexity of the preview image is greater than a certain value, the electronic device (100) can identify a high-resolution image greater than the threshold resolution as the recommended resolution.

[0106] According to one embodiment, the electronic device (100) can identify a recommended resolution provided in AI shooting mode if the zoom distance to an object of interest included in a captured image is greater than or equal to a specific distance. For example, the specific distance may be set during the manufacturing of the electronic device (100) or may be set by a user. For example, the specific distance may be a value that can be changed by a user. For example, the specific distance may be a value that can be changed by a signal received from an external server.

[0107] According to one example, the zoom distance to an object of interest included in a captured image may be the degree to which the subject is magnified or reduced during shooting. For example, the zoom distance may be implemented optically and / or digitally. For example, the zoom distance may represent a magnification ratio relative to the base focal length. For example, the zoom distance may be indicated as a magnification factor, such as 1x, 2x, or 10x.

[0108] According to one example, the electronic device (100) can identify a high-resolution image with a threshold resolution or higher as the recommended resolution if the zoom distance to an object of interest included in the captured image is greater than a certain distance. For example, when a user zooms in beyond a certain distance, the high-resolution image can be identified as the recommended resolution with the intention of wanting clear image quality for a distant subject.

[0109] According to one embodiment, the electronic device (100) can identify a recommended resolution corresponding to a preview image based on ambient illumination information. For example, this is because a brighter and clearer image can be provided when shooting at a low resolution in a low-light environment. According to one embodiment, the electronic device (100) acquires illumination information based on sensing data and can identify a recommended resolution based on the illumination information.

[0110] According to one example, the electronic device (100) can obtain illuminance information based on the intensity of light obtained through an illuminance sensor. For example, the electronic device (100) can obtain illuminance information by converting an analog signal generated from an illuminance sensor into a digital value.

[0111] According to one example, an electronic device (100) can obtain illuminance information based on image data obtained through an image sensor (e.g., CMOS (Complementary Metal-Oxide-Semiconductor), CCD (Charge-Coupled Device)). For example, the image sensor can detect light through a sensor array consisting of numerous pixels and convert it into an electrical signal to be stored as a digital image. For example, the electronic device (100) can obtain illuminance information by analyzing pixel data included in the digital image. For example, the electronic device (100) can obtain the luminance value of each pixel in the digital image, obtain luminance information from multiple pixels of the image, and then calculate an average value to estimate the ambient illuminance.

[0112] According to one embodiment, the electronic device (100) can identify a recommended resolution corresponding to a preview image based on the storage capacity of the memory (120). For example, this is because low-resolution shooting may be appropriate when the storage capacity of the memory (120) of the electronic device (100) is not large.

[0113] According to one embodiment, the electronic device (100) can identify a recommended resolution corresponding to a preview image based on the remaining battery amount. For example, since shooting at high resolution requires more power, shooting at low resolution may be appropriate.

[0114] In operation 320, it is possible to identify whether a shooting command is received.

[0115] According to one example, a shooting command may be received by the electronic device (100) according to the previous embodiment based on at least one of a soft button input provided on the screen of the device (100), a physical button input provided in the electronic device (100), a voice command input, or a gesture input. According to one example, a shooting command may be received based on an additional shooting button input displayed along with recommended resolution information. However, it is not limited thereto, and the shooting command may be received based on at least one of a voice command input or a gesture input corresponding to the additional shooting button.

[0116] For example, a shooting command can be received based on user input, such as touching an existing shooting button and dragging it to an additional shooting button.

[0117] For example, a shooting command can be received based on user input, such as touching an existing shooting button and dragging and releasing it to an additional shooting button.

[0118] For example, a shooting command may be received based on user input touching an existing shooting button. For example, an additional shooting button may not be provided separately, and only the existing shooting button may be provided. For example, when the existing shooting button is selected, multiple images corresponding to the default resolution and the recommended resolution may be captured and saved.

[0119] An electronic device (100) according to one embodiment may display a first UI item for receiving user input to take an image according to a default resolution on a screen, and may display a second UI item on a screen containing information about a recommended resolution. For example, taking a picture may be performed based on the recommended resolution. For example, the first UI item and the second UI item may be shooting button items.

[0120] When a shooting command is received (320:Y), in operation 325, the electronic device (100) according to one embodiment can perform image shooting based on the recommended resolution.

[0121] According to one example, the electronic device (100) can capture a high-resolution image of a higher than threshold resolution by using all pixels of an image sensor equipped in a camera (130).

[0122] According to one example, the electronic device (100) may capture at least one of an intermediate resolution image or a low resolution image below a threshold resolution by merging (or grouping) pixels of an image sensor equipped in a camera (130). For example, the electronic device (100) may capture a low resolution image through pixel binning. Pixel binning may be a technique designed to merge multiple pixels into one to receive more light. For example, if a 48MP image sensor performs 4:1 pixel binning, the final output may be an image of 12MP resolution. For example, if a 64MP image sensor performs 4:1 (4-in-1) pixel binning, the final output may be an image of 16MP resolution. For example, if a 108MP image sensor performs 9:1 (9-in-1) pixel binning, the final output may be an image of 12MP resolution. For example, the electronic device (100) can provide a bright and clear image by collecting more light through pixel binning in a low-light environment.

[0123] FIGS. 4a and 4b are drawings for explaining a method for identifying a recommended resolution corresponding to a captured image using an artificial intelligence model according to one embodiment.

[0124] According to one embodiment, the electronic device (100) can input a preview image into a trained artificial intelligence model to identify whether the preview image includes a preset object of interest. For example, the electronic device (100) can acquire a real-time preview image by capturing frame data displayed on a screen.

[0125] According to one embodiment illustrated in FIG. 4a, a learned first artificial intelligence model (410) can identify whether a preview image (420) includes a landmark of a specific place. For example, the landmark may include at least one of a building, natural topography, public space, and cultural heritage of the specific place.

[0126] According to one example, the first artificial intelligence model trained may be a model that has been previously trained (or pre-trained) to identify whether a specific place includes a landmark. For example, the electronic device (100) may have the first artificial intelligence model collect images of landmarks and train the first artificial intelligence model based on the collected images.

[0127] According to one embodiment illustrated in FIG. 4b, the learned second artificial intelligence model (430) can identify whether the preview image (440) includes at least one of a person, an object, and an animal that has been photographed more than a preset frequency. A person photographed more than a preset frequency may be a person that the user of the electronic device (100) frequently photographs, such as family or friends. An object photographed more than a preset frequency may be a person that the user of the electronic device (100) frequently photographs according to preference, such as food or furniture. An animal photographed more than a preset frequency may be an animal that the user of the electronic device (100) frequently photographs, such as a pet.

[0128] According to one example, the second artificial intelligence model trained may be a model that has been trained (or pre-trained) to identify at least one of a person, object, and animal that has been photographed more than a preset frequency. For example, the electronic device (100) may identify a photograph containing at least one of a frequently photographed person, object, and animal based on a photograph stored in memory (120), and train the second artificial intelligence model based on the identified photograph.

[0129] According to one embodiment, the electronic device (100) can identify a recommended resolution based on at least one of type information and size information of an object of interest. For example, the type information of the object of interest may include the name of the category or class to which the object belongs (e.g., person, car, dog, cat, etc.). For example, the size information of the object of interest may include information about the size of the pixel area of ​​the area occupied by the object.

[0130] According to one embodiment, the electronic device (100) can identify the recommended resolution provided in the AI ​​shooting mode if the type of the object of interest is a specific type. For example, the electronic device (100) can identify the recommended resolution provided in the AI ​​shooting mode if the type of the object of interest is a "flower". For example, the type of the object of interest for identifying the recommended resolution may be a type pre-set by the user.

[0131] According to one embodiment, the electronic device (100) can identify a recommended resolution provided in AI shooting mode if the type of the object of interest is a specific type and its size is greater than or equal to a threshold size. For example, the electronic device (100) can identify a recommended resolution provided in AI shooting mode if the type of the object of interest is a "flower" and its size is greater than or equal to a threshold size. For example, the threshold size of the object of interest for identifying the recommended resolution may be a size pre-set by the user.

[0132] According to one example, if the illuminance information is below a preset illuminance (e.g., low light environment), the electronic device (100) can identify a low resolution (e.g., 12MP) below a threshold resolution as the recommended resolution. For example, the preset illuminance may be set at the time of manufacture of the electronic device (100) or by the user to determine a low light environment. For example, the preset illuminance may be a value that can be changed by the user. For example, the preset illuminance may be a value that can be changed by a signal received from an external server.

[0133] According to one example, if the illuminance information is greater than a preset illuminance level (e.g., normal illuminance environment, high illuminance environment), the electronic device (100) can identify an intermediate resolution (e.g., 50MP) and / or a high resolution (e.g., 200MP) greater than the threshold resolution as the recommended resolution.

[0134] According to one example, the electronic device (100) can identify the recommended resolution provided in the AI ​​shooting mode by analyzing the preview image only when the illuminance information is greater than or equal to a preset illuminance.

[0135] According to one example, the electronic device (100) can identify a recommended resolution provided in AI shooting mode by analyzing at least one of the visual complexity of the preview image, the zoom distance with respect to the object of interest included in the captured image, and the dynamic range of the preview image. For example, if the illuminance information is greater than or equal to a preset illuminance, the recommended resolution provided in AI shooting mode may include at least one of a medium resolution and a high resolution.

[0136] FIG. 5 is a flowchart illustrating the operation of an electronic device according to one embodiment.

[0137] In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0138] According to one embodiment, operations 505 to 530 can be understood as being performed in the processor (110) of the electronic device (100).

[0139] According to one embodiment, detailed descriptions of operations 505 to 530 that partially overlap with operations 305 to 325 shown in FIG. 3 are omitted.

[0140] According to FIG. 5, in operation 505, an electronic device (100) according to one embodiment may provide a screen including a preview image acquired by a camera (130). According to one example, when a camera application is executed, the electronic device (100) may provide a screen including a preview image.

[0141] In operation 510, the electronic device (100) according to one embodiment can identify at least one of ambient illumination or visual complexity of a preview image.

[0142] In operation 515, an electronic device (100) according to one embodiment can identify a recommended resolution corresponding to a preview image among a plurality of resolutions based on at least one of ambient illumination or visual complexity of a preview image. According to one embodiment, the electronic device (100) can identify a recommended resolution based on a preview image among a plurality of available resolutions that can be captured.

[0143] In operation 520, the electronic device (100) according to one embodiment may provide a UI that includes information about a recommended resolution corresponding to a preview image.

[0144] According to one embodiment, the electronic device (100) may additionally display an additional shooting button (or additional shutter button) containing information about a recommended resolution corresponding to a preview image on one side of an existing shooting button (or existing shutter button). For example, the recommended resolution information may be displayed on one side of the additional shooting button or inside the additional shooting button. For example, the recommended resolution information may be displayed on at least one of the right, left, upper, or lower side of the additional shooting button. For example, the recommended resolution information may include a numerical value of the recommended resolution. For example, if the recommended resolution information is 200MP, a numerical value of "200M" may be displayed on one side of the additional shooting button or inside the additional shooting button. For example, the recommended resolution information may include a numerical value of the recommended resolution. For example, if the default resolution is 120 and the recommended resolution information is 200MP, a numerical value of the changed resolution of "80M UP" may be displayed on one side of the additional shooting button or inside the additional shooting button. For example, the recommended resolution information may include change level information based on the default resolution, such as "Resolution UP".

[0145] In operation 525, the electronic device (100) according to one embodiment can identify whether a shooting command based on a recommended resolution is received through the UI.

[0146] According to one example, a shooting command may be received based on an additional shooting button input displayed along with recommended resolution information. However, this is not limited thereto, and the shooting command may be received based on at least one of a voice command input or a gesture input corresponding to the additional shooting button. When a shooting command is received (525:Y), in operation 530, the electronic device (100) according to one embodiment may perform image shooting based on the recommended resolution.

[0147] According to one example, the electronic device (100) can take a high-resolution image using all pixels of the image sensor equipped in the camera (130).

[0148] According to one example, the electronic device (100) can capture a low-resolution image through pixel binning that merges pixels of an image sensor equipped in a camera (130).

[0149] FIG. 6 is a flowchart illustrating the operation of an electronic device according to one embodiment.

[0150] In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0151] According to one embodiment, operations 605 to 645 can be understood as being performed in the processor (110) of the electronic device (100).

[0152] According to one embodiment, detailed descriptions of operations 605 to 645 that partially overlap with operations 305 to 325 shown in FIG. 3 and operations 505 to 530 shown in FIG. 5 will be omitted.

[0153] According to FIG. 6, in operation 605, an electronic device (100) according to one embodiment may provide a screen including a preview image acquired by a camera (130). According to one example, when a camera application is executed, the electronic device (100) may provide a screen including a preview image.

[0154] In operation 610, an electronic device (100) according to one embodiment can identify a recommended resolution based on a preview image. According to one example, if the shooting mode is an AI shooting mode, the electronic device (100) can identify a recommended resolution corresponding to the preview image among a plurality of available resolutions that can be shot.

[0155] In operation 615, an electronic device (100) according to one embodiment can obtain illuminance information based on sensing data.

[0156] According to one example, the electronic device (100) can obtain illuminance information based on sensing data obtained through at least one of an illuminance sensor, a temperature sensing sensor, a light intensity sensing layer, or a camera (130).

[0157]

[0158] *In operation 620, an electronic device (100) according to one embodiment can identify whether illuminance information is less than a preset illuminance. For example, the preset illuminance may be set at the time of manufacture of the electronic device (100) or by a user to determine low illuminance. For example, the preset illuminance may be a value that can be changed by a user. For example, the preset illuminance may be a value that can be changed by a signal received from an external server.

[0159] If the illuminance information is less than the preset illuminance (625:Y), in operation 630, the electronic device (100) according to one embodiment can display a UI recommending a first resolution on the screen.

[0160] If the illuminance information is not less than the preset illuminance (625:N), then in 635, the electronic device (100) according to one embodiment can identify whether the illuminance information is greater than or equal to the preset illuminance.

[0161] If the illuminance information is greater than or equal to the preset illuminance (635:Y), in operation 635, the electronic device (100) according to one embodiment may display a UI on the screen recommending a second resolution or a third resolution.

[0162] According to one example, the first resolution may be lower than the second resolution and the third resolution.

[0163] In operation 640, the electronic device (100) according to one embodiment can identify whether a shooting command based on a recommended resolution is received through the UI.

[0164] According to one example, a shooting command may be received based on an additional shooting button input displayed along with recommended resolution information. However, this is not limited thereto, and the shooting command may be received based on at least one of a voice command input or a gesture input corresponding to the additional shooting button.

[0165] When a shooting command is received (640:Y), in operation 645, the electronic device (100) according to one embodiment can perform shooting based on the recommended resolution.

[0166] According to one example, the electronic device (100) can take a high-resolution image using all pixels of the image sensor equipped in the camera (130).

[0167] According to one example, the electronic device (100) can capture a low-resolution image through pixel binning that merges pixels of an image sensor equipped in a camera (130).

[0168] FIG. 7 is a flowchart illustrating the operation of an electronic device according to one embodiment.

[0169] In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0170] According to one embodiment, operations 705 to 750 can be understood as being performed in the processor (110) of the electronic device (100).

[0171] According to one embodiment, detailed descriptions of operations 705 to 750 that partially overlap with operations 305 to 325 shown in FIG. 3, operations 505 to 530 shown in FIG. 5, and operations 605 to 645 shown in FIG. 6 will be omitted.

[0172] According to FIG. 7, in operation 705, an electronic device (100) according to one embodiment may provide a screen including a preview image acquired by a camera (130). According to one example, when a camera application is executed, the electronic device (100) may provide a screen including a preview image.

[0173] In operation 710, an electronic device (100) according to one embodiment can identify a recommended resolution based on a preview image. According to one example, if the shooting mode is an AI shooting mode, the electronic device (100) can identify a recommended resolution corresponding to the preview image among a plurality of available resolutions that can be shot.

[0174] In operation 715, an electronic device (100) according to one embodiment can obtain illuminance information based on sensing data.

[0175] According to one example, the electronic device (100) can obtain illuminance information based on sensing data obtained through at least one of an illuminance sensor, a temperature sensing sensor, a light intensity sensing layer, or a camera (130).

[0176]

[0177] In operation 720, an electronic device (100) according to one embodiment can identify whether the illuminance information is greater than or equal to a preset illuminance. For example, the preset illuminance may be set at the time of manufacture of the electronic device (100) or by a user to determine low illuminance. For example, the preset illuminance may be a value that can be changed by a user. For example, the preset illuminance may be a value that can be changed by a signal received from an external server.

[0178] If the illuminance information is greater than or equal to a preset illuminance (720:Y), in operation 725, the electronic device (100) according to one embodiment can identify whether the visual complexity of the preview image is less than a threshold complexity. For example, the threshold complexity may be set at the time of manufacture of the electronic device (100) or by the user to determine the recommended resolution based on the visual complexity of the preview image. For example, the threshold complexity may be a value that can be changed by the user. For example, the threshold complexity may be a value that can be changed by a signal received from an external server.

[0179] According to one example, the visual complexity of a preview image may be a concept indicating how much information, detail, and / or elements the image visually contains. For example, the visual complexity of an image may be determined based on the number of components, color variety, level of detail, composition, and / or background complexity. For example, visual complexity may include spatial complexity, structural complexity, and / or cognitive complexity. According to one example, the visual complexity of an image may be calculated as at least one of a score or a level (e.g., numerical level, high / medium / low level).

[0180] If the visual complexity of the image being captured is less than the critical complexity (725:Y), in operation 730, the electronic device (100) according to one embodiment may display a UI recommending a second resolution on the screen.

[0181] If the visual complexity of the preview image is not less than the threshold complexity (725:N), in operation 735, the electronic device (100) according to one embodiment can identify whether the visual complexity of the preview image is greater than or equal to the threshold complexity.

[0182] If the visual complexity of the preview image is greater than or equal to the critical complexity (735:Y), the electronic device (100) according to one embodiment may display a UI recommending a third resolution on the screen. According to one example, the third resolution may be a higher resolution than the second resolution.

[0183] In operation 745, the electronic device (100) according to one embodiment can identify whether a shooting command based on a recommended resolution is received through the UI.

[0184] According to one example, a shooting command may be received based on an additional shooting button input displayed along with recommended resolution information. However, this is not limited thereto, and the shooting command may be received based on at least one of a voice command input or a gesture input corresponding to the additional shooting button.

[0185] When a shooting command is received (745:Y), in operation 750, the electronic device (100) according to one embodiment can perform image shooting based on the recommended resolution.

[0186] According to one example, the electronic device (100) can take a high-resolution image using all pixels of the image sensor equipped in the camera (130).

[0187] According to one example, the electronic device (100) can capture a low-resolution image through pixel binning that merges pixels of an image sensor equipped in a camera (130).

[0188] FIG. 8 is a flowchart illustrating the operation of an electronic device according to one embodiment.

[0189] In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0190] According to one embodiment, operations 805 to 850 can be understood as being performed in the processor (110) of the electronic device (100).

[0191] According to one embodiment, detailed descriptions of operations that partially overlap with operations 305 to 325 shown in FIG. 3, operations 505 to 530 shown in FIG. 5, operations 605 to 645 shown in FIG. 6, and operations 705 to 750 among operations 805 to 850 are omitted.

[0192] According to FIG. 8, in operation 805, an electronic device (100) according to one embodiment may provide a screen including a preview image acquired by a camera (130). According to one example, when a camera application is executed, the electronic device (100) may provide a screen including a preview image.

[0193] In operation 810, an electronic device (100) according to one embodiment can identify a recommended resolution based on a preview image. According to one example, if the shooting mode is an AI shooting mode, the electronic device (100) can identify a recommended resolution corresponding to the preview image among a plurality of available resolutions that can be shot.

[0194] In operation 815, an electronic device (100) according to one embodiment can obtain illuminance information based on sensing data.

[0195] According to one example, the electronic device (100) can obtain illuminance information based on sensing data obtained through at least one of an illuminance sensor, a temperature sensing sensor, a light intensity sensing layer, or a camera (130).

[0196] In operation 820, an electronic device (100) according to one embodiment can identify whether illuminance information is greater than or equal to a preset illuminance. For example, the preset illuminance may be set at the time of manufacture of the electronic device (100) or by a user to determine low illuminance. For example, the preset illuminance may be a value that can be changed by a user. For example, the preset illuminance may be a value that can be changed by a signal received from an external server.

[0197] If the illuminance information is greater than or equal to a preset illuminance (820:Y), in operation 825, the electronic device (100) according to one embodiment can identify whether the zoom distance to the object of interest is greater than or equal to a threshold distance. For example, the threshold distance may be set at the time of manufacture of the electronic device (100) or by the user to determine the recommended resolution according to the zoom distance of the preview image. For example, the threshold distance may be a value that can be changed by the user. For example, the threshold distance may be a value that can be changed by a signal received from an external server.

[0198] According to one example, the zoom distance to an object of interest included in a captured image may be the degree to which the subject is magnified or reduced during shooting. For example, the zoom distance may be implemented optically and / or digitally. For example, the zoom distance may represent a magnification ratio relative to the base focal length. For example, the zoom distance may be indicated as a magnification factor, such as 1x, 2x, or 10x.

[0199] If the zoom distance to the object of interest included in the captured image is greater than or equal to the threshold distance (825:Y), in operation 830, the electronic device (100) according to one embodiment can display a UI recommending a second resolution on the screen.

[0200] If the zoom distance to the object of interest included in the captured image is not greater than or equal to the threshold distance (825:N), in operation 835, the electronic device (100) according to one embodiment can identify whether the zoom distance to the object of interest included in the captured image is less than the threshold distance.

[0201] If the zoom distance to an object of interest included in the captured image is less than the threshold distance (835:Y), the electronic device (100) according to one embodiment may display a UI recommending a third resolution on the screen. According to one example, the third resolution may be a higher resolution than the second resolution.

[0202] In operation 845, the electronic device (100) according to one embodiment can identify whether a shooting command based on a recommended resolution is received through the UI.

[0203] According to one example, a shooting command may be received based on an additional shooting button input displayed along with recommended resolution information. However, this is not limited thereto, and the shooting command may be received based on at least one of a voice command input or a gesture input corresponding to the additional shooting button.

[0204] When a shooting command is received (845:Y), in operation 850, the electronic device (100) according to one embodiment can perform image shooting based on the recommended resolution.

[0205] According to one example, the electronic device (100) can take a high-resolution image using all pixels of the image sensor equipped in the camera (130).

[0206] According to one example, the electronic device (100) can capture a low-resolution image through pixel binning that merges pixels of an image sensor equipped in a camera (130).

[0207] FIG. 9 is a flowchart illustrating the operation of an electronic device according to one embodiment.

[0208] In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0209] According to one embodiment, operations 905 to 925 can be understood as being performed in the processor (110) of the electronic device (100).

[0210] According to one embodiment, detailed descriptions of operations 905 to 925 that partially overlap with operations 305 to 325 shown in FIG. 3 are omitted.

[0211] According to FIG. 9, in operation 905, an electronic device (100) according to one embodiment may provide a screen including an image being captured through a camera (130). According to one example, when a camera application is executed, the electronic device (100) may provide a screen including a preview image.

[0212] In operation 910, the electronic device (100) according to one embodiment can identify whether a shooting command according to the AI ​​shooting mode is received.

[0213] When a shooting command according to the AI ​​shooting mode is received (910:Y), in operation 915, the electronic device (100) according to one embodiment may acquire and store a plurality of shooting images based on each of a plurality of resolutions. According to one example, the electronic device (100) may acquire and store shooting images based on each of a plurality of available resolutions that can be shot. For example, when the plurality of available resolutions are 12MP, 50MP, and 200MP, the electronic device (100) may acquire and store a shooting image at 12MP resolution, a shooting image at 50MP resolution, and a shooting image at 200MP resolution.

[0214] In operation 920, an electronic device (100) according to one embodiment can identify a recommended resolution based on a plurality of captured images.

[0215] According to one embodiment, the electronic device (100) can identify a recommended resolution provided in an AI shooting mode based on at least one of whether the preview image includes a preset object of interest and the dynamic range of the image being shot.

[0216] According to one example, the electronic device (100) can identify a recommended resolution provided in an AI shooting mode when the preview image includes a preset object of interest. For example, the preset object of interest may include at least one of a person, an object, and an animal that has been photographed more than a preset frequency. For example, the preset object of interest may include a landmark of a specific place.

[0217] According to one example, if the electronic device (100) identifies that the dynamic range of the preview image is greater than a certain range, it can identify the recommended resolution provided in the AI ​​shooting mode.

[0218] According to one example, the electronic device (100) can identify a recommended resolution corresponding to the preview image based on at least one of the visual complexity of the preview image, the zoom distance with respect to the object of interest included in the captured image, and the dynamic range of the preview image.

[0219] According to one embodiment, the electronic device (100) can identify a high resolution greater than or equal to a threshold resolution as a recommended resolution if the visual complexity of the preview image is greater than or equal to a specific value or at least one of the zoom distance to the object of interest is greater than or equal to a specific distance. According to one example, if a plurality of images captured include a low resolution image of 12MP, a medium resolution image of 50MP, and a high resolution image of 200MP, the high resolution of 200MP can be identified as a recommended resolution.

[0220] According to one embodiment, the electronic device (100) can acquire illuminance information based on sensing data and identify a recommended resolution based on the illuminance information.

[0221] According to one embodiment, if the illuminance information is less than a preset illuminance, the electronic device (100) can identify a low resolution below a threshold resolution as a recommended resolution. According to one embodiment, the electronic device (100) can identify a recommended resolution provided in AI shooting mode by analyzing at least one of the visual complexity of the preview image, the zoom distance to the object of interest included in the captured image, and the dynamic range of the preview image only when the illuminance information is greater than or equal to a preset illuminance. For example, when the illuminance information is greater than or equal to a preset illuminance, the recommended resolution provided in AI shooting mode may include at least one of a medium resolution and a high resolution.

[0222] In operation 925, the electronic device (100) according to one embodiment may delete the remaining images among the stored multiple images, excluding the image corresponding to the recommended resolution. According to one example, if a high resolution of 200MP is identified as the recommended resolution corresponding to the preview image, the low resolution image of 12MP and the medium resolution image of 50MP, excluding the high resolution image of 200MP, may be deleted from the memory (120).

[0223] FIG. 10 is a diagram illustrating a generative artificial intelligence model according to one embodiment.

[0224]

[0225] According to one embodiment, the artificial intelligence model applied in various examples of the present disclosure can be implemented as a Generative AI Model (1005).

[0226] According to FIG. 10, the User Query / Response Interface (1001) can receive user input. The user input may be in the form of natural language, images and / or videos.

[0227]

[0228] For example, user input may include user voice received through a microphone. However, it is not limited thereto, and user input may include text corresponding to the voice generated by a speech-to-text (STT) model in addition to voice. Furthermore, context information may be transmitted along with the user input. Context information may include various additional information at the time of user input. For example, this may include information about the application currently being used by the user or the user's location information. Additionally, user input may take the form of a mixture of the aforementioned natural language, images, sounds, and context information. Furthermore, user input may also take the form of non-natural language input, such as menu selection.

[0229] The User Query / Response Interface (1001) can output results from a generative artificial intelligence system to the user. The output may be in the form of natural language or specific content, and may also be provided in the form of an action requested by the user. The User query interface (1001) can output results from a generative artificial intelligence system to the user. The output may be in the form of natural language or specific content, and may also be provided in the form of an action requested by the user. For example, the User Query / Response Interface (1001) can output content generated by a Generative AI Model (1005) based on voice received from the user.

[0230] The AI ​​framework (1002) receives user input and can coordinate and control each component necessary to perform the user's intent based on the user's query.

[0231] User input received from the User Query / Response Interface (1001) can be transmitted to the Prompt design component (1002-1). The Prompt design component (1002-1) can be used to generate a prompt suitable for inputting user input into a large language model (LLM) or a large multimodal model (LMM). The Prompt design component (1002-1) may be an AI component that uses machine learning algorithms or neural networks to develop better prompts over time. Based on user input, the Prompt design component (1002-1) can generate a prompt by accessing knowledge repositories (1003) containing user preference data, a prompt library, and prompt examples, and can transmit the generated prompt to the LLM or LMM.

[0232] The API / Plug-in management component (1002-2) can perform the role of communicating with external information when there is a request for additional information while passing user input as input to a generative model. The API / Plug-in management component (1002-2) establishes a channel to communicate with the outside of the AI ​​Interface via API, and can enable access to various data sources through the established channel. Additionally, the API / Plug-in management component (1002-2) can request an action via API if an application or service needs to perform an action that executes the user input as a final step, rather than an intermediate result. Information obtained from the outside (e.g., the Applications / service component (1004)) may be used to generate a prompt in the Prompt design component (1002-1) along with user input, or it may be passed as input to the generative model.

[0233] The Output modification Component (1002-3) (or Refiner component) can fine-tune the output of the generative model. For example, the Output modification Component (1002-3) can verify whether the content generated through LLM and / or LMM is irrelevant, contains biased content, or contains harmful content. Additionally, the Output modification Component (1002-3) can determine the extent to which the output matches the desired result and, if additional processing is required, proceed with that process. Furthermore, the Output modification Component (1002-3) can configure and provide hints to the user to avoid unwanted output.

[0234] A Generative AI Model (1005) generally refers to an artificial intelligence neural network that generates new forms of data based on user input information. A Generative AI Model (1005) may include models that generate images and / or models that generate language. Models that generate images include, but are not limited to, GANs (generative adversarial networks) and VAEs (variational autoencoders), and examples include Diffusion-based generative models that use VAEs and Transformer structures. Models that generate language are models trained to output the most statistically appropriate output value based on input values, and examples include models such as CHAT-GPT 3 and CHAT-GPT 4 (e.g., CHAT-GPT 4o). There are also LMMs (large multimodal models) that can recognize various forms of data input, such as text, images, and voice, and generate new data corresponding to them.

[0235] According to an embodiment, when a prompt is input from the Prompt design component (1002-1), the Generative AI Model (1005) generates content corresponding to the prompt based on the instructions and can output the content through the User Query / Response Interface (1001).

[0236] FIG. 11 is a drawing illustrating a method for providing a UI for resolution recommendation according to one embodiment.

[0237] According to one embodiment, the electronic device (100) can provide a UI that includes information about a recommended resolution corresponding to a preview image at a specific illuminance or higher.

[0238] According to an example illustrated on the left side of FIG. 11, when a recommended resolution corresponding to a preview image (1110) is identified, the electronic device (100) may provide an additional shooting button (1130) containing information about the recommended resolution on one side of an existing shooting button (1120). For example, the recommended resolution information may be displayed inside the additional shooting button (1130) as illustrated in FIG. 11. For example, if the recommended resolution information is 200MP, a number such as "200M" may be displayed inside the additional shooting button. However, this is not limited thereto, and the recommended resolution information may also be displayed on one side of the additional shooting button (1130).

[0239] According to an example illustrated on the right side of FIG. 11, when an additional shooting button (1130) is selected by a first user input and a shooting command is received, shooting can be performed at a recommended resolution of 200MP. According to an example, the shooting command may be received based on at least one of a voice command input or a gesture input corresponding to the additional shooting button. For example, the first type of user input may be a touch and release input. A touch and release input may be a method of conveying a command by the action of the user pressing and releasing the screen.

[0240] According to one example, the shooting command may be a user command that touches an existing shooting button and drags it to an additional shooting button. According to one example, the shooting command may be a user command that touches an existing shooting button and drags and releases it to an additional shooting button. FIG. 12 is a diagram illustrating a method for providing a UI for resolution recommendation according to one embodiment.

[0241] According to one embodiment, the electronic device (100) can provide a UI for automatic low-resolution shooting at less than a certain illuminance.

[0242] According to an example illustrated on the left side of FIG. 12, if the electronic device (100) identifies that the ambient light is less than a certain light level, it may provide an additional shooting button (1230) on one side of the existing shooting button (1220) that recommends low-resolution shooting. For example, as illustrated in FIG. 12, the additional shooting button (1230) may include information such as "Night" indicating low-resolution shooting. However, it is not limited thereto, and instead of the information "Night," a numerical value corresponding to low resolution (e.g., 12M) may be provided on the additional shooting button (1230). According to an example, information indicating low-resolution shooting (e.g., Night, 12M) may be displayed on one side of the additional shooting button (1230).

[0243] According to one example illustrated on the right side of FIG. 12, when an additional shooting button (1230) is selected by user input (e.g., touch and hold input) and a shooting command is received, shooting can be performed at a recommended resolution of 12MP. According to one example, the shooting command may be received based on at least one of a voice command input or a gesture input corresponding to the additional shooting button.

[0244] FIG. 13 is a drawing illustrating a method for providing a UI for resolution recommendation according to one embodiment.

[0245] According to one embodiment, the electronic device (100) provides a UI containing information about a recommended resolution corresponding to a preview image at a specific illumination level or higher, and can adjust the resolution according to a user selection entered through the UI.

[0246] According to an example illustrated on the far left of FIG. 13, when a recommended resolution corresponding to a preview image (1310) is identified, the electronic device (100) may provide an additional shooting button (1330) containing information about the recommended resolution on one side of an existing shooting button (1320). For example, the recommended resolution information may be displayed inside the additional shooting button (1330) as illustrated in FIG. 13. For example, if the recommended resolution information is 200MP, a number such as "200M" may be displayed inside the additional shooting button.

[0247] According to an example illustrated in the center of FIG. 13, the electronic device (100) may provide additional resolution information for resolution adjustment when an additional shooting button (1130) is selected by a second type user input. For example, the electronic device (100) may provide a GUI (1331) containing "50M", which is additional resolution information, on one side (e.g., the left side) of the additional shooting button (1130). For example, the second type user input may include at least one of a long press input or a touch and hold input. The long press input and the touch and hold input may be input methods that execute a specific command through an action in which the user presses the screen for a certain period of time or longer.

[0248] According to an example illustrated on the far right of FIG. 13, shooting can be performed according to "50M", which is additional resolution information, based on a third type user input to a GUI (1331) that includes additional resolution information. For example, the third type input may be a drag and release input. For example, shooting corresponding to the additional resolution information can be performed based on a user input in which a touch object (e.g., finger, stylus pen) is dragged from the additional shooting button (1130) to the GUI (1331) and then released from the GUI (1331).

[0249] FIG. 14 is a block diagram of an electronic device in a network environment according to various embodiments.

[0250] The electronic device (2401) can be implemented as the electronic device (100) shown in FIG. 2 according to one example.

[0251] Referring to FIG. 14, in a network environment (2400), an electronic device (2401) may communicate with an electronic device (2402) through a first network (2498) (e.g., a short-range wireless communication network) or with at least one of an electronic device (2404) or a server (2408) through a second network (2499) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (2401) may communicate with the electronic device (2404) through a server (2408). According to one embodiment, the electronic device (2401) may include a processor (2420), memory (2430), input module (2450), sound output module (2455), display module (2460), audio module (2470), sensor module (2476), interface (2477), connection terminal (2478), haptic module (2479), camera module (2480), power management module (2488), battery (2489), communication module (2490), subscriber identification module (2496), or antenna module (2497). In some embodiments, at least one of these components (e.g., connection terminal (2478)) may be omitted from the electronic device (2401), or one or more other components may be added. In some embodiments, some of these components (e.g., sensor module (2476), camera module (2480), or antenna module (2497)) may be integrated into a single component (e.g., display module (2460)).

[0252] The processor (2420) can, for example, execute software (e.g., program (2440)) to control at least one other component (e.g., hardware or software component) of the electronic device (2401) connected to the processor (2420) and can perform various data processing or operations. According to one embodiment, as at least part of the data processing or operations, the processor (2420) can store commands or data received from other components (e.g., sensor module (2476) or communication module (2490)) in volatile memory (2432), process the commands or data stored in volatile memory (2432), and store the resulting data in non-volatile memory (2434). According to one embodiment, the processor (2420) may include a main processor (2421) (e.g., a central processing unit or an application processor) or an auxiliary processor (2423) that can operate independently or together with it (e.g., a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor). For example, if the electronic device (2401) includes a main processor (2421) and an auxiliary processor (2423), the auxiliary processor (2423) may be configured to use lower power than the main processor (2421) or to be specialized for a specified function. The auxiliary processor (2423) may be implemented separately from the main processor (2421) or as part thereof.

[0253] The auxiliary processor (2423) may control at least some of the functions or states associated with at least one component of the electronic device (2401) (e.g., display module (2460), sensor module (2476), or communication module (2490)) on behalf of the main processor (2421) while the main processor (2421) is in an inactive (e.g., sleep) state, or together with the main processor (2421) while the main processor (2421) is in an active (e.g., application execution) state. According to one embodiment, the auxiliary processor (2423) (e.g., image signal processor or communication processor) may be implemented as part of another functionally related component (e.g., camera module (2480) or communication module (2490)). According to one embodiment, the auxiliary processor (2423) (e.g., neural network processing unit) may include a hardware structure specialized for processing an artificial intelligence model. The artificial intelligence model may be generated through machine learning. Such learning may be performed, for example, on the electronic device (2401) itself where the artificial intelligence model is executed, or through a separate server (e.g., server (2408)). The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model may include a plurality of artificial neural network layers.An artificial neural network may be a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to the hardware structure, an artificial intelligence model may include a software structure, either additionally or substantially.

[0254] The memory (2430) can store various data used by at least one component of the electronic device (2401) (e.g., processor (2420) or sensor module (2476)). The data may include, for example, input data or output data for software (e.g., program (2440)) and related commands. The memory (2430) may include volatile memory (2432) or non-volatile memory (2434).

[0255] The program (2440) may be stored as software in memory (2430) and may include, for example, an operating system (1442), middleware (1444), or an application (1446).

[0256] The input module (2450) can receive commands or data to be used for a component of the electronic device (2401) (e.g., processor (2420)) from outside the electronic device (2401) (e.g., user). The input module (2450) may include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0257] The sound output module (2455) can output a sound signal to the outside of the electronic device (2401). The sound output module (2455) may include, for example, a speaker or a receiver. The speaker may be used for general purposes, such as multimedia playback or recording playback. The receiver may be used to receive incoming calls. According to one embodiment, the receiver may be implemented separately from the speaker or as part thereof.

[0258] The display module (2460) can visually provide information to an external (e.g., user) of the electronic device (2401). The display module (2460) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling said device. According to one embodiment, the display module (2460) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of the force generated by said touch.

[0259] The audio module (2470) can convert sound into an electrical signal or, conversely, convert an electrical signal into sound. According to one embodiment, the audio module (2470) can acquire sound through the input module (2450) or output sound through the sound output module (2455) or an external electronic device (e.g., electronic device (2402)) (e.g., speaker or headphones) connected directly or wirelessly to the electronic device (2401).

[0260] The sensor module (2476) can detect the operating state of the electronic device (2401) (e.g., power or temperature) or the external environmental state (e.g., user state) and generate an electrical signal or data value corresponding to the detected state. According to one embodiment, the sensor module (2476) may include, for example, a gesture sensor, a gyroscope sensor, a barometric pressure sensor, a magnetic sensor, an accelerometer sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biosensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0261] The interface (2477) may support one or more specified protocols that can be used for the electronic device (2401) to be connected directly or wirelessly to an external electronic device (e.g., electronic device (2402)). According to one embodiment, the interface (2477) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0262] The connection terminal (2478) may include a connector through which the electronic device (2401) can be physically connected to an external electronic device (e.g., electronic device (2402)). According to one embodiment, the connection terminal (2478) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0263] The haptic module (2479) can convert an electrical signal into a mechanical stimulus (e.g., vibration or movement) or an electrical stimulus that can be perceived by the user through tactile or kinesthetic senses. According to one embodiment, the haptic module (2479) may include, for example, a motor, a piezoelectric element, or an electric stimulation device.

[0264] The camera module (2480) can capture still images and video. According to one embodiment, the camera module (2480) may include one or more lenses, image sensors, image signal processors, or flashes.

[0265] The power management module (2488) can manage power supplied to the electronic device (2401). According to one embodiment, the power management module (2488) can be implemented, for example, as at least part of a power management integrated circuit (PMIC).

[0266] The battery (2489) can supply power to at least one component of the electronic device (2401). According to one embodiment, the battery (2489) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0267] The communication module (2490) can support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between an electronic device (2401) and an external electronic device (e.g., electronic device (2402), electronic device (2404), or server (2408)), and the performance of communication through the established communication channel. The communication module (2490) may include one or more communication processors that operate independently of the processor (2420) (e.g., application processor) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (2490) may include a wireless communication module (2492) (e.g., cellular communication module, short-range wireless communication module, or GNSS (global navigation satellite system) communication module) or a wired communication module (1494) (e.g., LAN (local area network) communication module, or power line communication module). Among these communication modules, the communication module described above can communicate with an external electronic device (2404) through a first network (2498) (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network (2499) (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN). These various types of communication modules may be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (2492) can identify or authenticate the electronic device (2401) within a communication network such as the first network (2498) or the second network (2499) using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module (2496).

[0268] The wireless communication module (2492) can support 5G networks and next-generation communication technologies following 4G networks, for example, new radio access technology. NR access technology can support high-speed transmission of high-capacity data (enhanced mobile broadband (eMBB)), minimization of terminal power and connection of multiple terminals (massive machine type communications (mMTC)), or high reliability and low latency (ultra-reliable and low-latency communications (URLLC)). The wireless communication module (2492) can support a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate, for example. The wireless communication module (2492) can support various technologies for securing performance in the high-frequency band, such as beamforming, massive MIMO (multiple-input and multiple-output), full-dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large-scale antenna. The wireless communication module (2492) can support various requirements specified in the electronic device (2401), external electronic device (e.g., electronic device (2404)), or network system (e.g., second network (2499)). According to one embodiment, the wireless communication module (2492) can support a Peak data rate (e.g., 20 Gbps or more) for realizing eMBB, loss coverage (e.g., 164 dB or less) for realizing mMTC, or U-plane latency (e.g., downlink (DL) and uplink (UL) each 0.5 ms or less, or round trip 1 ms or less) for realizing URLLC.

[0269] An antenna module (2497) can transmit a signal or power to or from an external source (e.g., an external electronic device). According to one embodiment, the antenna module (2497) may include an antenna comprising a radiator made of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). According to one embodiment, the antenna module (2497) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as a first network (2498) or a second network (2499), may be selected from the plurality of antennas, for example, by a communication module (2490). A signal or power may be transmitted or received between the communication module (2490) and an external electronic device through the selected at least one antenna. According to some embodiments, in addition to the radiator, other components (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as part of the antenna module (2497).

[0270] According to various embodiments, the antenna module (2497) may form a mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent to a first surface (e.g., bottom surface) of the printed circuit board and capable of supporting a specified high frequency band (e.g., mmWave band), and a plurality of antennas (e.g., array antennas) disposed on or adjacent to a second surface (e.g., top surface or side surface) of the printed circuit board and capable of transmitting or receiving a signal of the specified high frequency band.

[0271] At least some of the above components can be connected to each other via a communication method between peripheral devices (e.g., bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)) and exchange signals (e.g., commands or data) with each other.

[0272] According to one embodiment, commands or data may be transmitted or received between the electronic device (2401) and an external electronic device (2404) through a server (2408) connected to a second network (2499). Each of the external electronic devices (2402, or 2404) may be the same or a different type of device as the electronic device (2401). According to one embodiment, all or part of the operations performed on the electronic device (2401) may be performed on one or more of the external electronic devices (2402, 2404, or 2408). For example, if the electronic device (2401) needs to perform a function or service automatically or in response to a request from a user or another device, the electronic device (2401) may request one or more external electronic devices to perform at least part of the function or service instead of performing the function or service itself or additionally. One or more external electronic devices that receive the above request may execute at least part of the requested function or service, or additional function or service related to the request, and transmit the result of the execution to the electronic device (2401). The electronic device (2401) may provide the result as is or additionally processed as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device (2401) may provide ultra-low latency services using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device (2404) may include an Internet of Things (IoT) device. The server (2408) may be an intelligent server using machine learning and / or neural networks.According to one embodiment, an external electronic device (2404) or server (2408) may be included within the second network (2499). The electronic device (2401) may be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0273]

[0274] According to one embodiment, an electronic device (100) comprises a camera (130); a display (140); a memory (120) for storing instructions; and at least one processor (110) including processing circuitry, wherein when the instructions are executed individually or collectively by the at least one processor, the electronic device provides a screen including a preview image acquired by the camera through the display, identifies a recommended resolution for capturing an image among a plurality of resolutions based on at least one of ambient illumination or the visual complexity of the preview image, and, when a shooting command is received, performs image capture based on the recommended resolution.

[0275] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may display a UI containing information about the recommended resolution on a screen including the preview image, and when a shooting command based on the recommended resolution is received through the UI, the device may perform shooting based on the recommended resolution.

[0276] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may display a first UI item for receiving user input to take an image according to a default resolution on the screen, display a second UI item on the screen containing information about the recommended resolution, and perform taking based on the recommended resolution according to a shooting command received through the second UI item.

[0277] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may identify the recommended resolution based on at least one of the ambient illumination or the visual complexity of the preview image through a learned artificial intelligence model.

[0278] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may identify the recommended resolution based on at least one of whether the preview image includes a preset object of interest and the dynamic range of the preview image.

[0279] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device inputs the preview image into a learned artificial intelligence model to identify whether the preview image includes a preset object of interest, and if the preview image is identified as including an object of interest, identifies the recommended resolution, and the learned artificial intelligence model may be trained to identify whether the input image includes the preset object of interest.

[0280] The aforementioned pre-set object of interest may include at least one of a person, object, and animal that has been photographed more than a pre-set frequency, or may include a landmark of a specific place.

[0281] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may identify the recommended resolution if it is identified that the dynamic range of the preview image is greater than or equal to a specific range.

[0282] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may identify the recommended resolution based on the zoom distance with the preset object of interest.

[0283] According to one embodiment, the device further includes a sensor; and when the instructions are executed individually or collectively by the at least one processor, the electronic device acquires illuminance information based on sensing data acquired through the sensor, and if the illuminance information is less than a preset illuminance, displays a UI recommending a first resolution on a screen including the preview image, and if the illuminance information is greater than or equal to a preset illuminance, displays a UI recommending a second resolution or a third resolution on a screen including the preview image, and the first resolution may be a resolution lower than the second resolution and the third resolution.

[0284] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device identifies the visual complexity of the preview image if the illuminance information is greater than or equal to the preset illuminance, displays a UI recommending the second resolution on a screen including the preview image if the visual complexity of the preview image is less than the threshold complexity, and displays a UI recommending the third resolution on a screen including the image being captured if the visual complexity of the preview image is greater than or equal to the threshold complexity, and the second resolution may be a resolution lower than the third resolution.

[0285] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device identifies the zoom distance to an object of interest included in the preview image if the illuminance information is greater than or equal to the preset illuminance, displays a UI recommending the third resolution on a screen including the preview image if the zoom distance to the object of interest is less than a threshold distance, and displays a UI recommending the second resolution on a screen including the preview image if the zoom distance to the object of interest is greater than or equal to the threshold distance, and the second resolution may be a resolution lower than the third resolution.

[0286] An electronic device (100) according to one embodiment comprises: a camera (130); a display (140); a memory (120) for storing instructions; and at least one processor (110) including a processing circuitry. When the instructions are executed individually or collectively by the at least one processor, the electronic device provides a screen through the display that includes a preview image acquired by the camera, and when a shooting command is received, acquires a plurality of captured images based on each of a plurality of resolutions and stores them in the memory. When a recommended resolution is identified based on at least one of ambient illumination or the visual complexity of the preview image, the electronic device deletes the remaining captured images from the memory, excluding the captured image corresponding to the recommended resolution among the plurality of captured images stored in the memory.

[0287] According to one embodiment, a control method for an electronic device comprises: providing a screen including a preview image acquired by a camera through a display; identifying a recommended resolution for capturing an image among a plurality of resolutions based on at least one of ambient illumination or the visual complexity of the preview image; and, when a shooting command is received, performing image capture based on the recommended resolution.

[0288] According to one embodiment, the control method further includes the operation of displaying a UI containing information about the recommended resolution on a screen including the preview image; and the operation of performing the shooting may include the operation of performing the shooting based on the recommended resolution when a shooting command based on the recommended resolution is received through the UI.

[0289] According to one embodiment, the control method may further include: an operation of displaying a first UI item on the screen to receive user input for capturing an image according to a default resolution; an operation of displaying a second UI item on the screen including information about the recommended resolution; and an operation of performing a shot based on the recommended resolution according to a shooting command received through the second UI item.

[0290] According to one embodiment, the operation of identifying the recommended resolution may include identifying the recommended resolution based on at least one of the ambient illumination or the visual complexity of the preview image through a learned artificial intelligence model.

[0291] According to one embodiment, the operation of identifying the recommended resolution may include the operation of identifying the recommended resolution based on at least one of whether the preview image includes a preset object of interest and the dynamic range of the preview image.

[0292] According to one embodiment, the operation of identifying the recommended resolution comprises: inputting the preview image into a trained artificial intelligence model to identify whether the preview image includes a preset object of interest; and, if the preview image is identified as including the object of interest, identifying the recommended resolution; wherein the trained artificial intelligence model may be trained to identify whether the input image includes the preset object of interest.

[0293] According to one embodiment, the control method further comprises: an operation of acquiring illuminance information based on sensing data acquired through a sensor; an operation of displaying a UI recommending a first resolution on a screen including the preview image if the illuminance information is less than a preset illuminance; and an operation of displaying a UI recommending a second resolution or a third resolution on a screen including the preview image if the illuminance information is greater than or equal to a preset illuminance, wherein the first resolution may be a resolution lower than the second resolution and the third resolution.

[0294] According to one embodiment, in a non-transient computer-readable medium storing instructions that cause the electronic device to perform an operation when executed by a processor of the electronic device, the operation comprises: providing a screen containing a preview image acquired by a camera through a display; identifying a recommended resolution among a plurality of resolutions for capturing an image based on at least one of ambient illumination or the visual complexity of the preview image; and, when a shooting command is received, capturing an image based on the recommended resolution.

[0295] According to the various embodiments described above, it is possible to efficiently manage storage space while providing the user with a high-quality shooting experience.

[0296] Although the various embodiments described above use multiple individual neural network models, the operation of at least two of the multiple neural network models may be implemented in a single neural network model.

[0297] Each operation according to the various embodiments described above may be performed by the processor (110), but if necessary, a module for each operation may be used. For example, each module may be implemented with at least one software, at least one hardware, and / or a combination thereof. Each module may be implemented to use a predefined algorithm, a predefined formula, and / or a learned artificial intelligence model to perform the operation. However, at least some modules may be distributed to external devices.

[0298] The methods according to the various embodiments of the present disclosure described above may be implemented in the form of an application that can be installed on an existing electronic device. Alternatively, the methods according to the various embodiments of the present disclosure described above may be performed using a deep learning-based artificial neural network (or deep artificial neural network), that is, a learning network model.

[0299] The methods according to the various embodiments of the present disclosure described above can be implemented by software upgrades or hardware upgrades alone for existing electronic devices.

[0300] The various embodiments of the present disclosure described above may also be performed through an embedded server equipped in an electronic device or an external server of the electronic device.

[0301] According to a specific example of the present disclosure, the various embodiments described above may be implemented as software comprising instructions stored on a machine-readable storage medium (e.g., a computer). The machine may include an electronic device (e.g., electronic device (A)) according to the disclosed embodiments, which is a device capable of calling instructions stored from the storage medium and operating according to the called instructions. When instructions are executed by a processor, the processor may perform a function corresponding to the instructions directly or by using other components under the control of the processor. Instructions may include code generated or executed by a compiler or an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, "non-transitory" means only that the storage medium does not contain a signal and is tangible, and does not distinguish whether data is stored semi-permanently or temporarily in the storage medium.

[0302] Additionally, according to one embodiment of the present disclosure, the method according to the various embodiments described above may be provided as included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)) or online through an application store (e.g., Play Store™). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created in a storage medium such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0303] Additionally, each component (e.g., module or program) according to the various embodiments described above may be composed of a single or multiple entities, and some of the aforementioned sub-components may be omitted, or other sub-components may be further included in the various embodiments. Generally or additionally, some components (e.g., module or program) may be integrated into a single entity to perform the functions performed by each of the respective components prior to integration in the same or similar manner. The operations performed by the module, program, or other components according to the various embodiments may be executed sequentially, in parallel, iteratively, or heuristically, or at least some operations may be executed in a different order, omitted, or other operations added.

[0304] Although an embodiment of the present disclosure has been illustrated and described above, the embodiments are not limited to the specific embodiment described above. It is understood that various modifications can be made by those skilled in the art without departing from the gist of the present disclosure as claimed in the claims, and such modifications should not be understood individually from the technical spirit or perspective of the present disclosure.

Claims

1. In an electronic device (100), Camera (130); Display (140); Memory (120) for storing instructions; and It includes at least one processor (110) including a processing circuitry; and When the above instructions are executed individually or collectively by the at least one processor, the electronic device, A screen including a preview image acquired by the camera is provided through the display, and Identifying a recommended resolution for capturing an image among a plurality of resolutions based on at least one of ambient illumination or the visual complexity of the preview image, and An electronic device that performs image capture based on the recommended resolution when a shooting command is received.

2. In Paragraph 1, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, A UI including information about the above recommended resolution is displayed on a screen including the above preview image, and An electronic device that performs shooting based on the recommended resolution when a shooting command based on the recommended resolution is received through the UI above.

3. In Paragraph 1 or 2, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, Displays a first UI item on the above screen for receiving user input to capture an image according to the default resolution, and Displaying a second UI item on the screen containing information about the recommended resolution, An electronic device that performs shooting based on the recommended resolution according to a shooting command received through the second UI item.

4. In Paragraph 1 or 2, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, An electronic device that identifies the recommended resolution based on at least one of the ambient illuminance or the visual complexity of the preview image through a learned artificial intelligence model.

5. In Paragraph 1 or 2, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, An electronic device that identifies the recommended resolution based on at least one of whether the preview image includes a preset object of interest and the dynamic range of the preview image.

6. In Paragraph 5, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, Input the above preview image into a trained artificial intelligence model to identify whether the above preview image includes a pre-set object of interest, and If the above preview image is identified as containing an object of interest, the above recommended resolution is identified, and The above-mentioned trained artificial intelligence model is, An electronic device trained to identify whether an input image includes the aforementioned pre-set object of interest.

7. In Paragraph 5 or 6, The previously configured interest object above is, An electronic device comprising at least one of a person, object, and animal that has been photographed more than a preset frequency, or comprising a landmark of a specific place.

8. In any one of paragraphs 3 through 7, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, An electronic device that identifies the recommended resolution when the dynamic range of the above preview image is identified to be greater than a specific range.

9. In any one of Paragraph 5, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, An electronic device that identifies the recommended resolution based on the zoom distance with the previously set object of interest.

10. In any one of paragraphs 1 through 9, It further includes a sensor; When the above instructions are executed individually or collectively by the at least one processor, the electronic device, Based on the sensing data obtained through the above sensor, the illuminance information is obtained, and If the above illuminance information is less than a preset illuminance, a UI recommending a first resolution is displayed on a screen including the above preview image, and If the above illuminance information is greater than or equal to a preset illuminance, a UI recommending a second or third resolution is displayed on the screen including the above preview image, and The above first resolution is, An electronic device having a resolution lower than the second resolution and the third resolution.

11. In Paragraph 10, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, If the above illuminance information is greater than or equal to the above preset illuminance, the visual complexity of the above preview image is identified, and If the visual complexity of the above preview image is less than the critical complexity, a UI recommending the above second resolution is displayed on the screen including the above preview image, and If the visual complexity of the above preview image is greater than or equal to the above threshold complexity, a UI recommending the above third resolution is displayed on the screen including the image being captured, and The above second resolution is, An electronic device having a resolution lower than the third resolution mentioned above.

12. In Paragraph 10 or 11, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, If the above illuminance information is greater than or equal to the above preset illuminance, the zoom distance with the object of interest included in the above preview image is identified, and If the zoom distance with the object of interest is less than the threshold distance, a UI recommending the third resolution is displayed on the screen including the preview image, and If the zoom distance with the object of interest is greater than or equal to the threshold distance, a UI recommending the second resolution is displayed on the screen including the preview image, and The above second resolution is, An electronic device having a resolution lower than the third resolution mentioned above.

13. In an electronic device (100), Camera (130); Display (140); Memory (120) for storing instructions; and It includes at least one processor (110) including a processing circuitry; and When the above instructions are executed individually or collectively by the at least one processor, the electronic device, A screen including a preview image acquired by the camera is provided through the display, and When a shooting command is received, multiple captured images are acquired based on each of the multiple resolutions and stored in the memory, and An electronic device that, when a recommended resolution is identified based on at least one of ambient illumination or the visual complexity of the preview image, deletes from the memory all other captured images except for the captured image corresponding to the recommended resolution among the plurality of captured images stored in the memory.

14. In a method for controlling an electronic device, The operation of providing a screen containing a preview image acquired by a camera through a display; An operation to identify a recommended resolution for capturing an image among a plurality of resolutions based on at least one of ambient illumination or the visual complexity of the preview image; and A control method comprising: an action of capturing an image based on the recommended resolution when a shooting command is received.

15. A non-transient computer-readable medium storing instructions that cause said electronic device to perform an operation when executed by a processor of said electronic device, The above operation is, The operation of providing a screen containing a preview image acquired by a camera through a display; An operation to identify a recommended resolution for capturing an image among a plurality of resolutions based on at least one of ambient illumination or the visual complexity of the preview image; and A non-transient computer-readable medium comprising: an operation of capturing an image based on the recommended resolution when a shooting command is received.

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