WO2022240186A1

WO2022240186A1 - Image distortion correction method and electronic device therefor

Info

Publication number: WO2022240186A1
Application number: PCT/KR2022/006737
Authority: WO
Inventors: 신대규; 문승민; 임광용
Original assignee: 삼성전자 주식회사
Priority date: 2021-05-11
Filing date: 2022-05-11
Publication date: 2022-11-17
Also published as: KR20220153366A

Abstract

An electronic device, according to one embodiment, comprises: an image sensor; a display; and at least one processor operatively connected to the image sensor and the display. The at least one processor: acquires an image frame through the image sensor and segments the image frame into a plurality of lattice regions; detects, in the acquired image frame, at least one element among at least one object or line component; by analyzing a lattice region including the detected at least one element, determines regions, among the plurality of lattice regions, where line distortion correction is to be carried out; on the basis of the determined regions, carries out line distortion correction on a first lattice region, among the plurality of lattice regions, on the basis of a first weighted value, and carries out line distortion correction on a second lattice region, among the plurality of lattice regions, on the basis of a second weighted value; and may display the distortion-corrected image frame on the display. Other various embodiments are possible as identified in the specification.

Description

Method for correcting image distortion and its electronic device

Embodiments disclosed in this document relate to an electronic device and method for correcting distortion of an image.

As the performance requirements of mobile terminals increase, a digital camera-level field of view (FOV) is required for a camera of the mobile terminal. Therefore, cameras with various angles of view are applied to mobile terminals, and in particular, wide-angle cameras (eg, ultra wide) can display a wide area on the display of mobile terminals.

Also, in order to correct image distortion caused by using a wide-angle camera, a stereographic projection method may be used. The stereographic projection method is a method used to correct an object by changing the angle of view in an image distorted by lens characteristics.

When correcting a distorted image using a stereo graphic projection method, the object at the edge of the image is corrected, but the line around the object is rather distorted because the angle of view is changed for the entire image. occurs.

Conversely, correction in the form of extending the image periphery to reduce distortion of the line can correct the line, but causes a problem of intensifying distortion of an object other than the line.

Various embodiments of the present disclosure provide a method capable of identifying characteristics of each region of an image and performing at least one of line correction, face correction, and/or object correction for each region based on the identified characteristics.

According to an embodiment, an electronic device includes an image sensor, a display, and at least one processor operatively connected to the image sensor and the display, and the at least one processor acquires an image frame through the image sensor to obtain an image. Dividing the frame into a plurality of lattice areas, detecting at least one element among at least one object or line component in the acquired image frame, and analyzing the lattice area including the detected at least one element, thereby forming a plurality of lattice areas. An area to be subjected to line distortion correction is determined, and based on the determined area, a first lattice area among a plurality of lattice areas performs line distortion correction based on a first weight, and a second lattice area among the plurality of lattice areas is determined based on the determined area. may perform line distortion correction based on the second weight, and display an image frame on which distortion correction is performed on a display.

An operating method of an electronic device according to an embodiment includes obtaining an image frame through an image sensor, dividing the image frame into a plurality of lattice areas, and selecting at least one element among at least one object or line component in the obtained image frame. Detecting, analyzing a lattice area including at least one detected element, and determining an area to perform line distortion correction among a plurality of lattice areas, based on the determined area, a first lattice area among the plurality of lattice areas An operation of performing line distortion correction on a region based on a first weight, and performing line distortion correction on a second grid region among a plurality of grid regions based on a second weight, and displaying an image frame on which distortion correction is performed on a display. action may be included.

According to various embodiments disclosed in this document, it is possible to efficiently perform distortion correction by determining characteristics of each region of an image.

In addition, according to various embodiments, power consumption may be minimized by reducing an amount of computation related to correction.

Also, according to various embodiments, distortion is minimized even in a wide-angle shooting environment, so that high-quality photos can be provided to the user.

In addition to this, various effects identified directly or indirectly through this document may be provided.

1 is a diagram illustrating structures of an electronic device and a camera module according to an embodiment.

2 illustrates a hardware configuration of an electronic device according to an embodiment.

3 illustrates a process for correcting image distortion in an electronic device according to an embodiment.

4 illustrates a process of performing line correction on an image obtained by an electronic device according to an embodiment.

5 illustrates a process of performing object correction on an image acquired by an electronic device according to an embodiment.

6 is a flowchart illustrating a process for correcting a distorted image in an electronic device according to an embodiment.

7 is a diagram illustrating that an electronic device divides and analyzes an input image into grid areas according to an exemplary embodiment.

8 illustrates a first image 700 acquired by an electronic device and a region obtained by cropping a part of the first image 700 according to an exemplary embodiment.

9 illustrates matching of mismatched cell points generated in a process of performing warping in an electronic device according to an embodiment.

10 is a block diagram of an electronic device in a network environment according to various embodiments.

11 is a block diagram illustrating a camera module, according to various embodiments.

Hereinafter, various embodiments of this document will be described with reference to the accompanying drawings. However, this document is not intended to limit the specific embodiments, and should be understood to include various modifications, equivalents, and/or alternatives of the embodiments of the present invention.

1 is a diagram schematically illustrating an external appearance of an electronic device 100 equipped with a camera module 180 and a camera module 180 according to an exemplary embodiment. Although the embodiment of FIG. 1 has been illustrated and described on the premise of a mobile device, in particular, a smart phone, it can be applied to an electronic device equipped with a camera among various electronic devices or mobile devices to those skilled in the art. will be clearly understood.

Referring to FIG. 1 , a display 110 may be disposed on a front surface of an electronic device 100 according to an embodiment. In one embodiment, the display 110 may occupy most of the front surface of the electronic device 100 . A display 110 and a bezel 190 area surrounding at least some edges of the display 110 may be disposed on the front surface of the electronic device 100 . The display 110 may include a flat area and a curved area extending from the flat area toward the side of the electronic device 100 . The electronic device 100 shown in FIG. 1 is an example, and various embodiments are possible. For example, the display 110 of the electronic device 100 may include only a flat area without a curved area or may have a curved area only at one edge rather than both sides. Also, in one embodiment, the curved area extends to the rear surface of the electronic device, so that the electronic device 100 may include an additional flat area.

In one embodiment, the electronic device 100 may additionally include a speaker, a receiver, a front camera, a proximity sensor, a home key, and the like. In the electronic device 100 according to an embodiment, the rear cover 150 may be integrally provided with the main body of the electronic device. In another embodiment, the rear cover 150 may be separated from the main body of the electronic device 100 and may have a form in which a battery can be replaced. The rear cover 150 may also be referred to as a battery cover or a rear cover.

In one embodiment, a fingerprint sensor 171 for recognizing a user's fingerprint may be included in the first area 170 of the display 110 . Since the fingerprint sensor 171 is disposed on a lower layer of the display 110, it may not be recognized by the user or may be difficult to be recognized. In addition to the fingerprint sensor 171 , a sensor for additional user/biometric authentication may be disposed in a partial area of the display 110 . In another embodiment, a sensor for user/biometric authentication may be disposed in one area of the bezel 190 . For example, an IR sensor for iris authentication may be exposed through one area of the display 110 or through one area of the bezel 190 .

In one embodiment, a front camera 161 may be disposed in the second region 160 of the front of the electronic device 100 . In the embodiment of FIG. 1 , the front camera 161 is shown as being exposed through one area of the display 110, but in another embodiment, the front camera 161 may be exposed through the bezel 190. The electronic device 100 may include one or more front cameras 161 . For example, the electronic device 100 may include two front cameras such as a first front camera and a second front camera. In one embodiment, the first front camera and the second front camera may be cameras of the same type having the same specifications (eg, pixels), but the first front camera and the second front camera may be implemented as cameras having different specifications. . The electronic device 100 may support functions related to dual cameras (eg, 3D shooting, auto focus, etc.) through two front cameras. The above-mentioned description of the front camera may be equally or similarly applied to the rear camera of the electronic device 100 .

In one embodiment, the electronic device 100 may additionally include various types of hardware or sensors 163 that assist shooting, such as a flash. For example, a distance sensor (eg, a TOF sensor) for detecting a distance between a subject and the electronic device 100 may be further included. The distance sensor may be applied to both a front camera and/or a rear camera. The distance sensor may be disposed separately or included in the front camera and/or the rear camera.

In one embodiment, at least one physical key may be disposed on a side surface of the electronic device 100 . For example, the first function key 151 for turning on/off the display 110 or turning on/off the power of the electronic device 100 may be disposed on the right edge of the electronic device 100 based on the front side. have. In one embodiment, the second function key 152 for controlling the volume or screen brightness of the electronic device 100 may be disposed at the left edge of the electronic device 100 based on the front surface. In addition to this, additional buttons or keys may also be disposed on the front or rear of the electronic device 100. For example, a physical button or touch button mapped to a specific function may be disposed in a lower area of the front bezel 190 .

The electronic device 100 shown in FIG. 1 corresponds to one example and does not limit the shape of a device to which the technical ideas disclosed in this disclosure are applied. For example, by adopting a flexible display and a hinge structure, a foldable electronic device capable of being folded horizontally or vertically, a rollable electronic device capable of rolling, a tablet or a laptop may also be used according to the technical spirit of the present disclosure. this may apply. In addition, the present technical concept may be applied even when the first camera and the second camera facing the same direction can be disposed to face different directions through rotation, folding, or deformation of the device.

Referring to FIG. 1 , an electronic device (eg, electronic device 1001 of FIG. 10) 100 according to an embodiment may include a camera module (eg, camera module 1080 of FIG. 10) 180. have. The camera module 180 includes a lens assembly (eg, the lens assembly 1110 of FIG. 11) 111, a housing 113, an infrared cut filter 115, an image sensor (eg, the image of FIG. 11 ). A sensor 1130) 120 and an image signal processor (eg, the image signal processor 1160 of FIG. 11) 130 may be included.

In one embodiment, the lens assembly 111 may have different numbers, arrangements, and types of lenses according to the front camera and the rear camera. Depending on the type of lens assembly, the front camera and rear camera may have different characteristics (eg, focal length, maximum magnification, etc.). The lens can be moved forward and backward along the optical axis, and can be operated so that a target object to be a subject can be clearly photographed by changing a focal length.

In one embodiment, the camera module 180 may include a lens barrel for mounting at least one lens aligned on an optical axis and a housing 113 for mounting at least one coil surrounding the barrel around the optical axis. can

In one embodiment, the infrared cut filter 115 may be disposed on the upper surface of the image sensor 120 . An image of the subject passing through the lens may be partially filtered by the infrared cut filter 115 and then detected by the image sensor 120 .

In one embodiment, the image sensor 120 may be disposed on the upper surface of the printed circuit board. The image sensor 120 may be electrically connected to the image signal processor 130 connected to the printed circuit board 140 through a connector. A flexible printed circuit board (FPCB) or a cable may be used as the connector.

In an embodiment, the image sensor 120 may be a complementary metal oxide semiconductor (CMOS) sensor or a charged coupled device (CCD) sensor. A plurality of individual pixels are integrated in the image sensor 120, and each individual pixel may include a micro lens, a color filter, and a photodiode. Each individual pixel can convert input light into an electrical signal as a kind of photodetector. Photodetectors generally cannot detect the wavelength of the captured light by themselves and cannot determine color information. The photodetector may include a photodiode.

In one embodiment, light information of a subject incident through the lens assembly 111 may be converted into an electrical signal by the image sensor 120 and input to the image signal processor 130 .

In one embodiment, the camera module 180 may be disposed on the front as well as the back of the electronic device 100 . In addition, the electronic device 100 may include not only one camera module 180 but also multiple camera modules 180 to improve camera performance. For example, the electronic device 100 may further include a front camera 161 for video call or self-portrait. The front camera 161 may support a relatively low number of pixels compared to the rear camera module. The front camera may be relatively smaller than the rear camera module.

2 illustrates a hardware configuration of an electronic device according to an embodiment. In the description of FIG. 2, the configuration described in FIG. 1 may be briefly described or omitted.

Referring to FIG. 2 , in one embodiment, the electronic device 100 includes a camera module 180, a processor (eg, the processor 1020 of FIG. 10) 220, a display (eg, the display module 1060 of FIG. 10) ) 110 and a memory (eg, the memory 1030 of FIG. 10) 230. In the description of FIG. 2 , descriptions of the same reference numerals as in FIG. 1 may be omitted.

In one embodiment, the camera module 180 may include a lens assembly 111 , an image sensor 120 , a distance detection sensor 210 and an image signal processor 130 .

Components shown in FIG. 2 are exemplary, and the electronic device 100 may further include additional components. For example, the electronic device 100 may further include at least one microphone for recording audio data. Also, for example, the electronic device 100 may include at least one sensor for determining a direction in which the front or rear side of the electronic device 100 faces and/or attitude information of the electronic device 100 . In one embodiment, the at least one sensor may include an acceleration sensor, a gyro sensor, and the like. A detailed description of hardware included or may be included in the electronic device 100 of FIG. 2 is provided with reference to FIG. 11 .

In an embodiment, the image sensor 120 may include a complementary metal oxide semiconductor (CMOS) sensor or a charged coupled device (CCD) sensor. Light information of a subject incident through the lens assembly 111 may be converted into electrical signals by the image sensor 120 and input to the image signal processor 130 . An infrared cut filter (hereinafter referred to as an IR cut filter) may be disposed on the upper surface of the image sensor 120, and an image of a subject passing through the lens is partially filtered by the IR cut filter, and then the image sensor 120 ) can be detected by

In one embodiment, when the image signal processor 130 and the image sensor 120 are physically separated, there may be a sensor interface that meets the standard.

In one embodiment, the image signal processor 130 may perform image processing on electrically converted image data. A process in the image signal processor 130 may be divided into a pre-ISP (hereinafter referred to as pre-processing) and an ISP chain (hereinafter referred to as post-processing). Image processing before the demosaicing process may mean pre-processing, and image processing after the demosaicing process may mean post-processing. The preprocessing process may include 3A processing, lens shading correction, edge enhancement, dead pixel correction, and knee correction. The 3A may include at least one of auto white balance (AWB), auto exposure (AE), and auto focusing (AF). The post-processing process may include at least one of changing a sensor index value, changing a tuning parameter, and adjusting an aspect ratio. The post-processing process may include processing image data output from the image sensor 120 or image data output from the scaler. The image signal processor 130 may adjust contrast, sharpness, saturation, dithering, and the like of an image through a post-processing process. Here, the contrast, sharpness, and saturation adjustment procedures may be executed in the YUV color space, and the dithering procedure may be executed in the RGB (Red Green Blue) color space. . Some of the pre-processing may be performed in the post-processing process, or some of the post-processing may be performed in the pre-processing process. Also, some of the pre-processing processes may overlap with some of the post-processing processes.

In one embodiment, the display 110 may display content such as an execution screen of an application executed by the processor 220 or an image and/or video stored in the memory 230 on the display 110 . Also, the processor 220 may display image data acquired through the camera module 180 on the display 110 in real time.

In one embodiment, the display 110 may be integrally implemented with the touch panel. The display 110 may support a touch function, detect a user input such as a touch using a finger, and transmit the same to the processor 220 . The display 110 may be connected to a display driver integrated circuit (DDIC) for driving the display 110, and the touch panel may be connected to a touch IC that detects touch coordinates and processes touch-related algorithms. In one embodiment, the display driving circuit and the touch IC may be integrally formed, and in another embodiment, the display driving circuit and the touch IC may be formed separately. The display driving circuit and/or touch IC may be electrically connected to the processor 220 .

In one embodiment, the processor 220 may execute/control various functions supported by the electronic device 100 . For example, the processor 220 may execute an application and control various types of hardware by executing codes written in a programming language stored in the memory 230 . For example, the processor 220 may execute an application that supports a photographing function stored in the memory 230 . Also, the processor 220 may execute the camera module 180 and set and support an appropriate shooting mode so that the camera module 180 may perform an operation intended by the user.

In one embodiment, the memory 230 may store instructions executable by the processor 220 . The memory 230 may be understood as a concept including a component for temporarily storing data, such as random access memory (RAM), and/or a component for permanently storing data, such as a solid state drive (SSD). . For example, the processor 220 may implement a software module in the RAM space by calling instructions stored in the SSD. In various embodiments, the memory 230 may include various types, and an appropriate type may be selected according to the purpose of the device.

In one embodiment, an application associated with the camera module 180 may be stored in the memory 230 . For example, a camera application may be stored in the memory 230 . The camera application may support various shooting functions such as photo shooting, video shooting, panorama shooting, and slow motion shooting.

In one embodiment, applications associated with the camera module 180 may correspond to various types of applications. For example, chat applications, web browser applications, e-mail applications, shopping applications, etc. may use the camera module 180 to support video calls, photo/video attachments, streaming services, product images, or product-related VR (virtual reality) shooting functions. can

3 illustrates a process for correcting image distortion in an electronic device according to an embodiment. An operation subject of the flowchart illustrated in FIG. 3 may be understood as a processor (eg, the processor 220 of FIG. 2 ) or an image signal processor (eg, the image signal processor 130 of FIG. 1 ).

In operation 301 according to an embodiment, the processor 220 may obtain an input image. The input image may be understood as image data or an image frame acquired through the image sensor 120 and input to the processor 220 . The input image may be understood as an image in which distortion occurs in a portion corresponding to the outer edge of the lens when photographing with a wide-angle camera having a wide angle of view. The processor 220 may perform distortion correction on the input image through the following operations. In other words, the processor 220 may identify features of each region of the obtained input image, and perform at least one of line correction, face correction, and/or object correction for each region based on the identified features. For example, the processor 220 may perform line correction on a first area and object correction on a second area that is different from the first area.

In operation 310 according to an embodiment, the processor 220 may perform line correction on the obtained input image. The processor 220 may perform correction on a distorted line in the obtained input image. Operation 310 may be described in detail in operations 311 to 319 of FIG. 4 below.

In operation 320 according to an embodiment, the processor 220 may correct a face region of the obtained input image. After detecting a face in the obtained input image, the processor 220 may perform correction on the distorted face. Operation 320 may be described in detail in operations 321 to 325 of FIG. 5 below.

In operation 330 according to an embodiment, the processor 220 may correct the object area of the obtained input image. After detecting an object other than a face in the acquired input image, the processor 220 may perform correction on the distorted object. Operation 330 may be described in detail in operations 331 to 335 of FIG. 5 below.

In operation 303 according to an embodiment, the processor 220 may output, as a resultant image, an image on which at least one of line correction, face area correction, and object area correction has been performed. The processor 220 may output the resulting image through the display 110 as a preview image. In other words, the processor 220 may display a preview image of the resulting image on the display 110 through a predetermined image processing process on the resulting image.

4 illustrates a process of performing line correction on an image obtained by an electronic device according to an embodiment. Operation 301 and operation 303 according to an embodiment correspond to operation 301 and operation 303 of FIG. 3, so descriptions thereof will be omitted.

In operation 311 according to an embodiment, the processor 220 may divide the acquired image into a plurality of grid areas. For example, the processor 220 may divide the acquired image into 12 grid areas of 3×4. However, this is only an example, and the processor 220 may divide the obtained input image based on various grid patterns or the number of grids. In one embodiment, the processor 220 may refer to an area formed of four dots in the shape of the grid area. For example, the shape of the grid area may include at least a square, rectangular, trapezoidal, and/or rhombic shape.

In operation 313 according to an embodiment, the processor 220 may detect a line component. The processor 220 may detect line components for each of the plurality of divided grids. The processor 220 may analyze the detected line component. The processor 220 may determine whether there are few line components or whether the line has a certain directivity by detecting line components for each grid area.

In operation 315 according to an embodiment, the processor 220 may determine a candidate region to correct a line. The processor 220 may determine a candidate region for correcting a line based on the detected line component. For example, when distortion occurs in a detected line, the processor 220 may determine a grid area including the line as a candidate area to correct the line.

In operation 317 according to an embodiment, the processor 220 may update a candidate region for line correction. Updating the line correction candidate region may mean adding or excluding the line correction region or changing the intensity of correction among the line correction candidate regions.

In an embodiment, the processor 220 may update a candidate region for correcting a line based on a distance from the center of an image among a plurality of grid regions, the number of lines included in the grid region, and/or directionality of the lines. . For example, when there are few line components in the candidate region, the processor 220 may exclude a lattice region including the line components from the region to be corrected for lines or reduce the intensity of line correction. For example, the processor 220 may not perform the line correction or reduce the strength of the line correction because distortion may further occur when performing the line correction when there are few line components or the directionality of the lines is mixed. . For example, the processor 220 may lower the intensity of line correction as the distance from the center of the image decreases. For example, when a face or an object other than a face is detected in an area to be line-corrected, the processor 220 may not perform the line-correction or reduce the strength of the line-correction.

In an embodiment, the processor 220 may update the candidate region to correct the line based on the face region analysis result of operation 323 of FIG. 5 and the object region analysis result of operation 333 of FIG. 5 . For example, when the weight of the face and/or the object in the grid area where the line component is detected is equal to or greater than the first weight, the processor 220 may not perform line correction or may lower the strength of the correction.

In operation 319 according to an embodiment, the processor 220 may perform line correction. The processor 220 may perform line correction based on calibration data for each region to be line corrected. The calibration data may be data composed of pre-stored tables or data generated in real time based on an image acquired by a camera. In one embodiment, the processor 220 may perform line correction based on each weight for each region. For example, the processor 220 may perform line correction on a first grid area based on a first weight and line correction on a second grid area based on a second weight different from the first weight. have.

In one embodiment, the processor 220 may perform warping. For example, the processor 220 may perform a warping operation on an image on which a stereographic projection has been performed. The processor 220 may perform a warping operation so that a distorted image may be displayed on the display 110 by performing the projection method. In an embodiment, the processor 220 may perform image warping by comparing an image on which a projection method has been performed and raw image data obtained through the image sensor 120 . The processor 220 may perform image warping so that the image on which the projection method has been performed corresponds to the position or coordinate information of the original lattice points included in the raw image data.

5 illustrates a process of performing object correction on an image acquired by an electronic device according to an embodiment. Operation 301 and operation 303 according to an embodiment correspond to operation 301 and operation 303 of FIG. 3, so descriptions thereof will be omitted.

In operation 321 according to an embodiment, the processor 220 may detect a face from an image acquired through the image sensor 120 . The processor 220 may detect at least two or more faces in the image. The processor 220 may detect at least a human face or animal face from the image. It will be clearly understood by those skilled in the art that the face detection may be performed by not only the processor 220, but also the image signal processor 130, other hardware and software modules not shown. Operation 321 may follow or precede operation 311 of FIG. 4 .

In operation 323 according to an embodiment, the processor 220 may analyze the face region. The face area may be understood as an area corresponding to the detected face and/or a grid area including the detected face. The processor 220 may determine whether correction is required by analyzing the facial region. The processor 220 may determine whether to correct based on the detected face information. The processor 220 may determine whether or not to correct based on information about the grid area including the face area. The processor 220 may determine whether correction is necessary based on the location where the face is detected and the size of the face. For example, the processor 220 may determine that correction is necessary when the position of the face is located on the periphery away from the center of the image by a first distance or more and the size of the face is equal to or greater than the first size.

In operation 325 according to an embodiment, the processor 220 may perform distortion correction on the detected face area. The processor 220 may perform correction on an image area corresponding to the detected face. The processor 220 may determine a correction weight based on at least one of the detected face shape, size, and/or face distortion degree. The processor 220 may correct the face region based on the weight.

In an embodiment, the processor 220 may extract feature points of the detected face and transform coordinates of the feature points. The processor 220 may perform warping after converting the coordinates. For example, the processor 220 may perform a stereographic projection method in correcting the face area. However, this is only an example, and the processor 220 may correct the distorted face area in other ways. In an embodiment, the processor 220 may perform correction on the center of the face region with a first intensity, and may perform correction on the periphery of the face region with a second intensity lower than the first intensity.

In operation 331 according to an embodiment, the processor 220 may detect an object from an image acquired through the image sensor 120 . The processor 220 may detect at least two or more objects in the image. The object may mean an object different from the face mentioned in operation 321 above. For example, the objects may mean objects such as a chair, a monitor, a beverage bottle, toilet paper, and a pot. It will be clearly understood by those skilled in the art that the object detection may be performed by not only the processor 220, but also the image signal processor 130, other hardware and software modules not shown. Operation 331 may follow or precede operation 311 of FIG. 4 .

In operation 333 according to an embodiment, the processor 220 may perform object area analysis. The object area may be understood as an area corresponding to the detected object and/or a grid area including the detected object. The processor 220 may determine whether correction is required by analyzing the object area. The processor 220 may determine whether or not to correct based on the detected object information. The processor 220 may determine whether or not to correct based on information about the grid area including the object area.

In one embodiment, the processor 220 may determine whether the detected object is an object of a predefined class. The processor 220 may set different levels of importance for each class. The processor 220 may determine whether object correction is to be performed and/or the intensity of correction based on the degree of importance. For example, the processor 220 may determine to perform object correction when an object of a predefined class such as a doll, cat, or dog is detected.

In one embodiment, the processor 220 may determine whether or not to correct the object based on the location where the object is detected and the size of the object. For example, the processor 220 may determine that correction is required when the location of the detected object is located outside the center of the image by a first distance or more and the size of the detected object is greater than or equal to the first size.

In an embodiment, the processor 220 may determine whether or not to correct the object based on the number of line components detected in the grid area including the object area and/or the directionality of the line components.

In operation 335 according to an embodiment, the processor 220 may perform correction on the detected object. When it is determined that correction is necessary in operation 333, the processor 220 may perform correction on the detected object. The processor 220 may perform correction on an image area corresponding to the detected object.

In an embodiment, the processor 220 may extract feature points of the detected object and convert coordinates of the feature points. The processor 220 may perform warping after converting the coordinates. For example, the processor 220 may perform a stereographic projection method in correcting the object area. However, this is only an example, and the processor 220 may correct the distorted object area in other ways. In an embodiment, the processor 220 may perform correction on the center of the object area with a first intensity, and may perform correction on a peripheral portion of the object area with a second intensity lower than the first intensity.

According to operation 610 according to an embodiment, the processor 220 may acquire an image frame through the image sensor 120 . The processor 220 may divide the acquired image frame into a plurality of grid areas.

According to operation 620 according to an embodiment, the processor 220 may detect at least one element among at least one object or line component in the obtained image frame. The at least one object may be an object such as a face or an object.

According to operation 630 according to an embodiment, the processor 220 may determine an area to perform line distortion correction by analyzing a grid area including at least one detected element. The processor 220 may determine a candidate region to perform line distortion correction. The processor 220 may update a candidate region based on information on the determined candidate region. Since this is explained through FIGS. 3 to 5, it will be briefly described here.

According to operation 640 according to an embodiment, the processor 220 performs line distortion correction on the first grid area based on the first weight, and performs line distortion correction on the second grid area based on the second weight. can For example, when the number of lines is large or the proportion of objects included in the first grid region is low, the processor 220 may perform line distortion correction on the first grid region based on the first weight. have. For example, when the number of lines is small or the proportion of objects included in the second grid region is high, the processor 220 corrects line distortion based on a second weight lower than the first weight for the second grid region. can be performed.

According to operation 650 according to an embodiment, the processor 220 may display an image frame on which distortion correction is performed on a display. The processor 220 may output, as a preview image, an image frame on which at least one of line correction, face area correction, and object area correction has been performed through the display 110 .

In one embodiment, referring to FIG. 7 , the first image 700 may be an image acquired through the camera module 180 . The first image 700 may be an image captured by a wide-angle camera and/or an ultra-wide-angle camera. The first image 700 may be an image in which distortion occurs in a portion corresponding to the outer edge of the lens when light is incident through the wide-angle lens and/or the ultra-wide-angle lens. For example, distortion may occur in a mountain ridge 711, a cloud 721, a human face 731, and a tree 741 included in a grid area outside the first image 700.

In an embodiment, the processor 220 may detect line components in at least one grid area. The processor 220 may perform line correction on the distorted line component. For example, the processor 220 may detect a mountain ridge 711 as a line component in the first grid area 710 . In an embodiment, the processor 220 may perform correction by determining strength of line correction based on the directionality and number of detected lines. For example, when the number of detected line components is small and the directionality is not regular, the processor 220 may perform correction by lowering the intensity of line correction. In an embodiment, the processor 220 may determine whether or not to correct based on information about the grid area in which the line component is detected. For example, the processor 220 may perform line correction on the distorted mountain ridge 711 when the specific gravity of the object detected in the first grid area 710 is less than or equal to a certain level.

In an embodiment, the processor 220 may detect line components and objects in at least one grid area. The processor 220 may detect a mountain ridge 711, which is a line component, and an object (eg, a cloud 722) in the second grid area 720. In an embodiment, the processor 220 may perform image correction in consideration of the line component detected in the second grid area 720 and the specific gravity of the object. For example, the processor 220 may perform both line correction and object correction on the second grid area 720 . For example, the processor 220 may perform line correction on the second grid area 720 without object correction. For example, the processor 220 may perform object correction without line correction on the second grid area 720 .

In one embodiment, the processor 220 may detect a face in at least one grid area. The processor 220 may perform face correction on the distorted face. For example, the processor 220 may detect the face 731 in the third grid area 730 . For example, the processor 220 may perform face correction based on the weight of line components included in the third grid area 730 and/or the weight of the distorted face.

In one embodiment, the processor 220 may detect an object included in at least one grid area. The processor 220 may perform object correction on the distorted object. For example, when the processor 220 detects an object (eg, a tree 741) without detecting a line component in the fourth grid area 740, it may perform object correction on the distorted object. .

8 illustrates a first image 700 acquired by an electronic device and a region obtained by cropping a part of the first image 700 according to an exemplary embodiment. Although FIG. 8 is described based on the face 811, it is obvious to those skilled in the art that it can be applied to objects other than the face.

In one embodiment, the processor 220 may detect the face 811 included in the first image 700 . The processor 220 may set a face area 810 including the detected face 811 . The processor 220 may extract feature points from the face area 810 and transform coordinates of the feature points. The processor 220 may perform warping after converting the coordinates.

Referring to reference numeral 900 in FIG. 9 , it can be seen that the cell points do not match during the process of warping by the processor 220 . For example, the first point 901 and the second point 902 may not match.

Referring to reference numeral 910 in FIG. 9 , the processor 220 may match inconsistent cell points in a warping process. The processor 220 may adjust movement values of cell points to gradually change. However, since moving the first point 901 to match the second point 902 or moving the second point 902 to match the first point 901 does not naturally perform distortion correction, The point 901 and the second point 902 may be moved. In other words, the processor 220 may match the first point 901 and the second point 902 at an intermediate value 903 of the first point 901 and the second point 902 .

10 is a block diagram of an electronic device 1001 within a network environment 1000 according to various embodiments. Referring to FIG. 10 , in a network environment 1000, an electronic device 1001 communicates with an electronic device 1002 through a first network 1098 (eg, a short-distance wireless communication network) or through a second network 1099. It is possible to communicate with the electronic device 1004 or the server 1008 through (eg, a long-distance wireless communication network). According to an embodiment, the electronic device 1001 may communicate with the electronic device 1004 through the server 1008. According to an embodiment, the electronic device 1001 includes a processor 1020, a memory 1030, an input module 1050, an audio output module 1055, a display module 1060, an audio module 1070, a sensor module ( 1076), interface 1077, connection terminal 1078, haptic module 1079, camera module 1080, power management module 1088, battery 1089, communication module 1090, subscriber identification module 1096 , or an antenna module 1097. In some embodiments, in the electronic device 1001, at least one of these components (eg, the connection terminal 1078) may be omitted or one or more other components may be added. In some embodiments, some of these components (eg, sensor module 1076, camera module 1080, or antenna module 1097) are integrated into a single component (eg, display module 1060). It can be.

The processor 1020, for example, executes software (eg, the program 1040) to cause at least one other component (eg, hardware or software component) of the electronic device 1001 connected to the processor 1020. It can control and perform various data processing or calculations. According to one embodiment, as at least part of data processing or operation, processor 1020 transfers commands or data received from other components (eg, sensor module 1076 or communication module 1090) to volatile memory 1032. , process commands or data stored in the volatile memory 1032 , and store resultant data in the non-volatile memory 1034 . According to an embodiment, the processor 1020 may include a main processor 1021 (eg, a central processing unit or an application processor) or a secondary processor 1023 (eg, a graphic processing unit, a neural network processing unit ( NPU: neural processing unit (NPU), image signal processor, sensor hub processor, or communication processor). For example, when the electronic device 1001 includes a main processor 1021 and an auxiliary processor 1023, the auxiliary processor 1023 may use less power than the main processor 1021 or be set to be specialized for a designated function. can The auxiliary processor 1023 may be implemented separately from or as part of the main processor 1021 .

The secondary processor 1023 may, for example, take the place of the main processor 1021 while the main processor 1021 is inactive (eg sleep), or the main processor 1021 is active (eg application execution). ) state, together with the main processor 1021, at least one of the components of the electronic device 1001 (eg, the display module 1060, the sensor module 1076, or the communication module 1090) It is possible to control at least some of the related functions or states. According to one embodiment, the auxiliary processor 1023 (eg, image signal processor or communication processor) may be implemented as part of other functionally related components (eg, camera module 1080 or communication module 1090). have. According to an embodiment, the auxiliary processor 1023 (eg, a neural network processing device) may include a hardware structure specialized for processing an artificial intelligence model. AI models can be created through machine learning. Such learning may be performed, for example, in the electronic device 1001 itself where artificial intelligence is performed, or may be performed through a separate server (eg, the server 1008). The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning or reinforcement learning, but in the above example Not limited. The artificial intelligence model may include a plurality of artificial neural network layers. Artificial neural networks include deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), restricted boltzmann machines (RBMs), deep belief networks (DBNs), bidirectional recurrent deep neural networks (BRDNNs), It may be one of deep Q-networks or a combination of two or more of the foregoing, but is not limited to the foregoing examples. The artificial intelligence model may include, in addition or alternatively, software structures in addition to hardware structures.

The memory 1030 may store various data used by at least one component (eg, the processor 1020 or the sensor module 1076) of the electronic device 1001 . The data may include, for example, input data or output data for software (eg, the program 1040) and commands related thereto. The memory 1030 may include a volatile memory 1032 or a non-volatile memory 1034 .

The program 1040 may be stored as software in the memory 1030 and may include, for example, an operating system 1042 , middleware 1044 , or an application 1046 .

The input module 1050 may receive a command or data to be used for a component (eg, the processor 1020) of the electronic device 1001 from an outside of the electronic device 1001 (eg, a user). The input module 1050 may include, for example, a microphone, a mouse, a keyboard, a key (eg, a button), or a digital pen (eg, a stylus pen).

The sound output module 1055 may output sound signals to the outside of the electronic device 1001 . The sound output module 1055 may include, for example, a speaker or receiver. The speaker can be used for general purposes such as multimedia playback or recording playback. A receiver may be used to receive an incoming call. According to one embodiment, the receiver may be implemented separately from the speaker or as part of it.

The display module 1060 may visually provide information to the outside of the electronic device 1001 (eg, a user). The display module 1060 may include, for example, a display, a hologram device, or a projector and a control circuit for controlling the device. According to an embodiment, the display module 1060 may include a touch sensor configured to detect a touch or a pressure sensor configured to measure the intensity of force generated by the touch.

The audio module 1070 may convert sound into an electrical signal or vice versa. According to an embodiment, the audio module 1070 acquires sound through the input module 1050, the sound output module 1055, or an external electronic device connected directly or wirelessly to the electronic device 1001 (eg: Sound may be output through the electronic device 1002 (eg, a speaker or a headphone).

The sensor module 1076 detects an operating state (eg, power or temperature) of the electronic device 1001 or an external environmental state (eg, a user state), and generates an electrical signal or data value corresponding to the detected state. can do. According to one embodiment, the sensor module 1076 may include, for example, a gesture sensor, a gyro sensor, an air pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a bio sensor, It may include a temperature sensor, humidity sensor, or light sensor.

The interface 1077 may support one or more designated protocols that may be used to directly or wirelessly connect the electronic device 1001 to an external electronic device (eg, the electronic device 1002). According to one embodiment, the interface 1077 may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

The connection terminal 1078 may include a connector through which the electronic device 1001 may be physically connected to an external electronic device (eg, the electronic device 1002). According to one embodiment, the connection terminal 1078 may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (eg, a headphone connector).

The haptic module 1079 may convert electrical signals into mechanical stimuli (eg, vibration or motion) or electrical stimuli that a user can perceive through tactile or kinesthetic senses. According to one embodiment, the haptic module 1079 may include, for example, a motor, a piezoelectric element, or an electrical stimulation device.

The camera module 1080 may capture still images and moving images. According to one embodiment, the camera module 1080 may include one or more lenses, image sensors, image signal processors, or flashes.

The power management module 1088 may manage power supplied to the electronic device 1001 . According to one embodiment, the power management module 1088 may be implemented as at least part of a power management integrated circuit (PMIC), for example.

The battery 1089 may supply power to at least one component of the electronic device 1001 . According to an embodiment, the battery 1089 may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

The communication module 1090 is a direct (eg, wired) communication channel or a wireless communication channel between the electronic device 1001 and an external electronic device (eg, the electronic device 1002, the electronic device 1004, or the server 1008). Establishment and communication through the established communication channel may be supported. The communication module 1090 may include one or more communication processors that operate independently of the processor 1020 (eg, an application processor) and support direct (eg, wired) communication or wireless communication. According to one embodiment, the communication module 1090 is a wireless communication module 1092 (eg, a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module 1094 (eg, : a local area network (LAN) communication module or a power line communication module). Among these communication modules, the corresponding communication module is a first network 1098 (eg, a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a second network 1099 (eg, a legacy communication module). It may communicate with the external electronic device 1004 through a cellular network, a 5G network, a next-generation communication network, the Internet, or a telecommunications network such as a computer network (eg, LAN or WAN). These various types of communication modules may be integrated as one component (eg, a single chip) or implemented as a plurality of separate components (eg, multiple chips). The wireless communication module 1092 uses subscriber information (eg, International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module 1096 within a communication network such as the first network 1098 or the second network 1099. The electronic device 1001 may be identified or authenticated.

The wireless communication module 1092 may support a 5G network after a 4G network and a next-generation communication technology, for example, NR access technology (new radio access technology). NR access technologies include high-speed transmission of high-capacity data (enhanced mobile broadband (eMBB)), minimization of terminal power and access of multiple terminals (massive machine type communications (mMTC)), or high reliability and low latency (ultra-reliable and low latency (URLLC)). -latency communications)) can be supported. The wireless communication module 1092 may support a high frequency band (eg, mmWave band) to achieve a high data rate, for example. The wireless communication module 1092 uses various technologies for securing performance in a high frequency band, such as beamforming, massive multiple-input and multiple-output (MIMO), and full-dimensional multiplexing. Technologies such as input/output (FD-MIMO: full dimensional MIMO), array antenna, analog beam-forming, or large scale antenna may be supported. The wireless communication module 1092 may support various requirements defined for the electronic device 1001, an external electronic device (eg, the electronic device 1004), or a network system (eg, the second network 1099). According to an embodiment, the wireless communication module 1092 may be used to realize peak data rate (eg, 20 Gbps or more) for realizing eMBB, loss coverage (eg, 164 dB or less) for realizing mMTC, or U-plane latency (for realizing URLLC). Example: downlink (DL) and uplink (UL) each of 0.5 ms or less, or round trip 1 ms or less) may be supported.

The antenna module 1097 may transmit or receive signals or power to the outside (eg, an external electronic device). According to an embodiment, the antenna module 1097 may include an antenna including a radiator formed of a conductor or a conductive pattern formed on a substrate (eg, PCB). According to an embodiment, the antenna module 1097 may include a plurality of antennas (eg, an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network such as the first network 1098 or the second network 1099 is selected from the plurality of antennas by, for example, the communication module 1090. can be chosen A signal or power may be transmitted or received between the communication module 1090 and an external electronic device through the selected at least one antenna. According to some embodiments, other components (eg, a radio frequency integrated circuit (RFIC)) may be additionally formed as a part of the antenna module 1097 in addition to the radiator.

According to various embodiments, the antenna module 1097 may form a mmWave antenna module. According to one embodiment, the mmWave antenna module includes a printed circuit board, an RFIC disposed on or adjacent to a first surface (eg, a lower surface) of the printed circuit board and capable of supporting a designated high frequency band (eg, mmWave band); and a plurality of antennas (eg, array antennas) disposed on or adjacent to a second surface (eg, a top surface or a side surface) of the printed circuit board and capable of transmitting or receiving signals of the designated high frequency band. can do.

At least some of the components are connected to each other through a communication method between peripheral devices (eg, a bus, general purpose input and output (GPIO), serial peripheral interface (SPI), or mobile industry processor interface (MIPI)) and signal ( e.g. commands or data) can be exchanged with each other.

According to an embodiment, commands or data may be transmitted or received between the electronic device 1001 and the external electronic device 1004 through the server 1008 connected to the second network 1099 . Each of the external electronic devices 1002 or 1004 may be the same as or different from the electronic device 1001 . According to an embodiment, all or part of operations executed in the electronic device 1001 may be executed in one or more external electronic devices among the external electronic devices 1002 , 1004 , or 1008 . For example, when the electronic device 1001 needs to perform a certain function or service automatically or in response to a request from a user or another device, the electronic device 1001 instead of executing the function or service by itself. Alternatively or additionally, one or more external electronic devices may be requested to perform the function or at least part of the service. One or more external electronic devices receiving the request may execute at least a part of the requested function or service or an additional function or service related to the request, and deliver the execution result to the electronic device 1001 . The electronic device 1001 may provide the result as at least part of a response to the request as it is or after additional processing. To this end, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device 1001 may provide an ultra-low latency service using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device 1004 may include an internet of things (IoT) device. Server 1008 may be an intelligent server using machine learning and/or neural networks. According to an embodiment, the external electronic device 1004 or server 1008 may be included in the second network 1099. The electronic device 1001 may be applied to intelligent services (eg, smart home, smart city, smart car, or health care) based on 5G communication technology and IoT-related technology.

11 is a block diagram 1100 illustrating a camera module 1080, according to various embodiments. Referring to FIG. 11 , a camera module 1080 includes a lens assembly 1110, a flash 1120, an image sensor 1130, an image stabilizer 1140, a memory 1150 (eg, a buffer memory), or an image signal processor. (1160). The lens assembly 1110 may collect light emitted from a subject that is an image capture target. The lens assembly 1110 may include one or more lenses. According to one embodiment, the camera module 1080 may include a plurality of lens assemblies 1110. In this case, the camera module 1080 may form, for example, a dual camera, a 360-degree camera, or a spherical camera. Some of the plurality of lens assemblies 1110 may have the same lens properties (eg, angle of view, focal length, auto focus, f number, or optical zoom), or at least one lens assembly may have the same lens properties as another lens assembly. may have one or more lens properties different from the lens properties of . The lens assembly 1110 may include, for example, a wide-angle lens or a telephoto lens.

The flash 1120 may emit light used to enhance light emitted or reflected from a subject. According to one embodiment, the flash 1120 may include one or more light emitting diodes (eg, a red-green-blue (RGB) LED, a white LED, an infrared LED, or an ultraviolet LED), or a xenon lamp. The image sensor 1130 may acquire an image corresponding to the subject by converting light emitted or reflected from the subject and transmitted through the lens assembly 1110 into an electrical signal. According to an embodiment, the image sensor 1130 may be, for example, one image sensor selected from among image sensors having different properties, such as an RGB sensor, a black and white (BW) sensor, an IR sensor, or a UV sensor, It may include a plurality of image sensors having a property, or a plurality of image sensors having other properties. Each image sensor included in the image sensor 1130 may be implemented using, for example, a charged coupled device (CCD) sensor or a complementary metal oxide semiconductor (CMOS) sensor.

The image stabilizer 1140 moves at least one lens or image sensor 1130 included in the lens assembly 1110 in a specific direction in response to movement of the camera module 1080 or the electronic device 1001 including the same. Operation characteristics of the image sensor 1130 may be controlled (eg, read-out timing is adjusted, etc.). This makes it possible to compensate at least part of the negative effect of the movement on the image being taken. According to an embodiment, the image stabilizer 1140 may include a gyro sensor (not shown) or an acceleration sensor (not shown) disposed inside or outside the camera module 1080. Such a movement of the camera module 1080 or the electronic device 1001 can be detected using . According to an embodiment, the image stabilizer 1140 may be implemented as, for example, an optical image stabilizer. The memory 1150 may at least temporarily store at least a portion of an image acquired through the image sensor 1130 for a next image processing task. For example, when image acquisition is delayed according to the shutter, or when a plurality of images are acquired at high speed, the acquired original image (eg, a Bayer-patterned image or a high-resolution image) is stored in the memory 1150 and , a copy image (eg, a low resolution image) corresponding thereto may be previewed through the display device 1060 . Thereafter, when a specified condition is satisfied (eg, a user input or a system command), at least a part of the original image stored in the memory 1150 may be acquired and processed by, for example, the image signal processor 1160 . According to an embodiment, the memory 1150 may be configured as at least a part of the memory 1030 or as a separate memory operated independently of the memory 1030 .

The image signal processor 1160 may perform one or more image processes on an image acquired through the image sensor 1130 or an image stored in the memory 1150 . The one or more image processes, for example, depth map generation, 3D modeling, panorama generation, feature point extraction, image synthesis, or image compensation (eg, noise reduction, resolution adjustment, brightness adjustment, blurring ( blurring, sharpening, or softening. Additionally or alternatively, the image signal processor 1160 may include at least one of the components included in the camera module 1080 (eg, an image sensor). 1130) may be controlled (eg, exposure time control, read-out timing control, etc.) The image processed by the image signal processor 1160 is stored again in the memory 1150 for further processing. or may be provided as an external component of the camera module 1080 (eg, the memory 1030, the display device 1060, the electronic device 1002, the electronic device 1004, or the server 1008). According to an example, the image signal processor 1160 may be configured as at least a part of the processor 1020 or may be configured as a separate processor that operates independently of the processor 1020. The image signal processor 1160 may be configured as a processor 1020 When configured as a separate processor, at least one image processed by the image signal processor 1160 may be displayed through the display device 1060 as it is by the processor 1020 or after additional image processing.

As mentioned above. According to an embodiment, the electronic device 1001 may include a plurality of camera modules 1080 each having different properties or functions. In this case, for example, at least one of the plurality of camera modules 1080 may be a wide-angle camera and at least the other may be a telephoto camera. Similarly, at least one of the plurality of camera modules 1080 may be a front camera and at least the other may be a rear camera.

According to an embodiment, an electronic device (eg, the electronic device 100 of FIG. 2 ) includes an image sensor (eg, the image sensor 120 of FIG. 2 ), a display (eg, the display 110 of FIG. 2 ) and and at least one processor (eg, the processor 220 of FIG. 2 ) operatively connected to the image sensor and the display, wherein the at least one processor obtains an image frame through the image sensor. dividing the image frame into a plurality of lattice areas, detecting at least one element among at least one object or line component in the obtained image frame, and analyzing a lattice area including the detected at least one element , determining an area to be subjected to line distortion correction among the plurality of lattice areas, based on the determined area, performing line distortion correction on a first lattice area among the plurality of lattice areas based on a first weight; A second grid area among the plurality of grid areas may perform line distortion correction based on the second weight, and display the image frame on which the distortion correction is performed on the display.

According to an embodiment, the at least one processor may determine an area in which the line distortion correction is to be performed based on the number of line components and directions of the line components.

According to an embodiment, the first lattice region may be a region in which the specific gravity of the line elements is greater than or equal to the first specific gravity, and the second lattice region may be an region in which the specific gravity of the line elements is less than the first specific gravity.

According to an embodiment, the at least one processor performs a stereographic projection on the at least one detected object, and image warping based on a grid node whose location is changed by the stereographic projection. (warping) can be performed.

According to an embodiment, in performing warping on the lattice points, the at least one processor may match a first lattice point and a second lattice point adjacent to the first lattice point.

According to an embodiment, the at least one processor is configured to match the first lattice point and the second lattice point with an intermediate value of a coordinate value for the first lattice point and a coordinate value for the second lattice point. can

According to an embodiment, the one or more processors may control the intensity of correction for the line distortion based on the size and position of at least one detected object among the one or more detected elements.

According to an embodiment, the at least one processor may determine whether the at least one object is included in a predefined class.

According to an embodiment, the at least one object may include a human face or an object.

According to an embodiment, in addition to the line distortion correction, the at least one processor performs object correction on the detected at least one object, and the image frame on which the line distortion correction and the object correction have been performed is stored in the image frame. can be displayed on the display.

As described above, the operating method of the electronic device (eg, the electronic device 100 of FIG. 2 ) includes obtaining an image frame through an image sensor and dividing the image frame into a plurality of grid areas, the acquired image frame Detecting at least one element among at least one object or line component, analyzing a lattice area including the detected at least one element, and determining an area to perform line distortion correction among the plurality of lattice areas. Based on the determined area, a first lattice area among the plurality of lattice areas performs line distortion correction based on a first weight, and a second lattice area among the plurality of lattice areas performs line distortion correction based on a second weight It may include an operation of performing line distortion correction and an operation of displaying the image frame on which the distortion correction is performed on a display.

According to an embodiment, an operation of determining an area in which the line distortion correction is to be performed based on the number of line components and the direction of the line components may be included.

According to an embodiment, a stereographic projection is performed on the at least one detected object, and image warping is performed based on a grid node whose position is changed by the stereographic projection. action may be included.

According to an embodiment, performing warping on the lattice points may include matching a first lattice point and a second lattice point adjacent to the first lattice point.

According to an embodiment, an operation of matching the first lattice point and the second lattice point with an intermediate value of a coordinate value for the first lattice point and a coordinate value for the second lattice point may be included. .

According to an embodiment, an operation of controlling the strength of correction for the line distortion based on the size and position of at least one detected object among the at least one detected element may be included.

According to an embodiment, an operation of determining whether the at least one object is included in a pre-specified class may be included.

According to an embodiment, in addition to the line distortion correction, an operation of performing object correction on the at least one detected object and an operation of displaying the image frame on which the line distortion correction and the object correction have been performed on the display. can include

Electronic devices according to various embodiments disclosed in this document may be devices of various types. The electronic device may include, for example, a portable communication device (eg, a smart phone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a home appliance. An electronic device according to an embodiment of this document is not limited to the aforementioned devices.

Various embodiments of this document and terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutes of the embodiments. In connection with the description of the drawings, like reference numerals may be used for like or related elements. The singular form of a noun corresponding to an item may include one item or a plurality of items, unless the relevant context clearly dictates otherwise. In this document, "A or B", "at least one of A and B", "at least one of A or B", "A, B or C", "at least one of A, B and C", and "A Each of the phrases such as "at least one of , B, or C" may include any one of the items listed together in that phrase, or all possible combinations thereof. Terms such as "first", "second", or "first" or "secondary" may simply be used to distinguish that component from other corresponding components, and may refer to that component in other respects (eg, importance or order) is not limited. A (eg, first) component is said to be "coupled" or "connected" to another (eg, second) component, with or without the terms "functionally" or "communicatively." When mentioned, it means that the certain component may be connected to the other component directly (eg by wire), wirelessly, or through a third component.

The term "module" used in various embodiments of this document may include a unit implemented in hardware, software, or firmware, and is interchangeably interchangeable with terms such as, for example, logic, logic blocks, components, or circuits. can be used A module may be an integrally constructed component or a minimal unit of components or a portion thereof that performs one or more functions. For example, according to one embodiment, the module may be implemented in the form of an application-specific integrated circuit (ASIC).

Various embodiments of this document describe one or more commands stored in a storage medium (eg, internal memory 1036 or external memory 1038) readable by a machine (eg, electronic device 1001). It may be implemented as software (eg, the program 1040) including them. For example, a processor (eg, the processor 1020) of a device (eg, the electronic device 1001) may call at least one command among one or more instructions stored from a storage medium and execute it. This enables the device to be operated to perform at least one function according to the at least one command invoked. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The device-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-temporary' only means that the storage medium is a tangible device and does not contain a signal (e.g. electromagnetic wave), and this term refers to the case where data is stored semi-permanently in the storage medium. It does not discriminate when it is temporarily stored.

According to one embodiment, the method according to various embodiments disclosed in this document may be included and provided in a computer program product. Computer program products may be traded between sellers and buyers as commodities. A computer program product is distributed 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 ^TM ) or on two user devices (e.g. It can be distributed (eg downloaded or uploaded) online, directly between smart phones. In the case of online distribution, at least part of the computer program product may be temporarily stored or temporarily created in a storage medium readable by a device such as a manufacturer's server, an application store server, or a relay server's memory.

According to various embodiments, each component (eg, module or program) of the components described above may include a single object or a plurality of objects, and some of the multiple objects may be separately disposed in other components. . According to various embodiments, one or more components or operations among the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (eg modules or programs) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by a corresponding component of the plurality of components prior to the integration. . According to various embodiments, operations performed by modules, programs, or other components are executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations are executed in a different order, omitted, or , or one or more other operations may be added.

Claims

In electronic devices,

image sensor;

display; and

at least one processor operatively connected with the image sensor and the display;

The at least one processor is:

Obtaining an image frame through the image sensor and dividing the image frame into a plurality of grid areas;

Detecting at least one element among at least one object or line component in the obtained image frame;

Analyzing a lattice area including the detected at least one element to determine an area to perform line distortion correction among the plurality of lattice areas;

Based on the determined area, a first lattice area among the plurality of lattice areas performs line distortion correction based on a first weight, and a second lattice area among the plurality of lattice areas performs line distortion correction based on a second weight. make a correction;

The electronic device displaying the image frame on which the distortion correction is performed on the display.
The method of claim 1,

The electronic device of claim 1 , wherein the at least one processor determines an area in which the line distortion correction is to be performed based on the number of line components and the direction of the line components.
The method of claim 1,

The first lattice region is a region in which the specific gravity of the line elements is equal to or greater than the first specific gravity, and the second lattice region is an region in which the specific gravity of the line elements is less than the first specific gravity.
The method of claim 1,

The at least one processor performs a stereographic projection on the at least one detected object,

An electronic device that performs image warping based on a grid node whose position is changed by the planar projection method.
The method of claim 4,

In performing warping with respect to the lattice points, the at least one processor matches a first lattice point and a second lattice point adjacent to the first lattice point.
The method of claim 5,

The electronic device of claim 1 , wherein the at least one processor matches the first lattice point and the second lattice point with an intermediate value of a coordinate value for the first lattice point and a coordinate value for the second lattice point.
The method of claim 1,

The electronic device of claim 1 , wherein the at least one processor controls strength of correction for the line distortion based on a size and a position of at least one detected object among the at least one detected element.
The method of claim 1,

The electronic device, wherein the at least one processor determines whether the at least one object is included in a pre-specified class.
The method of claim 1,

The electronic device of claim 1, wherein the at least one object includes a human face or an object.
The method of claim 1,

In addition to the line distortion correction, the at least one processor performs object correction on the detected at least one object,

The electronic device that displays the image frame on which the line distortion correction and the object correction have been performed on the display.
In the operating method of the electronic device,

obtaining an image frame through an image sensor and dividing the image frame into a plurality of grid areas;

detecting at least one element among at least one object or line component in the obtained image frame;

determining an area to perform line distortion correction among the plurality of lattice areas by analyzing a lattice area including the detected at least one element;

Based on the determined area, a first lattice area among the plurality of lattice areas performs line distortion correction based on a first weight, and a second lattice area among the plurality of lattice areas performs line distortion correction based on a second weight. performing a correction; and

and displaying the image frame on which the distortion correction is performed on a display.
The method of claim 11,

and determining an area in which the line distortion correction is to be performed based on the number of line components and the direction of the line components.
The method of claim 11,

The first lattice region is a region in which the specific gravity of the line elements is equal to or greater than the first specific gravity, and the second lattice region is an region in which the specific gravity of the line elements is less than the first specific gravity.
The method of claim 11,

performing a stereographic projection on the at least one detected object;

and performing image warping based on a grid node whose position is changed by the planar projection method.
The method of claim 11,

and controlling strength of correction for the line distortion based on the size and position of at least one detected object among the at least one detected element.