Electronic device for adjusting ambient brightness, control method, and non-transitory computer-readable storage medium

Abstract

This electronic device comprises: a display disposed on the front surface thereof; at least one light-emitting element disposed on the rear surface thereof; a sensor; a memory for storing instructions; and at least one processor including processing circuitry, wherein, when executed individually or collectively by the at least one processor, the instructions instruct the electronic device to: acquire, on the basis of sensing data acquired through the sensor, first brightness information corresponding to a space in which the electronic device is positioned; acquire second brightness information corresponding to the screen brightness of the display when the first brightness information is less than a preset value; acquire, on the basis of a contrast ratio between the first brightness information and the second brightness information, third brightness information for adjusting the ambient brightness of the electronic device; and control, on the basis of the third brightness information, light emission of the at least one light-emitting element disposed on the rear surface of the electronic device.

Description

Electronic device for adjusting ambient brightness, control method, and non-transient computer-readable storage medium

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

[0002] Driven by advancements in electronic technology, various types of electronic devices are being developed and distributed. In particular, various forms of portable electronic devices, such as smartphones, tablets, wireless earphones, and smartwatches, have been continuously evolving over the past few years.

[0003] With the widespread adoption of portable electronic devices, there is an increasing number of instances where users view small screens, such as smartphones, for extended periods in dark environments. This leads to increased eye strain for users.

[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 display disposed on the front of the electronic device; at least one light-emitting element disposed on the rear of the electronic device; a sensor; a memory for storing instructions; and at least one processor including a processing circuit. When the instructions are executed individually or collectively by the at least one processor, the electronic device acquires first brightness information corresponding to the space where the electronic device is located based on sensing data acquired through the sensor; if the first brightness information is less than a preset value, acquires second brightness information corresponding to the screen brightness of the display; acquires third brightness information for adjusting the ambient brightness of the electronic device based on the contrast ratio between the first brightness information and the second brightness information; and controls the light emission of at least one light-emitting element disposed on the rear of the electronic device based on the third brightness information.

[0006] A control method for an electronic device according to one embodiment comprises: acquiring first brightness information corresponding to a space where the electronic device is located based on sensing data acquired through a sensor; acquiring second brightness information corresponding to a screen brightness of a display disposed on the front of the electronic device if the first brightness information is less than a preset value; acquiring third brightness information for adjusting the ambient brightness of the electronic device based on a contrast ratio between the first brightness information and the second brightness information; and controlling the light emission of at least one light-emitting element disposed on the rear of the electronic device based on the third brightness information.

[0007] A non-transient computer-readable medium storing computer 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: an operation of acquiring first brightness information corresponding to a space where the electronic device is located based on sensing data acquired through a sensor; an operation of acquiring second brightness information corresponding to a screen brightness of a display disposed on the front of the electronic device if the first brightness information is less than a preset value; an operation of acquiring third brightness information for adjusting the ambient brightness of the electronic device based on a contrast ratio between the first brightness information and the second brightness information; and an operation of controlling the light emission of at least one light-emitting element disposed on the rear of the electronic device based on the third brightness information.

[0008] The above and other aspects and features of specific embodiments of the present disclosure will become more apparent from the following description taken together with the accompanying drawings.

[0009] FIGS. 1A, FIGS. 1B, and FIGS. 1C are drawings for illustrating a human vision system according to one embodiment.

[0010] FIG. 2 illustrates an example of a block diagram of an electronic device according to one embodiment.

[0011] FIG. 3 is a flowchart illustrating an example of a control method for an electronic device according to one embodiment.

[0012] FIGS. 4A, FIGS. 4B, FIGS. 4C, and FIGS. 4D are drawings for explaining an example of the operation method of a brightness calculation model according to one embodiment.

[0013] FIG. 5 is a diagram illustrating an example of the operation method of a brightness calculation model according to one embodiment.

[0014] FIGS. 6A, FIGS. 6B, FIGS. 6C, and FIGS. 6D are drawings for explaining an example of the operation method of a brightness calculation model according to one embodiment.

[0015] FIG. 7 is a drawing for explaining an example of the operation method of a brightness calculation model according to one embodiment.

[0016] FIG. 8 is a drawing for explaining an example of a method for adjusting the brightness of a bright light element according to one embodiment.

[0017] FIG. 9 is a drawing for explaining an example of a method for adjusting the brightness of a bright light element according to one embodiment.

[0018] FIG. 10 is a drawing for explaining an example of a background brightness adjustment method according to one embodiment.

[0019] FIG. 11 is a drawing for explaining an example of a background brightness adjustment method according to one embodiment.

[0020] FIG. 12 is a drawing for explaining an example of a background brightness adjustment method according to one embodiment.

[0021] FIGS. 13a and FIGS. 13b are drawings for explaining an example of a light-emitting element according to one embodiment.

[0022] FIGS. 14a and FIGS. 14b are drawings for explaining an example of a light-emitting element according to one embodiment.

[0023] FIG. 15 is a flowchart illustrating an example of a method for providing a vision protection function according to one embodiment.

[0024] FIG. 16 is a block diagram of an electronic device in a network environment according to various embodiments.

[0025] The present disclosure will be described in detail below with reference to the attached drawings.

[0026] The terms used in the embodiments of this disclosure have been selected to be as widely used 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, the emergence of new technologies, etc. 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, the terms used in this disclosure should be defined based on their meanings and the overall content of this disclosure, rather than merely their names (such as analyzing calls, messages, schedules, etc.).

[0027] In this specification, expressions such as “have,” “may have,” “include,” or “may include” indicate the presence of the above features (e.g., numerical values, functions, actions, or components such as parts) and do not exclude the presence of additional features.

[0028] The expression "at least one of A or / and B" should be understood as representing either "A" or "B" or "A and B".

[0029] 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.

[0030] 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).

[0031] The singular expression includes the plural expression unless the context clearly indicates otherwise. In this application, terms such as “comprising” or “consisting of” are intended to specify the existence of the features, numbers, steps, 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, steps, actions, components, parts, or combinations thereof.

[0032] 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.

[0033] 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).

[0034] 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.

[0035] Embodiments of the present disclosure will be described in more detail below with reference to the attached drawings.

[0036] FIGS. 1a and FIGS. 1b are drawings for illustrating a human vision system according to one embodiment.

[0037] FIG. 1a is a diagram illustrating the visual stimulation phenomenon of an electronic device (100) based on the human visual system.

[0038] The left drawing (10) of FIG. 1a illustrates an example of a color appearance model according to one example. For example, the color appearance model may be CIECAM02, published by the International Commission on Illumination (CIE) in 2002. CIECAM02 is designed to mimic the human visual system that perceives color and can enable color recognition and comparison. Among the CAM02 models, the SFB (surround field background) model is a part that processes spatial information, and the SFB model can model the background remaining outside the area occupied by the object within the surround field. The surround field may be the area of ​​the observer's field of vision around the object being observed. The background may be a color and / or pattern located immediately behind the object being observed.

[0039] Depending on the example, SFB models can be divided into LSF (local surround field) and GSF (global surround field). For instance, the LSF can model the local background surrounding the object of interest, while the GSF can model the entire scene. The LSF processes nearby textures or patterns around the object of interest and reduces the difference between the object and its surrounding environment, allowing the object's colors to appear harmonious with the surroundings as seen by humans. The GSF processes information about distant areas or the entire scene; it is important for ensuring consistency across the entire space and can also be used to respond to environmental changes, such as variations in lighting conditions.

[0040] Ultimately, the CIE CAM02 SFB model was developed based on a deep understanding of how the human visual system perceives and understands various color changes, and can be utilized in various application fields such as display calibration, image quality evaluation, and visual communication.

[0041] The right drawing (20) of FIG. 1a illustrates the case where the principle of the SFB model is applied when viewing an electronic device (100) (e.g., a smartphone) in a dark environment. For example, as shown in FIG. 1b when using a smartphone, the user's effective field of view is significantly reduced, and in a dark environment, the field of view is almost entirely focused on the smartphone, so the principle of the SFB model can be applied.

[0042] According to FIG. 1c, when viewing the electronic device (100) in a dark environment (30), visual fatigue may increase compared to when viewing the electronic device (100) on a relatively bright screen (40). For example, visual fatigue may include stress or strain on the eyes.

[0043] According to research, the reason people's eyes get tired quickly when looking at a bright screen in a dark environment is due to the difference in brightness between the screen and the surrounding environment. This implies that eye health can be deteriorated due to continuous stimulation. However, if the screen brightness is excessively lowered (50) to reduce the difference in brightness with the surrounding environment, the dynamic range of the image is narrowed and the ability to express gradation is reduced, resulting in a problem where the satisfaction of the viewing experience is lower compared to cases where this is not done (60). For example, viewing fatigue may occur due to reduced perception of gradation. In particular, when using a device with a small screen, such as a smartphone, in a dark environment, the screen brightness shows a large difference from the surrounding environment, so the resulting eye fatigue can become more severe.

[0044] Accordingly, the following describes various embodiments for adjusting the brightness and / or color of the electronic device (100) to minimize the difference between screen brightness and ambient brightness when viewing the electronic device (100) in a dark environment, thereby reducing eye strain for the user and satisfying the user's viewing experience.

[0045] FIG. 2 illustrates an example of a block diagram of an electronic device according to one embodiment.

[0046] 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 device. 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.

[0047] According to one embodiment, the electronic device (100) may include at least one of a processor (110), memory (120), display (130), light-emitting element (140), sensor (150), communication circuit (160), user input unit (170), or speaker (180). The processor (110), memory (120), display (130), light-emitting element (140), sensor (150), communication circuit (160), user input unit (170), and speaker (180) may be electrically and / or operably coupled with each other by an electronic component such as a communication bus.

[0048] 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.

[0049] According to one embodiment, a processor (110) of an 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), 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.

[0050] The CPU 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.

[0051] A GPU 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.

[0052] An 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 computation, the NPU can be implemented in various forms such as TPUs (Tensor Processing Units), IPUs (Intelligence Processing Units), and VPUs (Vision Processing Units). Artificial intelligence processors are not limited to the examples mentioned above, except for cases specified as NPUs.

[0053] 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 state drive (SSD), and embedded multimedia card (eMMC).

[0054] 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).

[0055] One or more processors (110) control input data to be processed according to a predefined operation rule or AI model (artificial-intelligence model) stored in memory (120). The predefined operation rule or AI model is characterized by being created through learning. Being created through learning means that a predefined operation rule or AI 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.

[0056] An AI 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.

[0057] 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.

[0058] According to one embodiment, a display (130) of an electronic device (100) can output visualized information to a user. For example, the display (130) can be controlled by a controller, such as a GPU (graphic processing unit), to output visualized information to a user. The display (130) 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) display, and / or an e-ink display or / and an e-paper display. According to one example, the display (130) may be implemented as a flat display, a curved display, a folding or / and rolling flexible display, etc.

[0059] At least one light-emitting element (140) of an electronic device (100) according to one embodiment may include at least one LED element. For example, the at least one LED element may include a plurality of LED elements of different colors (e.g., R, G, B LED elements).

[0060] A light-emitting element (140) of an electronic device (100) according to one example may include a flash light. For example, the flash light may include a plurality of LED elements of different colors (e.g., R, G, B LED elements). For example, the flash light may emit white light mixed with a plurality of colors, or emit color light that is not white light.

[0061] A light-emitting element (140) according to one example may be implemented as a light-emitting element separate from the flash light. For example, the light-emitting element separate from the flash light may include an ambient-only LED element. For example, the ambient-only light-emitting element may include LED elements of different colors (e.g., R, G, B LED elements). For example, the ambient-only light-emitting element may emit white light mixed with a plurality of colors, or emit color light that is not white light.

[0062] A light-emitting element (140) according to one embodiment may be implemented as a light-emitting element included in an accessory device. For example, the accessory device may be attached to the back of an electronic device. For example, the light-emitting element (140) may be included in an accessory device such as a protective case or a card holder. For example, the light-emitting element (140) may include LED elements of different colors (e.g., R, G, B LED elements). For example, the light-emitting element (140) may emit white light mixed with a plurality of colors, or emit colored light that is not white light.

[0063] According to one example, the brightness of at least one light-emitting element may be implemented to provide a different maximum brightness depending on at least one of the type of electronic device (100), the type of light-emitting element, or the purpose of the light-emitting element. For example, if the electronic device (100) is implemented as a smartphone and the light-emitting element (140) is implemented as a flashlight, the light-emitting element may have a brightness of 20 to 50 lumens.

[0064] A sensor (150) of an electronic device (100) according to one embodiment can sense various information. The sensor (150) can be implemented as various types of sensors.

[0065] According to one example, the sensor (150) may include a camera. The camera may capture surrounding subjects and convert image information into digital data to provide to the processor (110). The electronic device (100) may include at least one camera on the front and / or the rear, opposite direction, where the display (120) is included in the housing. According to one embodiment, the camera may include a lens assembly comprising at least one lens that collects light emitted from an external environment (or subject), an image sensor (e.g., a CCD (charged coupled device) sensor, a CMOS (complementary metal oxide semiconductor) sensor) that converts the light collected through the lens assembly into an electrical signal to generate image data, and an image signal processor that performs various processing on the image data acquired from the image sensor. At least some of the above-described configurations of the camera may be omitted or replaced with other configurations. The camera may provide images of the external environment captured in real time to the processor (110) through an interface (e.g., a mobile industry processor interface). For example, the camera may include at least one of an RGB camera, an ultra-wide angle camera, a depth camera, or an IR camera.

[0066] According to one example, the processor (110) may obtain at least one of ambient brightness information or color information based on a captured image obtained through a camera. For example, the processor (110) may analyze the captured image to collect pixel-unit color data and use an image processing algorithm to calculate the ratio of an average color or a specific color.

[0067] According to one 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 detection sensor, a light sensor, and a motion detection sensor.

[0068] 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.

[0069] 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, and a light intensity sensing layer. For example, the illuminance sensor may measure the amount of ambient light through components such as a photovoltaic cell or a photodiode that react to light. For example, the illuminance sensor may convert ambient light into an electrical signal using a photodiode or a phototransistor, and measure the ambient brightness in units of lux through the converted signal.

[0070] 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.

[0071] 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, 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.

[0072] According to one example, the electronic device (100) may be connected to a server 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.

[0073] The user input unit (170) of the electronic device (100) according to one embodiment may be implemented as a device such as a button or a touch pad, or as a touch screen capable of performing the display function and operation input function described above.

[0074] A speaker (180) of an electronic device (100) according to one embodiment may be configured to output various audio data as well as various notification sounds or voice messages. A processor (110) may control the speaker (180) to output feedback or various notifications in the form of audio according to various embodiments of the present disclosure.

[0075] FIG. 3 is a flowchart illustrating an example of a control method for an electronic device according to one embodiment.

[0076] 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.

[0077] According to one embodiment, operations 310 to 350 can be understood as being performed in the processor (110) of the electronic device (100).

[0078] According to FIG. 3, in operation 310, an electronic device (100) according to one embodiment may obtain first brightness information corresponding to the space where the electronic device (100) is located, based on sensing data obtained through an illuminance sensor (150). For example, the first brightness information may be brightness information of a surround field described in the SFB model of FIG. 1a, and thus may also be referred to as Ls. The surround field may be an area of ​​view of an observer around an object of observation (e.g., the screen of the electronic device (100)).

[0079] According to one example, the sensing data obtained through the illuminance sensor (150) may be data that detects the intensity of light in the surrounding environment. According to one example, the sensing data obtained through the illuminance sensor (150) may be transmitted to the processor (110) in the form of a digital value or an analog signal. According to one example, the ambient brightness information may include ambient illuminance (unit: lux). Lux may be the intensity of light when 1 lumen of light reaches an area of ​​1 m².

[0080] In operation 320, the electronic device (100) according to one embodiment can identify whether the first brightness information is less than a preset value. The preset value may be a value for determining whether a dark environment (or darkroom environment) requiring ambient brightness adjustment according to one embodiment is present. For example, the preset value may be a value determined by experiment. For example, the preset value may be a value that can be selected and / or changed by a user.

[0081] If the first brightness information is less than a preset value (330:Y), in operation 330, the electronic device (100) according to one embodiment can obtain second brightness information corresponding to the screen brightness of the display (130). If the first brightness information is greater than or equal to a preset value (330:N), the electronic device (100) may not perform subsequent operations.

[0082] According to one example, screen brightness information is the intensity of light emitted by the display (130) and may be referred to as luminance. For example, luminance, which is a physical unit, may be measured in candela / m² (cd / m²), which represents the amount of light emitted from a specific area. For example, the brightness of the display (130) may generally be about 300 to 500 cd / m². However, the display (130) may support up to 1000 cd / m² or more for outdoor visibility.

[0083] According to one embodiment, screen brightness information may be calculated based on the brightness of an image output to a display (130) and the brightness setting information of the display (130). For example, this is because the brightness of the image itself, as well as the brightness of the screen setting, affects the screen brightness perceived by the user.

[0084] For example, the brightness of an image can be calculated by analyzing the RGB values ​​of each pixel included in the image (e.g., grayscale values ​​of 0 to 255 for an 8-bit image).

[0085] According to one example, the brightness setting of the display (130) may be a screen brightness setting level (e.g., 0 to 100%). For example, if the screen brightness setting is adjusted high in the user settings, the display (130) emits more light, and the overall screen brightness may be increased.

[0086] According to one example, screen brightness information can be calculated as the product of the setting brightness of the display (130) and the image brightness as shown in Equation 1 below.

[0087]

[0088] B total is the final screen brightness, B d is the display setting brightness (e.g., a value between 0 and 1, 0 is the lowest setting (e.g., 0%), 1 is the maximum setting (e.g., 100%)), B v can be image brightness (e.g., a value between 0 and 1, where 0 is the darkest pixel and 1 is the brightest pixel).

[0089] According to one example, the set brightness of the display (130) may be set in proportion to the maximum brightness of the display (130). For example, if the maximum brightness of the display (130) is 500 cd / m² and the user sets the brightness to 50%, the set brightness may be 0.5 × 500 = 250 cd / m².

[0090] For example, image brightness can vary depending on the brightness value of each pixel. For instance, an 8-bit image has brightness values ​​from 0 to 255, which can be converted and used as a ratio between 0 and 1. For instance, if the brightness value of a specific pixel is 128, converting it to a value between 0 and 1 would result in 128 / 255 = 0.502.

[0091] According to one example, screen brightness information corresponding to a specific pixel is B according to the above mathematical formula 1. total = 250 × 0.502 = 125.5 cd / m². In this way, a screen brightness map can be obtained by calculating the brightness for all pixels included in the image.

[0092] According to one example, the electronic device (100) can obtain screen brightness information based on a screen brightness map. For example, the electronic device (100) can identify screen brightness information based on the average of the screen brightness values ​​for each pixel included in the screen brightness map. However, it is not limited thereto, and the electronic device (100) may also identify screen brightness information by multiplying the average value of the image brightness calculated for each pixel by the set brightness of the display (130).

[0093] In operation 340, an electronic device (100) according to one embodiment may obtain third brightness information for adjusting the ambient light of the electronic device (100) based on first brightness information and second brightness information. For example, the third brightness information may be background brightness information described in the SFB model of FIG. 1a, and thus referred to as Lb. The background is a color and / or pattern immediately behind the object of observation, and the background brightness information may be brightness information immediately behind the object of observation (e.g., electronic device (100)).

[0094] For example, the third brightness information may be a generalized level of brightness information for adjusting ambient brightness.

[0095] For example, the third brightness information may be normalized brightness information of a preset level range. In this case, the electronic device (100) may have brightness information (e.g., lumens) corresponding to a preset level range (e.g., 0 to 10 levels) stored in it.

[0096] For example, the third brightness information may be brightness information in a preset brightness unit (e.g., lumens). For example, the preset brightness unit may be lumens, but is not limited thereto. For example, the preset brightness unit may be at least one of candela (cd), lux (lx), or nit (cd / m²).

[0097] According to one embodiment, the electronic device (100) may obtain third brightness information based on the contrast ratio between first brightness information and second brightness information. Generally, the contrast ratio represents the difference between a bright area and a dark area on a screen and is associated with visual fatigue. Visual fatigue may be stress or burden placed on the eyes.

[0098] According to 'Spiegel's Law,' one of the theoretical formulas explaining the relationship between contrast and visual fatigue, the relationship between contrast and visual fatigue in an image is F = K * (C n It can be equal to ). Here, F represents visual fatigue, K and n are constants, and C represents the contrast value. According to this formula, visual fatigue tends to increase as contrast increases. In other words, the greater the difference between bright and dark areas, the more stress is placed on the eyes. It is known that a low contrast ratio is beneficial for eye health, especially in situations where one must stare at a screen for a long time. For example, when using a laptop or smartphone, it is important to maintain an appropriate contrast ratio by adjusting the brightness of the surrounding environment and the device. According to one example, the contrast ratio that humans find comfortable varies depending on the situation, but is generally known to be about 1:100 or less.

[0099] In the present disclosure, the relationship between contrast ratio and visual fatigue can be applied to the contrast ratio between screen brightness and background brightness.

[0100] According to one embodiment, the electronic device (100) can obtain third brightness information by inputting first brightness information and second brightness information into a brightness calculation model.

[0101] According to one embodiment, the brightness calculation model may be implemented as a regression analysis model or an artificial intelligence model.

[0102] Depending on the example, the brightness calculation model can be implemented as a regression analysis model or an ensemble model of regression analysis models.

[0103] A regression analysis model can be a statistical technique used to predict the values ​​of continuous variables or to analyze the relationships between variables. Regression analysis can predict output values ​​for a given input by expressing the relationship between independent variables (input variables) and dependent variables (output variables) using a mathematical formula. For example, a regression analysis model can be implemented as a multiple regression model. A multiple regression model can be a statistical technique for analyzing the relationship between a single dependent variable and multiple independent variables. A multiple regression model can simultaneously analyze the influence of multiple independent variables on the dependent variable. For instance, surround brightness information and screen brightness information could be multiple independent variables, while the brightness information of the light-emitting element could be the dependent variable.

[0104] An ensemble model of regression analysis is a technique that combines multiple regression models to improve prediction performance. Since individual regression models are trained in different ways, combining them can produce more accurate and stable predictions than a single model. Ensemble models are generally implemented using various methods such as bagging, boosting, and stacking, and the training and prediction methods of the models may differ depending on each method.

[0105] According to one embodiment, the brightness calculation model may be implemented as a deep learning-trained artificial intelligence model. According to one example, the artificial intelligence model may be composed of a plurality of neural network layers. At least one layer has at least one weight value and performs the layer's operation through the operation result of the previous layer and at least one defined operation. Examples of artificial intelligence models include a convolutional neural network (CNN), a recurrent neural network (RNN), a deep neural network (DNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), deep Q-networks, and a Transformer, and the artificial intelligence models in this disclosure are not limited to the aforementioned examples except where specified.

[0106] A learning algorithm is a method of training a specific target device (e.g., electronic device (100)) using a number of learning data so that the specific target device can 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.

[0107] In operation 350, the electronic device (100) according to one embodiment can control the light emission of at least one light-emitting element based on third brightness information.

[0108] For example, if the third brightness information is the 8th level of the normalized level and the brightness level of the light-emitting element corresponding to the 8th level is 5 levels according to the set brightness of the light-emitting element, the brightness of the light-emitting element can be controlled so that the light-emitting element emits at level 5.

[0109] For example, if the third brightness information is 40 lumens and the 20 lumens is the 5th level based on the 5th level based on the 5th level based on the 5th level based on the 5th level based on the 5th level based on the 5th level based on the 20

[0110] According to one embodiment, the electronic device (100) can increase the screen brightness of the display (110) when it is not possible to output a brightness corresponding to the third brightness information at the maximum brightness of at least one light-emitting element. For example, the electronic device (100) can increase the screen brightness by increasing at least one of the set brightness of the display (110) and the brightness of the image.

[0111] According to one embodiment, the electronic device (100) additionally acquires color information as well as brightness information for controlling a light-emitting element, and can control the light-emitting color of the light-emitting element based on the color information. According to one example, the electronic device (100) can acquire a first color information corresponding to surround brightness and a third color information for adjusting the ambient color of the electronic device (100) based on screen brightness. For example, the processor (110) can control the color of the light-emitting element based on the third color information.

[0112] According to one example, the electronic device (100) may acquire first color information based on a captured image obtained through a camera. For example, the processor (110) may analyze the captured image to collect pixel-unit color data and use an image processing algorithm to calculate the ratio of an average color or a specific color.

[0113] According to one example, the electronic device (100) can obtain second color information by analyzing an image displayed on a screen. For example, the processor (110) can analyze the input image to collect pixel-unit color data and calculate the ratio of an average color or a specific color using an image processing algorithm.

[0114] Meanwhile, in the above-described embodiment, it was explained that the third brightness information is calculated through the processing of the electronic device (100), but it is not necessarily limited thereto.

[0115] According to one example, the electronic device (100) can obtain third brightness information based on previously stored information. For example, a lookup table containing third brightness information mapped to each of the first brightness information and second brightness information may be previously stored in memory (120). For example, the lookup table may be stored by the manufacturer of the electronic device (100) or downloaded and stored from an external server.

[0116] According to one example, the electronic device (100) can obtain third brightness information by applying a pre-set rule to first brightness information and second brightness information. For example, the pre-set rule may be stored by the manufacturer of the electronic device (100) or downloaded and stored from an external server.

[0117] According to one example, the electronic device (100) can obtain third brightness information by applying a preset formula to first brightness information and second brightness information. For example, the preset formula may be stored by the manufacturer of the electronic device (100) or downloaded and stored from an external server.

[0118] According to one example, an electronic device (100) can obtain third brightness information from first brightness information and second brightness information using at least one threshold. For example, the electronic device (100) can obtain third brightness information by distinguishing the ranges of first brightness information, second brightness information and / or third brightness information based on at least one threshold. For example, at least one threshold may be stored by the manufacturer of the electronic device (100) or downloaded and stored from an external server.

[0119] As described above, the electronic device (100) can control the brightness of a light-emitting element (140) positioned opposite the display (130) in a dark viewing environment to perform ambient brightness control based on a human visual perception model. When a small amount of light is added in such a dark viewing environment, the user's eyes can see objects with higher contrast. This means that the light sensitivity of the eyes increases, which allows for better distinction between the contrast between dark and bright parts on the screen.

[0120] FIGS. 4, FIGS. 5a to 5d, and FIGS. 6a to 6d are drawings for explaining an example of the operation method of a brightness calculation model according to one embodiment.

[0121] According to one embodiment, when the brightness calculation model is implemented as a multiple regression model and when it is implemented as an artificial intelligence model, the training data set may be the same, so the following description will be based on the case where the brightness calculation model is trained. According to one example, in order to increase the accuracy of the training, the external device may be a device having a display of the same type and size as the display (130) of the electronic device (100), but is not limited thereto.

[0122] According to one embodiment, a brightness calculation model may be trained to output brightness information of a light-emitting element for adjusting ambient brightness based on a dataset including surround brightness information corresponding to the first brightness information described above, screen brightness information corresponding to the second brightness information described above, and recognition information regarding a gamma pattern. According to one example, the training of the brightness calculation model may be performed on at least one of an electronic device (100), an external device, or an external server separate from the external device. According to one example, the dataset for training may be data obtained through an external device.

[0123] For example, the dataset for learning may be data in which user perception information regarding the gamma pattern is acquired while displaying the gamma pattern on a screen and adjusting the screen brightness while adjusting the ambient light to adjust the screen brightness and surround brightness. For example, the gamma pattern may be a grayscale pattern containing various brightness levels (or brightness values). For example, the gamma pattern may be a grayscale bar pattern as illustrated in FIG. 4. For example, the gamma pattern may be a bar pattern listing brightness levels in steps from 0% to 100%. User perception information may be user feedback information, such as how well each bar included in the gamma pattern is distinguished and / or whether the intermediate brightness is too bright or too dark. For example, user perception information may include a perception score that reflects user feedback as a score.

[0124] For example, an external device can classify surround brightness into 10 brightness levels from level 1 to level 10 and acquire user perception information regarding the gamma pattern while changing the surround brightness by 1 level starting from the lowest level. For example, while maintaining screen brightness, an external device can classify the brightness of the light-emitting element into 10 brightness levels from level 1 to level 10 and acquire user perception information regarding the gamma pattern while changing it by 1 level starting from the lowest level. For example, an external device can acquire user perception information regarding the gamma pattern while sequentially changing the screen brightness in the same or similar manner as the surround brightness. For example, assuming that the brightness of the light-emitting element is the same as the background brightness, the external device can acquire user perception information regarding the gamma pattern according to changes in background brightness.

[0125] For example, a dataset corresponding to a condition in which the perception score is above a threshold value (e.g., the highest perception score) under each of the above-described conditions may be used as training data. For example, appropriate background brightness information at each surround brightness level and / or screen brightness level may be used as training data based on user perception scores for gamma patterns at each surround brightness level.

[0126] For example, to acquire training data that can reduce the user's visual fatigue, at least one of the eye movement amount during the perception of the gamma pattern or the time required for gamma pattern perception may be additionally utilized. For example, the eye movement amount may be acquired based on at least one of camera capture, electrical signal measurement, or magnetic signal measurement. For example, when viewing a screen in a dark environment, eye fatigue may occur as the movement of the pupils or focus continues to waver because the judgment of objects becomes blurred due to the inability to accurately perceive the precise gradation of the image. For example, eye fatigue can be calculated through pupil size and reactivity monitoring. For example, eye fatigue can be measured and used as training data until a viewing environment (e.g., surround brightness, screen brightness, and background brightness) in which all gradation differences of the gamma pattern can be perceived is identified.

[0127] According to one embodiment, a performance evaluation may be performed on a brightness calculation model trained based on the above-described training data, based on a validation data set and / or a test data set. During the performance evaluation process, the accuracy and / or stability of the brightness calculation model may be evaluated, and necessary modifications may be reflected. After the brightness calculation model is created, it may be further trained based on a user data set (e.g., a personalized data set) that is continuously collected.

[0128] According to FIG. 5a, a brightness calculation model (510) according to one embodiment can output third brightness information for adjusting the ambient brightness of an electronic device (100) when first brightness information corresponding to surround brightness and second brightness information corresponding to screen brightness are input. For example, the third brightness information may be information corresponding to the brightness of a light-emitting element.

[0129] According to FIG. 5b, a brightness calculation model (520) according to one embodiment can output updated third brightness information when first brightness information corresponding to surround brightness, second brightness information corresponding to screen brightness, and third brightness information of the current light-emitting element are input.

[0130] According to FIG. 5c, a brightness calculation model (530) according to one embodiment can output a third brightness information when inputs a first brightness information corresponding to surround brightness, a second brightness information corresponding to screen brightness, and eye movement information. For example, the eye movement information may include at least one of the amount of pupil movement, the amount of change in pupil size, the blinking frequency, and the pupil size.

[0131] According to FIG. 5d, a brightness calculation model (540) according to one embodiment can output updated third brightness information when first brightness information corresponding to surround brightness, second brightness information corresponding to screen brightness, third brightness information of the current light-emitting element, and eye movement information are input.

[0132] According to FIG. 6a, a brightness calculation model (610) according to one embodiment can output third brightness information and third color information for adjusting the ambient brightness and color of an electronic device (100) when first brightness information and first color information corresponding to surround brightness and second brightness information and second color information corresponding to screen brightness are input. For example, the third brightness information and third color information may be information corresponding to the brightness and color of a light-emitting element.

[0133] According to FIG. 6b, a brightness calculation model (620) according to one embodiment can output updated third brightness information and third color information when first brightness information and first color information corresponding to surround brightness, second brightness information and second color information corresponding to screen brightness, and third brightness information and third color information of the current light-emitting element are input.

[0134] According to FIG. 6c, a brightness calculation model (630) according to one embodiment can output third brightness information and third color information when first brightness information and first color information corresponding to surround brightness, and second brightness information and second color information and eye movement information corresponding to screen brightness are input.

[0135] According to FIG. 6d, a brightness calculation model (640) according to one embodiment can output updated third brightness information and third color information when inputs first brightness information and first color information corresponding to surround brightness, second brightness information and second color information corresponding to screen brightness, third brightness information and third color information of the current light-emitting element and eye movement information.

[0136] FIG. 7 is a drawing for explaining an example of the operation method of a brightness calculation model according to one embodiment.

[0137] According to one embodiment, the brightness calculation model must be trained to output the optimal background brightness (or light-emitting element brightness) for which gamma perception is best in a viewing environment, but the actual usage environment of the user may not maintain constant conditions. For example, even if the optimal background brightness is identified based on the user's viewing environment, the actual screen brightness may change as at least one of the image brightness and the setting brightness changes, so the brightness of the light-emitting element may need to be adjusted.

[0138] According to one embodiment, a brightness calculation model can be trained to output background brightness information based on the contrast ratio between screen brightness information and background brightness information. Generally, the contrast ratio represents the difference between bright and dark areas on a screen and is associated with visual fatigue. Visual fatigue can be stress or burden placed on the eyes. In the present disclosure, the relationship between the contrast ratio and visual fatigue can be applied to the contrast ratio between screen brightness and background brightness.

[0139] According to one embodiment, a brightness calculation model can be trained by applying the contrast ratio between screen brightness information and background brightness information as a constraint (or penalty) term. According to one example, the brightness calculation model can be trained to calculate (or predict) background brightness information such that the contrast ratio between screen brightness information and background information is less than a preset value.

[0140] According to one embodiment, when a brightness calculation model is implemented as a regression analysis model, the constraints of the regression analysis model can be implemented through regularization. Regularization may be a technique that prevents overfitting by controlling the complexity of the model in regression analysis. For example, regularization may be performed by adding a penalty to the L1 or L2 norm of the weight vector.

[0141] Depending on the example, normalization may be applied based on at least one of ridge regression, lasso regression, or elastic net.

[0142]

[0143] y: response variable (surround luminance prediction value), X is independent variable (feature) matrix (including gamma experimental data), β is regression coefficient vector, and ε may be the error term.

[0144] Ridge regression, which performs L2 regularization according to one example, can be applied based on the following mathematical formula 3.

[0145]

[0146] X[G] is the dependent variable obtained through the gamma experiment, J(β is the objective function, norm_L2(X[G]β- y) is the sum of squared residuals, norm_L2(β is the L2 norm of the regression coefficient vector, and δ may be a hyperparameter.

[0147] In norm_L2(β), β can be replaced with "CR ≤ 0.1" to apply a contrast ratio penalty. This is because the contrast ratio that humans find comfortable varies depending on the situation, but is generally known to be about 1:100 or less.

[0148] Referring to FIG. 7 according to one example, assuming that the electronic device (100) is used in a dark environment, and assuming that the screen brightness (Ld) is always brighter than the surround brightness (Ls) and thus the screen brightness is maintained, the background brightness determines the contrast ratio, and since the background brightness is determined by the brightness of the light-emitting element, the brightness of the light-emitting element is L F = L Fmax * min(L d / L s , 100) / 100(L Fmax It can be calculated as the maximum brightness of the light-emitting element.

[0149] For example, if the brightness of a light-emitting element is adjusted to be very bright, it implies that the space is a very dark darkroom environment, so L d : L s min(L when the value exceeds 100:1 d / L sIt can serve to limit the value of , 1.0) / 100 to 1.0. For example, L d (150) :L s (5) = 30:1, so min(L d / L s Since the value of , 1.0) / 100 is 0.3, the brightness level of the light-emitting element can be limited to about 30% of the maximum value (L s / L d (is the reciprocal of CR). By adjusting the brightness level of such a light-emitting element below a certain level, the contrast ratio can be maintained at 100:1 or less.

[0150] FIGS. 8 and 9 are drawings for explaining an example of a method for adjusting the brightness of a light-emitting element according to one embodiment.

[0151] According to one embodiment, as time passes, the user's eyes adapt to a dark environment, so the electronic device (100) can adjust the brightness of the light-emitting element according to a visual adaptation function. For example, since dark adaptation / light adaptation responds in a logarithmic form by the operation of human visual cells, the electronic device (100) can use an algorithm that initially adjusts the brightness of the light-emitting element with a large amount of change in a dark environment and gradually adjusts it over time.

[0152] For example, the human eye's cells respond at different speeds during light adaptation and dark adaptation. Theoretically, it can be assumed that the adaptation function over time has a relative critical luminance value over time as illustrated in Fig. 8. The relative critical luminance response appears similar during dark adaptation or light adaptation, and it can be seen that the responsiveness is high during the initial stages of dark or light adaptation. Based on this, the adjustment speed of the light-emitting element can be adjusted to perform surround brightness adjustment that is as closely matched as possible to the dark adaptation speed of the human eye.

[0153] According to one example, the electronic device (100) can adjust the brightness of the light-emitting element using IIR (infinite impulse response) filtering based on the dark adaptation response speed of human vision based on surround brightness. For example, the electronic device (100) can control the brightness of the light-emitting element (140) based on the brightness of the light-emitting element at a previous point in time and the brightness of the light-emitting element at a current point in time. For example, the electronic device (100) can calculate the adjusted brightness based on the following mathematical formula 4.

[0154]

[0155] λ is the dark adaptation threshold luminance coefficient of human vision, Lt is the brightness of the light-emitting element at time t, Lt-1 is the brightness of the light-emitting element at time t-1, and L may be the brightness of the light-emitting element adjusted according to the adaptation function.

[0156] According to one example, the brightness of the light-emitting element can be gradually adjusted according to the relative threshold luminance value shown in FIG. 8, as shown in FIG. 9. For example, according to FIG. 9, after the use of the electronic device (100) begins in a dark environment (910), the value of λ (vertical axis) is relatively large, so a relatively larger weight is applied to the previous brightness than to the current brightness (920). After that, as time passes and the eye begins to adapt to the dark environment, the value of λ gradually decreases, and a larger weight can be applied to the currently calculated brightness than to the previous brightness (930, 940).

[0157] FIG. 10 is a drawing for explaining an example of a background brightness adjustment method according to one embodiment.

[0158] According to one embodiment, when the electronic device (100) begins to use the electronic device (100) in a dark environment, the light-emitting element (140) can be controlled to emit light at a preset brightness initially, and then gradually increase the brightness of the light-emitting element (140) over time until it finally emits light at a brightness obtained by a brightness calculation model. For example, the preset brightness may be a value stored during the manufacture of the electronic device (100). For example, the preset brightness may be a value that can be set and / or changed by the user. For example, the preset brightness may be a brightness that is lower than a threshold value than the brightness obtained by the brightness calculation model.

[0159] According to one example, according to FIG. 10, after the use of the electronic device (100) in a dark environment begins (1010), the electronic device (100) can control the brightness of the light-emitting element (140) so that at time T+1, the light-emitting element (140) emits light at a preset first brightness, and as time passes, at time T+2, the light-emitting element (140) emits light at a lower brightness with a higher brightness than at time T+1, and at time T+3, it emits light at a final brightness obtained by a brightness calculation model.

[0160] FIG. 11 is a drawing for explaining an example of a background brightness adjustment method according to one embodiment.

[0161] According to one embodiment, when the electronic device (100) begins to use the electronic device (100) in a dark environment, the light-emitting element (140) can be controlled to emit light at a preset brightness initially, and then gradually decrease the brightness of the light-emitting element (140) over time so that it finally emits light at a brightness obtained by a brightness calculation model. For example, the preset brightness may be a value stored during the manufacture of the electronic device (100). For example, the preset brightness may be a value that can be set and / or changed by the user. For example, the preset second brightness may be a brightness lower than a threshold value than the brightness obtained by the brightness calculation model.

[0162] According to one example, according to FIG. 11, after the use of the electronic device (100) in a dark environment begins (1010), the electronic device (100) can control the brightness of the light-emitting element (140) so that at time T+1, the light-emitting element (140) emits light at a preset second brightness, and as time passes, at time T+2, the light-emitting element (140) emits light at a lower brightness than at time T+1, and at time T+3, it emits light at a final brightness obtained by a brightness calculation model.

[0163] FIG. 12 is a drawing for explaining an example of a background brightness adjustment method according to one embodiment.

[0164] According to one embodiment, the electronic device (100) may provide a user interface (UI) to guide the activation of a vision protection function when the illuminance information sensed by the sensor (150) is less than a preset value. For example, the UI may include at least one of a notification UI indicating that the activation of the vision protection function is recommended, or a button UI capable of activating the vision protection function. For example, the notification UI may be provided through at least one of voice, text, or a graphic image. For example, the button UI may be provided as a graphic image, but is not limited thereto.

[0165] According to FIG. 12, if the electronic device (100) identifies that the viewing environment (1210) is a dark environment, it may provide a button UI (1211) that can activate a vision protection function according to one embodiment. If the vision protection function is selected through the button UI (1211), the electronic device (100) may control the light emission of a light-emitting element (140) based on third brightness information obtained using a brightness calculation module according to one embodiment.

[0166] FIGS. 13a and FIGS. 13b are drawings for explaining an example of a light-emitting element according to one embodiment.

[0167] FIG. 13a illustrates a case where the electronic device (100) is implemented as a smartphone (1310), and FIG. 13b illustrates a case where the electronic device (100) is implemented as a tablet device (1620).

[0168] According to FIG. 13a, the light-emitting element (140) may be implemented as a flash light (1311) that is positioned at the top center of the smartphone (1310) and emits light backward. In one example, if the smartphone (1310) identifies that the viewing environment is a dark environment, it may emit the flash light (1311) to adjust the background brightness of the smartphone.

[0169] According to FIG. 13b, the light-emitting element (140) may be implemented as a flash light (1321) that is positioned at the top center of the tablet device (1620) and emits light backward. In one example, if the tablet device (1620) identifies that the viewing environment is a dark environment, it may emit the flash light (1321) to adjust the background brightness of the tablet device.

[0170] FIGS. 14a and FIGS. 14b are drawings for explaining an example of a light-emitting element according to one embodiment.

[0171] FIG. 14a illustrates a case where the electronic device (100) is implemented as a smartphone (1310), and FIG. 14b illustrates a case where the electronic device (100) is implemented as a tablet device (1620).

[0172] According to FIG. 14a, the light-emitting element (140) may be implemented as at least one of a flash light (1311) positioned at the top center of the smartphone (1310) or a bar-shaped accessory (1312) applied to the cover of the smartphone (1310). According to one example, the bar-shaped accessory (1312) applied to the cover may include a plurality of light-emitting elements. For example, the plurality of light-emitting elements may include LEDs of the same color or LEDs of different colors. For example, the bar-shaped accessory (1312) may include an LED flash bar applied to at least one corner of the cover of the smartphone (1310).

[0173] According to one example, as illustrated in FIG. 13a, a bar-shaped accessory (1312) may include LED flash bars placed at the four corners of the cover. According to one example, when the smartphone (1310) identifies that the viewing environment is a dark environment, it may light up the LED flash bars to adjust the background brightness of the smartphone (1310).

[0174] According to FIG. 14b, the light-emitting element (140) may be implemented as at least one of a flash light (1321) positioned at the top center of the tablet device (1620) or a bar-shaped accessory (1322) applied to the cover of the tablet device (1620). According to one example, the bar-shaped accessory (1322) applied to the cover may include a plurality of light-emitting elements. For example, the plurality of light-emitting elements may include LEDs of the same color or LEDs of different colors. For example, the bar-shaped accessory (1322) may include an LED flash bar applied to at least one corner of the cover of the tablet device (1620).

[0175] According to one example, as illustrated in FIG. 13a, a bar-shaped accessory (1322) may include LED flash bars placed at the four corners of the cover. According to one example, when the tablet device (1620) identifies that the viewing environment is a dark environment, it may light up the LED flash bars to adjust the background brightness of the tablet device (1620).

[0176] FIG. 15 is a flowchart illustrating an example of a method for providing a vision protection function according to one embodiment.

[0177] 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.

[0178] According to one embodiment, operations 1501 to 1510 can be understood as being performed in the processor (110) of the electronic device (100).

[0179] According to FIG. 15, in operation 1501, an electronic device (100) according to one embodiment can determine whether the viewing environment is a dark room or a light room. For example, the electronic device (100) can identify that the viewing environment is dark if the illuminance value sensed through an illuminance sensor is less than a preset value. A dark room is a space where there is little or no light, or where light is completely blocked, and a light room may be a bright space where natural light or artificial light is abundantly present.

[0180] When the viewing environment is identified as a dark room, in operation 1502, the electronic device (100) according to one embodiment can obtain surround brightness, background brightness, and screen brightness. For example, the surround brightness information may be brightness based on sensing data obtained through a light sensor. For example, the background brightness may be the current setting brightness of the light-emitting element (140).

[0181] In operation 1503, an electronic device (100) according to one embodiment can obtain brightness information of a light-emitting element (140) based on surround brightness, background brightness, and screen brightness. According to one example, the electronic device (100) can obtain a brightness value of a light-emitting element (140) by inputting surround brightness, background brightness, and screen brightness into a brightness calculation model. For example, the brightness calculation model may include at least one of a regression analysis model or an artificial intelligence model.

[0182] In operation 1504, the electronic device (100) according to one embodiment can adjust the background brightness by emitting light from the light-emitting element (1504) based on the brightness information of the light-emitting element (140).

[0183] In operation 1505, if the viewing environment is identified as a dark room in operation 1501, the electronic device (100) according to one embodiment can operate a timer to adjust the brightness of the light-emitting element according to the visual adaptation function described in FIG. 8, thereby adjusting the background brightness.

[0184] In operation 1506, the electronic device (100) according to one embodiment can identify whether the brightness (Lf) of the light-emitting element (140) identified in operation 1503 is greater than the maximum brightness of the light-emitting element (140).

[0185] In operation 1503, if the brightness (Lf) of the light-emitting element (140) identified is greater than the maximum brightness of the light-emitting element (140) (1506:Y), in operation 1507, the electronic device (100) according to one embodiment can identify the set brightness of the display (130). According to one example, the electronic device (100) can identify the set brightness of the display (130) based on the difference between the brightness (Lf) of the identified light-emitting element (140) and the maximum brightness of the light-emitting element (140). For example, if the electronic device (100) cannot reach the brightness (Lf) identified as the maximum brightness of the light-emitting element (140), it can adjust the set brightness of the display (130) to compensate for the insufficient brightness.

[0186] In operation 1508, the electronic device (100) according to one embodiment can complete darkroom brightness adjustment by further adjusting the screen brightness based on the set brightness of the display (130) identified in operation 1507.

[0187] If the brightness (Lf) of the light-emitting element (140) identified in operation 1503 is less than or equal to the maximum brightness of the light-emitting element (140) (1506:N), darkroom brightness adjustment can be completed (1508).

[0188] If the viewing environment is identified as a dark room in operation 1501, in operation 1509, the electronic device (100) according to one embodiment can perform brightness adjustment. According to one example, the electronic device (100) can increase the visibility of the screen by adjusting the screen brightness to the maximum.

[0189] FIG. 16 is a block diagram of an electronic device in a network environment according to various embodiments. In one example, the electronic device (1601) may be implemented as the electronic device (100) shown in FIG. 2 according to one example.

[0190] Referring to FIG. 16, in a network environment (1600), an electronic device (1601) may communicate with an electronic device (1602) through a first network (1698) (e.g., a short-range wireless communication network) or with at least one of an electronic device (1604) or a server (1608) through a second network (1699) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (1601) may communicate with the electronic device (1604) through a server (1608). According to one embodiment, the electronic device (1601) may include a processor (1620), memory (1630), input module (1650), sound output module (1655), display module (1660), audio module (1670), sensor module (1676), interface (1677), connection terminal (1678), haptic module (1679), camera module (1680), power management module (1688), battery (1689), communication module (1690), subscriber identification module (1696), or antenna module (1697). In some embodiments, at least one of these components (e.g., connection terminal (1678)) may be omitted from the electronic device (1601), or one or more other components may be added. In some embodiments, some of these components (e.g., sensor module (1676), camera module (1680), or antenna module (1697)) may be integrated into a single component (e.g., display module (1660)).

[0191] The processor (1620) can, for example, execute software (e.g., program (1340)) to control at least one other component (e.g., hardware or software component) of the electronic device (1601) connected to the processor (1620) and perform various data processing or operations. According to one embodiment, as at least part of the data processing or operations, the processor (1620) can store commands or data received from other components (e.g., sensor module (1676) or communication module (1690)) in volatile memory (1332), process the commands or data stored in volatile memory (1332), and store the resulting data in non-volatile memory (1334). According to one embodiment, the processor (1620) may include a main processor (1321) (e.g., a central processing unit or an application processor) or an auxiliary processor (1323) 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 (1601) includes a main processor (1321) and an auxiliary processor (1323), the auxiliary processor (1323) may be configured to use less power than the main processor (1321) or to be specialized for a designated function. The auxiliary processor (1323) may be implemented separately from the main processor (1321) or as part thereof.

[0192] The auxiliary processor (1323) may control at least some of the functions or states associated with at least one component of the electronic device (1601) (e.g., display module (1660), sensor module (1676), or communication module (1690)) on behalf of the main processor (1321) while the main processor (1321) is in an inactive (e.g., sleep) state, or together with the main processor (1321) while the main processor (1321) is in an active (e.g., application execution) state. According to one embodiment, the auxiliary processor (1323) (e.g., image signal processor or communication processor) may be implemented as part of another functionally related component (e.g., camera module (1680) or communication module (1690)). According to one embodiment, the auxiliary processor (1323) (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 (1601) itself where the artificial intelligence model is executed, or through a separate server (e.g., server (1608)). 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, the artificial intelligence model may include a software structure, either additionally or substantially.

[0193] The memory (1630) can store various data used by at least one component of the electronic device (1601) (e.g., processor (1620) or sensor module (1676)). The data may include, for example, software (e.g., program (1340)) and input or output data for related commands. The memory (1630) may include volatile memory (1332) or non-volatile memory (1334).

[0194] The program (1340) may be stored as software in memory (1630) and may include, for example, an operating system (1442), middleware (1444), or an application (1446).

[0195] The input module (1650) can receive commands or data to be used for a component of the electronic device (1601) (e.g., processor (1620)) from outside the electronic device (1601) (e.g., user). The input module (1650) 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).

[0196] The sound output module (1655) can output a sound signal to the outside of the electronic device (1601). The sound output module (1655) 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.

[0197] The display module (1660) can visually provide information to an external (e.g., user) of the electronic device (1601). The display module (1660) 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 (1660) 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.

[0198] The audio module (1670) can convert sound into an electrical signal or, conversely, convert an electrical signal into sound. According to one embodiment, the audio module (1670) can acquire sound through the input module (1650) or output sound through the sound output module (1655) or an external electronic device (e.g., electronic device (1602)) (e.g., speaker or headphones) connected directly or wirelessly to the electronic device (1601).

[0199] The sensor module (1676) can detect the operating state of the electronic device (1601) (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 (1676) 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.

[0200] The interface (1677) may support one or more specified protocols that can be used for the electronic device (1601) to be connected directly or wirelessly to an external electronic device (e.g., electronic device (1602)). According to one embodiment, the interface (1677) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0201] The connection terminal (1678) may include a connector through which the electronic device (1601) can be physically connected to an external electronic device (e.g., electronic device (1602)). According to one embodiment, the connection terminal (1678) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0202] The haptic module (1679) can convert an electrical signal into a mechanical stimulus (e.g., vibration or movement) or an electrical stimulus that the user can perceive through tactile or kinesthetic senses. According to one embodiment, the haptic module (1679) may include, for example, a motor, a piezoelectric element, or an electric stimulation device.

[0203] The camera module (1680) can capture still images and video. According to one embodiment, the camera module (1680) may include one or more lenses, image sensors, image signal processors, or flashes.

[0204] The power management module (1688) can manage power supplied to the electronic device (1601). According to one embodiment, the power management module (1688) can be implemented, for example, as at least part of a power management integrated circuit (PMIC).

[0205] The battery (1689) can supply power to at least one component of the electronic device (1601). According to one embodiment, the battery (1689) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0206] The communication module (1690) can support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between an electronic device (1601) and an external electronic device (e.g., electronic device (1602), electronic device (1604), or server (1608)), and the performance of communication through the established communication channel. The communication module (1690) may include one or more communication processors that operate independently of the processor (1620) (e.g., application processor) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (1690) may include a wireless communication module (1692) (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 (1604) through a first network (1698) (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network (1699) (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 (1692) can identify or authenticate an electronic device (1601) within a communication network such as the first network (1698) or the second network (1699) using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module (1696).

[0207] The wireless communication module (1692) 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 (1692) can support a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate, for example. The wireless communication module (1692) 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 (1692) can support various requirements specified in the electronic device (1601), external electronic device (e.g., electronic device (1604)), or network system (e.g., second network (1699)). According to one embodiment, the wireless communication module (1692) 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.

[0208] An antenna module (1697) 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 (1697) 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 (1697) 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 (1698) or a second network (1699), may be selected from the plurality of antennas, for example, by a communication module (1690). A signal or power may be transmitted or received between the communication module (1690) 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 (1697).

[0209] According to various embodiments, the antenna module (1697) 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.

[0210] 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.

[0211] According to one embodiment, commands or data may be transmitted or received between the electronic device (1601) and an external electronic device (1604) through a server (1608) connected to a second network (1699). Each of the external electronic devices (1602, or 1604) may be the same or a different type of device as the electronic device (1601). According to one embodiment, all or part of the operations performed on the electronic device (1601) may be performed on one or more of the external electronic devices (1602, 1604, or 1608). For example, if the electronic device (1601) needs to perform a function or service automatically or in response to a request from a user or another device, the electronic device (1601) 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 (1601). The electronic device (1601) 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 (1601) may provide ultra-low latency services using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device (1604) may include an Internet of Things (IoT) device. The server (1608) may be an intelligent server using machine learning and / or neural networks.According to one embodiment, an external electronic device (1604) or server (1608) may be included within the second network (1699). The electronic device (1601) 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.

[0212] According to one embodiment, the electronic device (100) comprises: a display (130) disposed on the front of the electronic device (100); at least one light-emitting element (140) disposed on the rear of the electronic device (100); a sensor (150); and a memory (120) for storing instructions. The invention includes at least one processor (150) comprising a processing circuitry, wherein the instructions, when executed individually or collectively by the at least one processor, enable the electronic device to acquire first brightness information corresponding to the space where the electronic device is located based on sensing data acquired through the sensor, and if the first brightness information is less than a preset value, acquire second brightness information corresponding to the screen brightness of the display, acquire third brightness information for adjusting the ambient brightness of the electronic device based on the contrast ratio between the first brightness information and the second brightness information, and control the light emission of at least one light-emitting element placed on the rear of the electronic device based on the third brightness information.

[0213] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may acquire first color information corresponding to the space where the electronic device is located based on sensing data acquired through the sensor, acquire second color information corresponding to the screen brightness of the display, acquire third color information for adjusting the ambient color of the electronic device based on the color difference between the first color information and the second color information, and control the light emission of the at least one light-emitting element based on the third color information.

[0214] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may acquire user eye movement information based on a captured image acquired through the sensor, and acquire third brightness information for adjusting the ambient brightness of the electronic device based on the eye movement information, the first brightness information, and the second brightness information.

[0215] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may increase the screen brightness of the display based on the difference between the maximum brightness of the at least one light-emitting element and the third brightness information when the electronic device cannot output a brightness corresponding to the third brightness information based on the maximum brightness of the at least one light-emitting element.

[0216] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may increase the screen brightness of the display by adjusting at least one of the brightness of the image displayed on the display or the set brightness of the display.

[0217] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may adjust the third brightness information based on a dark adaptation relative threshold brightness based on a human visual system, and control the light emission of the at least one light-emitting element based on the adjusted third brightness information.

[0218] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may acquire the third brightness information such that the contrast ratio between the first brightness information and the second brightness information is less than a preset value.

[0219] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device can control the brightness of the at least one light-emitting element based on the first brightness information when the first brightness information is less than the preset value, and control the brightness of the at least one light-emitting element to gradually increase to reach the third brightness information.

[0220] 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 (user interface) button on the display to guide the activation of a vision protection function if the first brightness information is less than the preset value, and if the vision protection function is selected through the UI button, input the first brightness information and the second brightness information into the brightness calculation model to obtain the third brightness information.

[0221] According to one embodiment, when the instructions are executed individually or collectively by the at least one processor, the electronic device may acquire the third brightness information using a multiple regression model that predicts the third brightness information through multiple regression analysis based on the first brightness information and the second brightness information, or an artificial intelligence model trained through deep learning that outputs the third brightness information based on the first brightness information and the second brightness information. A control method for an electronic device according to one embodiment includes: acquiring first brightness information corresponding to the space where the electronic device is located based on sensing data acquired through a sensor; acquiring second brightness information corresponding to the screen brightness of a display placed on the front of the electronic device if the first brightness information is less than a preset value; acquiring third brightness information for adjusting the ambient brightness of the electronic device based on the contrast ratio between the first brightness information and the second brightness information; and controlling the light emission of at least one light-emitting element placed on the rear of the electronic device based on the third brightness information.

[0222] According to one embodiment, the control method may further include: an operation of acquiring first color information corresponding to the space where the electronic device is located based on sensing data acquired through the sensor; an operation of acquiring second color information corresponding to the screen brightness of the display; an operation of acquiring third color information for adjusting the ambient color of the electronic device based on the color difference between the first color information and the second color information; and an operation of controlling the light emission of the at least one light-emitting element based on the third color information.

[0223] According to one embodiment, the control method further includes an operation of acquiring user eye movement information based on a captured image acquired through the sensor; and the operation of acquiring third brightness information may include an operation of acquiring third brightness information for adjusting the ambient brightness of the electronic device based on the eye movement information, the first brightness information, and the second brightness information.

[0224] According to one embodiment, the control method may further include an operation of increasing the screen brightness of the display based on the difference between the maximum brightness of the at least one light-emitting element and the third brightness information when it is not possible to output a brightness corresponding to the third brightness information based on the maximum brightness of the at least one light-emitting element.

[0225] According to one embodiment, the operation of increasing the screen brightness of the display may include the operation of increasing the screen brightness of the display by adjusting at least one of the brightness of an image displayed on the display or the set brightness of the display.

[0226] According to one embodiment, the control method may further include: an operation of adjusting the third brightness information based on a dark adaptation relative threshold brightness based on a human visual system; and an operation of controlling the emission of the at least one light-emitting element based on the adjusted third brightness information.

[0227] According to one embodiment, the operation of acquiring the third brightness information may include the operation of acquiring the third brightness information such that the contrast ratio between the first brightness information and the second brightness information becomes less than a preset value.

[0228] According to one embodiment, the control method may further include: an operation of controlling the brightness of the at least one light-emitting element based on the first brightness information when the first brightness information is less than the preset value; and an operation of controlling the brightness of the at least one light-emitting element to gradually increase to reach the third brightness information.

[0229] According to one embodiment, the control method may include: an operation of displaying a UI (user interface) button on the display to guide the activation of a vision protection function when the first brightness information is less than the preset value; and an operation of acquiring the third brightness information, wherein when the vision protection function is selected through the UI button, the third brightness information is acquired based on the first brightness information and the second brightness information.

[0230] A non-transient computer-readable medium storing computer 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: an operation of acquiring first brightness information corresponding to a space where the electronic device is located based on sensing data acquired through a sensor; an operation of acquiring second brightness information corresponding to a screen brightness of a display disposed on the front of the electronic device if the first brightness information is less than a preset value; an operation of acquiring third brightness information for adjusting the ambient brightness of the electronic device based on a contrast ratio between the first brightness information and the second brightness information; and an operation of controlling the light emission of at least one light-emitting element disposed on the rear of the electronic device based on the third brightness information.

[0231] According to the various embodiments described above, when using a personalized small device such as a smartphone in a dark environment, the user's eye strain can be reduced by adjusting the ambient brightness of the viewing environment using a flashlight provided on the smartphone or an LED provided on the cover.

[0232] 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.

[0233] 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.

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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 online in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)) or 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.

[0238] 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.

[0239] Although preferred embodiments of the present disclosure have been illustrated and described above, the present disclosure is not limited to the specific embodiments described above. It is understood that various modifications can be made by those skilled in the art without departing from the essence 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), A display (130) positioned on the front of the electronic device (100); At least one light-emitting element (140) disposed on the rear of the electronic device (100); Sensor (150); Memory (120) for storing instructions; and It includes at least one processor (150) including a processing circuitry; and 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, first brightness information corresponding to the space where the electronic device is located is obtained, and If the first brightness information is less than a preset value, second brightness information corresponding to the screen brightness of the display is obtained, and A third brightness information for adjusting the ambient brightness of the electronic device based on the contrast ratio between the first brightness information and the second brightness information is obtained, and An electronic device that controls the light emission of at least one light-emitting element disposed on the rear of the electronic device based on the third brightness information.

2. In Paragraph 1, 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 sensor, first color information corresponding to the space where the electronic device is located is obtained, and Acquiring second color information corresponding to the screen brightness of the above display, and A third color information for adjusting the ambient color of the electronic device based on the color difference between the first color information and the second color information is obtained, and An electronic device for controlling the light emission of at least one light-emitting element based on the above third color information.

3. In Paragraph 1 or 2, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, Information on the user's eye movement is obtained based on the captured image acquired through the above sensor, and An electronic device that obtains the third brightness information for adjusting the ambient brightness of the electronic device based on the above eye movement information, the above first brightness information, and the above second brightness information.

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 increases the screen brightness of the display based on the difference between the maximum brightness of the at least one light-emitting element and the third brightness information when it is not possible to output a brightness corresponding to the third brightness information based on the maximum brightness of the at least one light-emitting element.

5. In Paragraph 4, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, An electronic device that increases the screen brightness of the display by adjusting at least one of the brightness of the image displayed on the display or the set brightness of the display.

6. In Paragraph 1 or 2, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, Adjusting the third brightness information based on the dark adaptation relative threshold luminance based on the human visual system, and An electronic device for controlling the emission of at least one light-emitting element based on the above-mentioned adjusted third brightness information.

7. 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 obtains the third brightness information such that the contrast ratio between the first brightness information and the second brightness information is less than a preset value.

8. In Paragraph 1 or 2, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, If the first brightness information is less than the preset value, the brightness of the at least one light-emitting element is controlled based on the first brightness information, and An electronic device that controls the brightness of at least one light-emitting element to gradually increase to reach the third brightness information.

9. In Paragraph 1 or 2, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, If the above first brightness information is less than the above preset value, a UI (user interface) button to guide the activation of the eye protection function is displayed on the display, and An electronic device that, when the eye protection function is selected through the UI button, obtains the third brightness information based on the first brightness information and the second brightness information.

10. 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 obtains the third brightness information using a multiple regression model that predicts the third brightness information through multiple regression analysis based on the first brightness information and the second brightness information, or a deep learning-trained artificial intelligence model that outputs the third brightness information based on the first brightness information and the second brightness information.

11. In a method for controlling an electronic device, An operation of acquiring first brightness information corresponding to the space where the electronic device is located, based on sensing data acquired through a sensor; If the first brightness information is less than a preset value, the operation of acquiring second brightness information corresponding to the screen brightness of a display positioned on the front of the electronic device; The operation of obtaining third brightness information for adjusting the ambient brightness of the electronic device based on the contrast ratio between the first brightness information and the second brightness information; and A control method comprising: controlling the emission of at least one light-emitting element disposed on the rear of the electronic device based on the third brightness information.

12. In Paragraph 11, The above control method is, An operation of acquiring first color information corresponding to the space where the electronic device is located based on sensing data acquired through the sensor; and An operation to acquire second color information corresponding to the screen brightness of the above display; The operation of obtaining third color information for adjusting the ambient color of the electronic device based on the first color information and the color difference between the first color information; and A control method further comprising: an operation to control the emission of at least one light-emitting element based on the above third color information.

13. In Paragraph 11 or 12, The above control method is, The method further includes the operation of acquiring user eye movement information based on a captured image acquired through the sensor; The operation of acquiring the above third brightness information is, A control method comprising: an operation of obtaining third brightness information for adjusting the ambient brightness of the electronic device based on the eye movement information, the first brightness information, and the second brightness information.

14. In Paragraph 11 or 12, The above control method is, A control method further comprising: an operation to increase the screen brightness of the display based on the difference between the maximum brightness of the at least one light-emitting element and the third brightness information when the brightness corresponding to the third brightness information cannot be output based on the maximum brightness of the at least one light-emitting element.

15. A non-transient computer-readable medium storing computer instructions that cause said electronic device to perform an operation when executed by a processor of said electronic device, The above operation is, An operation of acquiring first brightness information corresponding to the space where the electronic device is located, based on sensing data acquired through a sensor; If the first brightness information is less than a preset value, the operation of acquiring second brightness information corresponding to the screen brightness of a display positioned on the front of the electronic device; The operation of obtaining third brightness information for adjusting the ambient brightness of the electronic device based on the contrast ratio between the first brightness information and the second brightness information; and A non-transient computer-readable medium comprising: an operation to control the emission of at least one light-emitting element disposed on the rear of the electronic device based on the third brightness information above.

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