Electronic device comprising vision sensor, and operation method thereof

Abstract

An electronic device according to one embodiment of the present invention may comprise: a vision sensor for outputting an event signal by detecting a change in the intensity of light incident from a light source; a noise distribution estimation unit for estimating a distribution of noise with respect to the detected event signal; and a filter unit for removing noise on the basis of the estimated distribution of the noise.

Description

Electronic device including a vision sensor and method of operation thereof

[0001] The present invention relates to an electronic device including a vision sensor and a method of operating the same. Specifically, the invention relates to an electronic device including a vision sensor that performs filtering for noise reduction by utilizing a vision sensor, an image sensor, an illuminance sensor, etc., and a method of operating the same.

[0002] When an event (e.g., a change in light intensity) occurs, the vision sensor generates information about the event, namely an event signal, and transmits the event signal to the processor.

[0003] Meanwhile, while an event may be triggered by a valid signal indicating a change in light intensity, it may also be triggered by noise. For example, a vision sensor determines whether an event occurs based on changes in light intensity (brightness); although an event should not occur when there is no change in light intensity, an event may still occur due to electronic noise in the circuit.

[0004] It is necessary to determine whether an event was caused by noise or a valid signal, and to conduct research not only on vision sensors for accurately sensing events caused by valid signals but also on configurations capable of accurately determining events caused by valid signals.

[0005] The present invention aims to provide an electronic device comprising a vision sensor to which a filtering method capable of reducing noise generated in an environment without changes in light intensity is applied, and a method of operating the same.

[0006] The technical problems to be solved by this embodiment are not limited to those described above, and other technical problems can be inferred from the following embodiments.

[0007] An electronic device according to one embodiment of the present invention may include: a vision sensor that detects a change in the intensity of light incident from a light source and outputs an event signal; a noise distribution estimation unit that estimates the distribution of noise for the detected event signal; and a filter unit that removes noise based on the estimated noise distribution.

[0008] In one embodiment, the noise distribution estimation unit can individually estimate the noise distribution determined as a positive event and the noise distribution determined as a negative event output from the vision sensor.

[0009] In one embodiment, the filter unit can remove the noise by utilizing a non-linear filtering method.

[0010] In one embodiment, the filter unit may include a first filter unit that performs filtering on a noise distribution determined to be a positive event; and a second filter unit that performs filtering on a noise distribution determined to be a negative event.

[0011] In one embodiment, the device further includes an illuminance sensor for measuring illuminance, and the noise distribution estimation unit can estimate the distribution of noise for the detected event signal by considering the measured illuminance.

[0012] In one embodiment, an image sensor for measuring illuminance is further included, and the noise distribution estimation unit can estimate the distribution of noise for the detected event signal by considering the measured illuminance.

[0013] In one embodiment, the image sensor divides the included pixels into a plurality of regions and measures the internal average illuminance value for each region, and the noise distribution estimation unit can estimate the distribution of noise for the detected event signal by considering the measured average illuminance value.

[0014] In one embodiment, the noise distribution estimation unit can estimate the noise distribution based on a previously observed noise pattern.

[0015] In one embodiment, the noise distribution estimation unit can estimate the noise distribution by utilizing a previously established artificial intelligence model.

[0016] A method of operation of an electronic device according to an embodiment of the present invention may include: a step of detecting a change in the intensity of light incident from a light source and outputting an event signal; a step of estimating the distribution of noise for the detected event signal; and a step of removing noise based on the estimated noise distribution.

[0017] According to the electronic device including a vision sensor and the method of operation thereof according to the present invention, generated noise can be efficiently removed, and thereby the accuracy of frame recognition of the electronic device can be improved.

[0018] FIG. 1 is a block diagram illustrating an image processing system according to an embodiment of the present invention.

[0019] FIG. 2a is a block diagram showing the configuration of an electronic device according to one embodiment of the present invention.

[0020] FIG. 2b is a block diagram showing the configuration of an electronic device according to one embodiment of the present invention.

[0021] FIG. 3 is a block diagram showing the configuration of a vision sensor according to one embodiment of the present invention.

[0022] FIG. 4 is a conceptual diagram showing the schematic configuration of a pixel array according to one embodiment.

[0023] FIG. 5 is a flowchart illustrating the operation of an electronic device according to one embodiment of the present invention.

[0024] FIG. 6 is a block diagram showing the configuration of an electronic device according to one embodiment of the present invention.

[0025] FIG. 7 is a block diagram showing the configuration of an electronic device according to one embodiment of the present invention.

[0026] FIG. 8 is a block diagram showing the configuration of an electronic device according to one embodiment of the present invention.

[0027] Hereinafter, various embodiments of the present invention are described with reference to the accompanying drawings. The present invention is not limited to specific embodiments and should be understood to include various modifications, equivalents, and / or alternatives of the embodiments of the present invention. In connection with the description of the drawings, similar reference numerals may be used for similar components.

[0028] In this document, expressions such as "have," "can have," "include," or "can include" refer to the existence of the relevant feature (e.g., numerical values, functions, actions, or components, etc.) and do not exclude the existence of additional features.

[0029] In this document, expressions such as “A or B,” “at least one of A or / and B,” or “one or more of A or / and B” may include all possible combinations of items listed together. For example, “A or B,” “at least one of A and B,” or “at least one of A or B” may refer to cases including (1) at least one A, (2) at least one B, or (3) both at least one A and at least one B.

[0030] Expressions such as "first," "second," "first," or "second" used in this document may modify various components regardless of order and / or importance, and are used merely to distinguish one component from another without limiting such components. For example, without departing from the scope of rights set forth in this document, the first component may be named the second component, and similarly, the second component may be renamed the first component.

[0031] As used in this document, the expression "configured to" may be replaced, depending on the context, with, for example, "suitable for," "having the capacity to," "designed to," "adapted to," "made to," or "capable of." The term "configured to" does not necessarily mean "specifically designed to."

[0032] In this document, terms transmitted or received between the first electronic device(s) and the second electronic device(s), such as “command,” “instruction,” “control information,” “message,” “information,” “data,” “packet,” “data packet,” “intent,” and / or “signal,” may include or refer to humanly perceptible ideas or specific electrical representations (e.g., digital codes / analog physical quantities) without being limited by their expression. It will be obvious to a person skilled in the art to which the invention disclosed in this document pertains that the exemplary expressions listed above may be interpreted in various ways depending on the context in which they are used. In this document, “a is greater than B” means not only that “a is greater than B” but also includes the meaning that “a is equal to or greater than B”.

[0033] The terms used in this document are used merely to describe specific embodiments and are not intended to limit the scope of other embodiments. Singular expressions may include plural expressions unless the context clearly indicates otherwise. Terms used herein, including technical or scientific terms, may have the same meaning as generally understood by those skilled in the art described in this document. Terms used in this document that are defined in general dictionaries may be interpreted as having the same or similar meaning as they have in the context of the relevant technology, and are not to be interpreted in an ideal or overly formal sense unless explicitly defined in this document. In some cases, even terms defined in this document may not be interpreted to exclude the embodiments of this document.

[0034] FIG. 1 is a block diagram for explaining an image processing system (1) according to an embodiment of the present invention.

[0035] The image processing system (1) may include a light source (10) and an electronic device (20).

[0036] According to an embodiment of the present invention, the light source (10) may include at least one light-emitting element. For example, the light source (10) may include an LED, a laser diode, and a VCSEL (Vertical Cavity Surface Emitting Laser).

[0037] According to an embodiment of the present invention, the electronic device (20) may include a sensor (21) and a processor (25).

[0038] According to an embodiment of the present invention, the sensor (21) may include at least one of an image sensor, an illuminance sensor, and a vision sensor.

[0039] The processor (25) can receive a signal generated from the sensor (21) and can generate an image corresponding to the subject based on the received signal.

[0040] According to an embodiment of the present invention, the processor (25) can convert raw data captured by the sensor (21) into a high-quality image. The processor (25) can improve image quality by removing noise occurring in a low-light environment. The processor (25) can adjust color imbalances caused by lighting conditions or sensor limitations. The processor (25) can perform noise removal, scene recognition, real-time object recognition, etc. by utilizing a pre-established artificial intelligence model.

[0041] FIGS. 2a and FIGS. 2b are block diagrams showing the configuration of an electronic device (20) according to one embodiment of the present invention.

[0042] Referring to FIG. 2a, an electronic device (20) according to one embodiment of the present invention may include a vision sensor (210), a noise distribution estimation unit (230), and a filter unit (250). The noise distribution estimation unit (230) and the filter unit (250) may be components included in a processor (25).

[0043] The vision sensor (210) can collect light incident from the light source (10). The vision sensor (210) can detect a change in the intensity of the incident light and output an event signal. For example, if an event occurs in which the intensity of the light increases, the vision sensor (210) can output a corresponding positive event. Conversely, if an event occurs in which the intensity of the light decreases, the vision sensor (210) can output a negative event.

[0044] According to an embodiment of the present invention, the vision sensor (210) may be a dynamic vision sensor. For example, the vision sensor (210) may access a pixel where a change in light intensity is detected and output an event signal. For example, the change in light intensity may be caused by the movement of a subject being captured by the vision sensor (210) or by the movement of the vision sensor (210) itself. The event signal may be generated mainly from the outline of the subject.

[0045] Since the vision sensor (210) outputs only the value corresponding to the light whose intensity changes, the amount of processing data can be reduced compared to other sensors (e.g., CMOS image sensor, etc.).

[0046] The vision sensor (210) can detect changes in the intensity of the collected light and provide an event signal to the noise distribution estimation unit (230).

[0047] The noise distribution estimation unit (230) can estimate the distribution of incorrectly recognized events (hereinafter, noise) among the event signals detected by the vision sensor (210).

[0048] According to one embodiment of the present invention, the noise distribution estimation unit (230) can estimate the distribution of noise in a situation where no significant event occurs in a low-light environment. For example, the noise distribution estimation unit (230) can estimate the noise distribution based on previously observed noise patterns. The noise distribution estimation unit (230) can estimate the noise distribution based on positive-event information and negative-event information for the entire area or for each area of ​​the cell array of the vision sensor (210).

[0049] According to one embodiment of the present invention, the noise distribution estimation unit (230) can estimate the noise distribution by utilizing a pre-established artificial intelligence model capable of estimating the noise distribution occurring in a low-light environment.

[0050] According to an embodiment of the present invention, the noise distribution estimation unit (230) can individually estimate the noise distribution determined as a positive event and the noise distribution determined as a negative event in a low-light environment.

[0051] The noise distribution estimation unit (230) can provide information about the estimated noise distribution to the filter unit (250).

[0052] The filter unit (250) can remove noise based on the provided noise distribution information.

[0053] According to an embodiment of the present invention, the filter unit (250) may be a non-linear filter. For example, the filter unit (250) may remove noise by analyzing the spatiotemporal characteristics of events generated in pixels surrounding the target pixel and selecting an intermediate value. As another example, the filter unit (250) may remove noise by analyzing the spatiotemporal characteristics of events generated in pixels surrounding the target pixel and selecting a minimum value. As yet another example, the filter unit (250) may remove noise by dynamically adjusting the size of the filtering window according to the event density. As yet another example, the filter unit (250) may learn the spatiotemporal characteristics of events using an artificial neural network and identify and remove noise.

[0054] According to an embodiment of the present invention, the filter unit (250) can remove noise using an order-statistics filter method that sorts input data and selects and outputs a specific rank value.

[0055] According to an embodiment of the present invention, the filter unit (250) can remove noise using a spatial filtering method based on the event distribution within a two-dimensional filter kernel. For example, the filter unit (250) can remove noise by utilizing at least one of density-based filtering, edge-preserving filtering, adaptive window filtering, maximum posterior probability (MAP)-based filtering, sparse coding-based filtering, etc. based on the event distribution within a two-dimensional filter kernel.

[0056] According to an embodiment of the present invention, the filter unit (250) can remove noise using a temporal filtering method based on the event distribution within a three-dimensional filter kernel. For example, the filter unit (250) can remove noise by utilizing at least one of the following: refractory filtering based on the event distribution within a three-dimensional filter kernel, correlation filtering, adaptive time window filtering, time surface filtering, spiking neural network-based filtering, etc.

[0057] According to an embodiment of the present invention, the filter unit (250) can individually perform filtering for a noise distribution determined to be a positive event and filtering for a noise distribution determined to be a negative event. The filter unit (250) may perform filtering for a noise distribution determined to be a positive event and filtering for a noise distribution determined to be a negative event in the same way or in different ways.

[0058] Referring to FIG. 2b, the filter unit (250) may include a first filter unit (251) that performs filtering on a noise distribution determined to be a positive event and a second filter unit (253) that performs filtering on a noise distribution determined to be a negative event.

[0059] The filter unit (250) can output data with noise removed.

[0060] FIG. 3 is a block diagram showing the configuration of a vision sensor (210) according to one embodiment of the present invention.

[0061] According to one embodiment of the present invention, the vision sensor (210) may include an event detection circuit (310) and an output buffer (330). For reference, the components (310, 330) of the vision sensor (210) shown in FIG. 3 are merely exemplary components for explaining the operation method of the electronic device (20) according to one embodiment of the present invention. That is, it is evident that the electronic device (20) according to one embodiment of the present invention may additionally include other components other than those shown.

[0062] According to an embodiment of the present invention, the event detection circuit (310) may include a pixel array (311), a column AER (Address Event Representation) circuit (313), and a row AER circuit (315).

[0063] The pixel array (311) may include at least one pixel that detects an event based on a change in incident light luminance. The pixel array (311) may include at least one pixel in which at least one row and at least one column are arranged in a matrix form.

[0064] According to an embodiment of the present invention, a pixel may be provided with a photoelectric conversion element that generates a charge according to the luminance of incident light. When the pixel detects a change in the luminance of incident light based on the photocurrent flowing from the photoelectric conversion element, it may provide a request for reading from the pixel to a column AER (Address Event Representation) circuit (313) and a row AER circuit (315). The pixel may output an event signal indicating that an event has been detected by the column AER circuit (313) and the row AER circuit (315).

[0065] Specifically, a signal indicating that an event has occurred in which the light intensity increases or decreases in a pixel included in the pixel array (311) may be provided from the pixel to the column AER circuit (313). For example, the pixel array (311) may detect a change in light from each pixel and output an output voltage, and determine whether an event has occurred by comparing the output voltage with a preset threshold value. When an event occurs, the pixel array (311) may provide an event signal to the column AER circuit (313).

[0066] The column AER circuit (313) can provide an acknowledgment signal (ACK) to the pixel in response to a signal received from the pixel that detected the event. The pixel that received the acknowledgment signal (ACK) can provide polarity information of the event that occurred to the row AER circuit (315).

[0067] The column AER circuit (315) can generate the column address of the pixel that detected the event based on the signal received from the pixel that detected the event.

[0068] The low AER circuit (315) can receive polarity information from a pixel that detected an event. Based on the polarity information, the low AER circuit (315) can generate a timestamp containing information about the time at which the event occurred.

[0069] The low AER circuit (315) can provide a reset signal to the pixel where the event occurred in response to polarity information. The reset signal can reset the pixel where the event occurred. Furthermore, the low AER circuit (315) can generate a low address of the pixel where the event occurred.

[0070] According to an embodiment of the present invention, a pixel can detect the presence or absence of an event by comparing a photocurrent corresponding to the luminance of incident light with a predetermined threshold value. For example, if the amount of change in luminance is greater than a preset threshold value, the pixel can detect that change as a positive event. As another example, if the amount of change in luminance is smaller than a preset threshold value, the pixel can detect that change as a negative event.

[0071] The event detection circuit (310) can provide information about the generated event, column address, row address, polarity information and timestamp to the output buffer (330).

[0072] The output buffer (330) can generate a packet based on a column address, a row address, polarity information, and a timestamp. The output buffer (330) can add a header indicating the start of the packet at the front of the packet and a tail indicating the end of the packet at the back.

[0073] FIG. 4 is a conceptual diagram showing the schematic configuration of a pixel array (311) according to one embodiment.

[0074] Multiple unit pixels (PX) arranged in an MxN array form can be connected to multiple row lines (ROW 0 to ROW M-1) and multiple column lines (COL 0 to COL N-1).

[0075] A plurality of unit pixels (PX) included in the pixel array (210) can be scanned in row (ROW) units or column (COL) units. In one embodiment, while sequentially scanning a plurality of columns (COL), pixel signals can be detected from the unit pixels (PX), and event signals can be generated using the pixel signals.

[0076] FIG. 5 is a flowchart illustrating the operation of an electronic device (20) according to an embodiment of the present invention. In particular, FIG. 5 illustrates the operation of an electronic device (20) that includes only the configuration shown in FIG. 2.

[0077] In step S501, the vision sensor (210) can detect an event signal. The vision sensor (210) can detect a change in the intensity of the collected light and provide the event signal to the noise distribution estimation unit (230).

[0078] In step S503, the noise distribution estimation unit (230) can estimate the distribution of incorrectly recognized events (hereinafter, noise) among the event signals detected by the vision sensor (210). The noise distribution estimation unit (230) can provide information about the estimated noise distribution to the filter unit (250).

[0079] In step S505, the filter unit (250) can remove noise based on the provided noise distribution information.

[0080] In step S507, the filter unit (250) can output data with noise removed.

[0081] FIG. 6 is a block diagram showing the configuration of an electronic device (60) according to one embodiment of the present invention. FIG. 6 is a block diagram showing an electronic device (60) including a vision sensor (610) and an image sensor (620).

[0082] An electronic device (60) according to one embodiment of the present invention may include a vision sensor (610), an image sensor (620), a noise distribution estimation unit (630), and a filter unit (650). The vision sensor (610) may correspond to the vision sensor (210) shown in FIG. 2.

[0083] The image sensor (620) can convert the optical signal of a subject into image data. The image sensor (620) can be mounted on an electronic device that has the function of detecting images or light.

[0084] The image sensor (620) may include a pixel array, a readout circuit, etc. The pixel array included in the image sensor (620) may be implemented as a photoelectric conversion device such as a CCD (Charge Coupled Devices) or CMOS (Complementary Metal Oxide Semiconductor), and may also be implemented as various other types of photoelectric conversion devices.

[0085] The image sensor (620) can measure illuminance for a pixel. For example, the image sensor (620) can measure illuminance for the entire pixel area or a part of the pixel area. The image sensor (620) can measure illuminance for the entire pixel area or a part of the pixel area by capturing with the same angle of view as the vision sensor (610).

[0086] The image sensor (620) can measure the average illuminance value for the entire pixel area. Additionally, the image sensor (620) can divide the pixel area into multiple parts and measure the average illuminance value differently for each area.

[0087] The image sensor (620) can provide the measured illuminance value to the noise distribution estimation unit (630).

[0088] The noise distribution estimation unit (630) can estimate the distribution of incorrectly recognized events (hereinafter, noise) among the event signals detected by the vision sensor (610).

[0089] According to one embodiment of the present invention, the noise distribution estimation unit (630) can estimate the distribution of noise based on an event signal received from the vision sensor (610) and an illuminance value received from the image sensor (620). For example, when the vision sensor (610) and the image sensor (620) photograph a subject with the same angle of view, the noise distribution can be estimated based on the light intensity information of the entire pixel area or by area, utilizing the illuminance value information measured by the image sensor (620) and the event signal generated by the vision sensor (610).

[0090] According to an embodiment of the present invention, the noise distribution estimation unit (630) can individually estimate the noise distribution determined as a positive event and the noise distribution determined as a negative event in a low-light environment.

[0091] The noise distribution estimation unit (630) can provide information about the estimated noise distribution to the filter unit (650).

[0092] The filter section (650) can correspond to the filter section (250) shown in FIG. 2.

[0093] FIG. 7 is a block diagram showing the configuration of an electronic device (70) according to one embodiment of the present invention. FIG. 7 is a block diagram showing an electronic device (70) including a vision sensor (710) and an illuminance sensor (720).

[0094] An electronic device (70) according to one embodiment of the present invention may include a vision sensor (710), an illuminance sensor (720), a noise distribution estimation unit (730), and a filter unit (750). The vision sensor (710) may correspond to the vision sensor (210) shown in FIG. 2.

[0095] The illuminance sensor (720) can measure the intensity of light and illuminance of the surrounding environment. For example, the illuminance sensor (620) can measure the illuminance of the entire pixel area or a part of the pixel area.

[0096] The illuminance sensor (720) can provide the measured illuminance value to the noise distribution estimation unit (730).

[0097] The noise distribution estimation unit (730) can estimate the distribution of incorrectly recognized events (hereinafter, noise) among the event signals detected by the vision sensor (710).

[0098] According to one embodiment of the present invention, the noise distribution estimation unit (730) can estimate the distribution of noise based on an event signal received from the vision sensor (710) and an illuminance value received from the illuminance sensor (720). For example, the noise distribution can be estimated based on the light intensity information for the entire pixel area or by area, utilizing the illuminance value information measured by the illuminance sensor (720) and the event signal generated by the vision sensor (710).

[0099] According to an embodiment of the present invention, the noise distribution estimation unit (730) can individually estimate the noise distribution determined as a positive event and the noise distribution determined as a negative event in a low-light environment.

[0100] The noise distribution estimation unit (730) can provide information about the estimated noise distribution to the filter unit (750).

[0101] The filter section (750) can correspond to the filter section (250) shown in FIG. 2.

[0102] FIG. 8 is a block diagram showing the configuration of an electronic device (80) according to one embodiment of the present invention. FIG. 8 is a block diagram showing an electronic device (80) including a vision sensor (810), an image sensor (820), and an illuminance sensor (830).

[0103] An electronic device (80) according to one embodiment of the present invention may include a vision sensor (810), an image sensor (820), an illuminance sensor (830), a noise distribution estimation unit (840), and a filter unit (850). The vision sensor (810) may correspond to the vision sensor (210) shown in FIG. 2. The image sensor (820) may correspond to the image sensor (620) shown in FIG. 6, and the illuminance sensor (830) may correspond to the illuminance sensor (720) shown in FIG. 7.

[0104] The noise distribution estimation unit (830) can estimate the distribution of incorrectly recognized events (hereinafter, noise) among the event signals detected by the vision sensor (810).

[0105] According to one embodiment of the present invention, the noise distribution estimation unit (830) can estimate the distribution of noise based on the event signal received from the vision sensor (810), the illuminance value received from the image sensor (820), and the illuminance value received from the illuminance sensor (830). The noise distribution estimation unit (840) can estimate the noise distribution by utilizing both the illuminance value received from the image sensor (820) and the illuminance value received from the illuminance sensor (830). For example, the noise distribution estimation unit (840) can utilize all of the illuminance values ​​received from each sensor by selecting some of them or calculating an average value.

[0106] According to an embodiment of the present invention, when a vision sensor (810) and an image sensor (820) capture a subject with the same angle of view, the noise distribution can be estimated based on the light intensity information of the entire pixel area or by area using the event signal generated from the vision sensor (810) and the illuminance value information measured by the image sensor (820) and the illuminance sensor (830), respectively.

[0107] According to an embodiment of the present invention, the noise distribution estimation unit (830) can individually estimate the noise distribution determined as a positive event and the noise distribution determined as a negative event in a low-light environment.

[0108] The noise distribution estimation unit (830) can provide information about the estimated noise distribution to the filter unit (850).

[0109] The filter section (850) can correspond to the filter section (250) shown in FIG. 2.

[0110] Although all components constituting an embodiment of the present invention have been described above as being combined or operating in combination, the present invention is not necessarily limited to such embodiments. That is, within the scope of the purpose of the present invention, all components may be selectively combined in one or more ways to operate.

[0111] Meanwhile, the various embodiments described herein may be implemented by hardware, middleware, microcode, software and / or combinations thereof. For example, the various embodiments may be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, other electronic units designed to perform the functions presented herein, or combinations thereof.

[0112] Additionally, for example, various embodiments may be stored or encoded on a computer-readable medium containing instructions. Instructions stored or encoded on a computer-readable medium may enable a programmable processor or other processor to perform a method, for example, when the instructions are executed. A computer-readable medium includes a computer storage medium, and the computer storage medium may be any available medium accessible by a computer. For example, such a computer-readable medium may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage media, magnetic disk storage media or other magnetic storage devices.

[0113] Such hardware, software, firmware, etc., may be implemented within the same device or in individual devices to support the various operations and functions described in this specification. Additionally, components, units, modules, components, etc., described as "parts" in this invention may be implemented together or individually as separate but interoperable logic devices. Descriptions of different features of modules, units, etc., are intended to highlight different functional embodiments and do not necessarily imply that they must be realized by individual hardware or software components. Rather, functions associated with one or more modules or units may be performed by individual hardware or software components or integrated within common or individual hardware or software components.

[0114] Although operations are depicted in a specific order in the drawings, it should not be understood that these operations must be performed in the specific order depicted or in a sequential order to achieve the desired result, or that all depicted operations must be performed. In any environment, multitasking and parallel processing may be advantageous. Furthermore, the distinction of various components in the above-described embodiments should not be understood as requiring such distinction in all embodiments, and it should be understood that the described components may generally be integrated together into a single software product or packaged into multiple software products.

[0115] The electronic device, server, or external device according to the various embodiments of the present document described above may include, for example, at least one of a smartphone, tablet PC, mobile phone, video phone, desktop PC, laptop PC, PDA (personal digital assistant), PMP (portable multimedia player), MP3 player, mobile medical device, camera, or wearable device.

[0116] According to various embodiments, the wearable device may include at least one of an accessory type (e.g., a watch, ring, bracelet, anklet, necklace, glasses, contact lens, or head-mounted device (HMD)), a fabric or clothing integrated type (e.g., electronic clothing), a body-attached type (e.g., a skin pad or tattoo), or a bio-implantable type (e.g., an implantable circuit).

[0117] In some embodiments, the electronic device or external device may be a home appliance. The home appliance may include, for example, at least one of a television, a DVD player (Digital Video Disk player), audio, a refrigerator, an air conditioner, a vacuum cleaner, an oven, a microwave oven, a washing machine, an air purifier, a set-top box, a home automation control panel, a security control panel, a TV box, a game console, an electronic dictionary, an electronic key, a camcorder, or a digital photo frame.

[0118] In another embodiment, the electronic device, external device, and wearable device may include at least one of various medical devices (e.g., various portable medical measuring devices (blood glucose meter, heart rate monitor, blood pressure monitor, or body temperature monitor, etc.), MRA (magnetic resonance angiography), MRI (magnetic resonance imaging), CT (computed tomography), imaging device, or ultrasound device, etc.), navigation device, satellite navigation system (GNSS (Global Navigation Satellite System)), EDR (event data recorder), FDR (flight data recorder), automotive infotainment device, home robot, or Internet of Things device (e.g., light bulb, various sensor, electric or gas meter, sprinkler device, fire alarm, thermostat, street light, exercise equipment, hot water tank, heater, boiler, etc.).

[0119]

[0120] As described above, the best embodiments have been disclosed in the drawings and specification. Specific terms have been used herein, but they are used only for the purpose of describing the invention and are not intended to limit the meaning or the scope of the invention as described in the claims. Therefore, those skilled in the art will understand that various modifications and equivalent alternative embodiments are possible therefrom. Accordingly, the true technical scope of protection of the invention should be determined by the technical spirit of the appended claims.

Claims

1. A vision sensor that detects changes in the intensity of light incident from a light source and outputs an event signal; A noise distribution estimation unit that estimates the distribution of noise for the above-detected event signal; and A filter unit that removes noise based on the above-mentioned estimated noise distribution An electronic device including 2. In Claim 1, The above noise distribution estimation unit is Individually estimating the noise distribution determined as a positive event and the noise distribution determined as a negative event output from the vision sensor. Electronic device.

3. In Claim 1, The above filter part Removing the above noise using a non-linear filtering method Electronic device.

4. In Claim 2, The above filter part A first filter unit that performs filtering on a noise distribution determined to be the above positive event; and A second filter unit that performs filtering on the noise distribution determined to be the above-mentioned sub-event An electronic device including 5. In Claim 1, Illumination sensor that measures illuminance Includes more, The above noise distribution estimation unit is Estimating the distribution of noise for the detected event signal by considering the above-mentioned measured illuminance Electronic device.

6. In Claim 1, Image sensor that measures illuminance Includes more, The above noise distribution estimation unit is Estimating the distribution of noise for the detected event signal by considering the above-mentioned measured illuminance Electronic device.

7. In Claim 6, The image sensor divides the included pixels into multiple regions and measures the internal average illuminance value for each region. The above noise distribution estimation unit is Estimating the distribution of noise for the detected event signal by considering the above-mentioned average illuminance value Electronic device.

8. In Claim 1, The above noise distribution estimation unit is Estimating the noise distribution based on previously observed noise patterns Electronic device.

9. In Claim 1, The above noise distribution estimation unit is Estimating the noise distribution using a pre-existing artificial intelligence model Electronic device.

10. In a method of operating an electronic device, A step of detecting a change in the intensity of light incident from a light source and outputting an event signal; A step of estimating the distribution of noise for the detected event signal; and Step of removing noise based on the above-mentioned estimated noise distribution A method of operation of an electronic device including

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