Abstract: A wrinkle detection method includes: obtaining an original image, where the original image includes a face; adjusting a size of an ROI region on the original image to obtain at least two ROI images of different sizes, where the ROI region is a region in which a wrinkle on the face is located. A terminal device processes all the at least two ROI images of different sizes to obtain at least two binary images, where a white region in each binary image is a region in which a wrinkle is suspected to appear. The terminal device fuses the at least two binary images to obtain a final image, where a white region on the final image is recognized as a wrinkle.

Abstract: This application provides a voice interaction method. For a plurality of electronic devices equipped with a same voice assistant, a voice assistant of only one electronic device is in a working mode, and voice assistants of other electronic devices are all in a silent mode. When a user gives a voice for the voice assistant, the other electronic devices whose voice assistants are in the silent mode do not respond to a first instruction triggered by the voice of the user, only the electronic device whose voice assistant is in the working mode sends, according to the first instruction triggered by the voice of the user, a second instruction to an electronic device that is in the plurality of electronic devices and that has a capability of executing a task requested by the user, and the electronic device that receives the second instruction executes the task requested by the user.

Abstract: A wrinkle detection method includes: rotating a region, in a face image, in which a wrinkle needs to be detected, to obtain a plurality of to-be-detected images; determining wrinkle points from all pixel points based on grayscale values of the pixel points in each of the to-be-detected images with different angles; determining at least one wrinkle line based on the wrinkle points; and then displaying, by the electronic device, the wrinkle line in the region in which the wrinkle needs to be detected, where each wrinkle line indicates one wrinkle in each of the to-be-detected images.

Abstract: An electronic device includes a display panel, a camera, a fingerprint recognition light source, and a light steering element, where in the display panel, transmittance of a first display area is greater than transmittance of a second display area that includes a fingerprint recognition area, where the camera, the fingerprint recognition light source, and the light steering element are all located on a side of the display panel that is back onto a light outlet surface of the display panel, and where the camera includes an optical-to-electrical conversion chip, the fingerprint recognition light source is configured to emit light to the fingerprint recognition area in a fingerprint recognition mode, and the light steering element is configured to transfer light reflected by a body part that presses the fingerprint recognition area to the optical-to-electrical conversion chip in the fingerprint recognition mode.

Abstract: An image acquisition method includes acquiring a first image based on a first photographing parameter, where the first image includes a first to-be-detected item, acquiring a second image based on a second photographing parameter, where the second image includes a second to-be-detected item, and determining, based on the first image and the second image, a detection result corresponding to the first to-be-detected item and a detection result corresponding to the second to-be-detected item.

Abstract: A skin detection method includes: dividing a region of interest in a face image into a highlighted region and a non-highlighted region; separately determining a first segmentation threshold of the highlighted region and a second segmentation threshold of the non-highlighted region; obtaining a binary image of the highlighted region based on the first segmentation threshold, and obtaining a binary image of the non-highlighted region based on the second segmentation threshold; fusing the binary image of the highlighted region and the binary image of the non-highlighted region; and identifying, based on a fused image, pores and/or blackheads included in the region of interest.

Abstract: A method includes, in response to a first operation performed on a first electronic device, obtaining, by the first electronic device, an image using a camera of the first electronic device, where the image includes a hand region and a face region, and the first operation indicates a start of a skin care process; extracting a target image feature from the image, where the target image feature is a feature related to the hand region and the face region; and outputting integrity of the skin care process based on target image features corresponding to a plurality of frames of images, where the frames of images are images generated in a time sequence in the skin care process.

Abstract: A dark circle detection and evaluation method includes: obtaining a to-be-processed image; extracting a dark circle region of interest from the to-be-processed image; performing color clustering on the dark circle region of interest to obtain n types of colors in the dark circle region of interest, where n is a positive integer; recognizing a dark circle region in the dark circle region of interest based on the n types of colors; and obtaining a dark circle evaluation result based on the dark circle region.

Abstract: An appearance analysis method includes an electronic device obtaining a first image associated with a first region of an object and a second image associated with a second region of the object, where the first image is collected by a first camera, where the second image is collected by a second camera, and wherein the first region is different from the second region. The electronic device provides an appearance evaluation of the object, where the appearance evaluation is determined based on the first image and the second image.

Abstract: A skin detection and evaluation method includes: obtaining a face image of a user; detecting a skin problem that appears in the face image; prompting in a first interface, the user that the skin problem appears on a face, wherein the first interface comprises the face image; and displaying a second interface in response to a first operation performed by the user in the first interface, wherein the second interface comprises a first facial simulated image obtained after the skin problem is aged; or displaying a third interface in response to a second operation performed by the user in the first interface, wherein the third interface comprises a second facial simulated image obtained after the skin problem is de-aged.

Abstract: The technology of this application relates to an artificial intelligence terminal-based image detection method and apparatus, and an electronic device. The method includes obtaining a to-be-detected image, determining a light source region of the to-be-detected image and a foreground region of the to-be-detected image, and determining a blurring degree of the to-be-detected image based on the light source region and the foreground region. Impact of a light source on clarity of the to-be-detected image is determined by performing light source region detection and foreground region detection on the to-be-detected image, to effectively detect whether an image shot in a backlight condition is blurred.

Abstract: An interaction method for an electronic device for skin detection includes recognizing a hand action and a face of a user to determine a target hand action; determining a detection target corresponding to the hand action based on the target hand action; determining from an extended content library based on the detection target and a shape of the detection target, extended content associated with the detection target and the shape of the detection target, and outputting the extended content.

Abstract: This application provides a skin color detection method and apparatus. The skin color detection method includes: obtaining a face image (101); determining a face key point (102) in the face image; determining a skin color estimation region of interest (Region Of Interest, ROI) and an illumination estimation region of interest ROI (103) in the face image based on the face key point; obtaining a detected skin color value (104) corresponding to the skin color estimation region of interest; obtaining a detected illumination color value (105) corresponding to the illumination estimation region of interest; and using the detected skin color value and the detected illumination color value as feature input of a skin color estimation model, and obtaining a corrected skin color value (106) output by the skin color estimation model.

Abstract: An image processing method includes: converting a red yellow blue RYB image into a grid image based on a red green blue RGB format; generating a first brightness layer of the grid image, and determining a reference gain compensation array used to adjust the first brightness layer; obtaining, based on a preset compensation array correspondence, a target gain compensation array that is associated with the reference gain compensation array and based on an RYB format; and adjusting a second brightness layer of the RYB image by using the target gain compensation array, to generate a corrected image.

Abstract: An electronic device having a flexible display screen and a processing method thereof, where bending the electronic device may cause the electronic device to switch between a smartphone mode and a wearable mode. In the wearable mode, the electronic device displays content on a part of the flexible display screen.

Abstract: In an example information search method, if a first terminal performs a first search based on a first keyword, and does not obtain a result, the first terminal generates a request for performing a second search, and sends, to a network device, the request for performing the second search. The network device sends a second request to a second terminal. The second terminal performs the second search based on the first keyword, obtains a second search result, and sends the second search result to the first terminal. Through this technique, it can be effectively ensured that a user finds a search result corresponding to the first keyword, and that user privacy is also ensured.

Abstract: The technology of this application relates to an artificial intelligence terminal-based image detection method and apparatus, and an electronic device. The method includes obtaining a to-be-detected image, determining a light source region of the to-be-detected image and a foreground region of the to-be-detected image, and determining a blurring degree of the to-be-detected image based on the light source region and the foreground region. Impact of a light source on clarity of the to-be-detected image is determined by performing light source region detection and foreground region detection on the to-be-detected image, to effectively detect whether an image shot in a backlight condition is blurred.

Abstract: In a facial skin detection method performed by a terminal device having a front-facing camera, a first image including a face is obtained and feature information of pores in a target area of the face is extracted. The pores in the target area are classified into pore categories based on the feature information of the pores in the target area. Feature information of pores of each pore category is input into at least one pore detection model to obtain pore detection data of each pore category and a skin detection result of the face is determined based on pore detection data of the pore categories.

Abstract: An electronic device having a touch-sensitive surface and a processing method for the electronic device. When a pressing operation on an application icon is detected on the touch-sensitive surface, a menu including m operation options is displayed on a display screen of the electronic device so that a user quickly performs different operations on an application program. The m operation options are determined based on at least one of: a quantity of times that an operation option is tapped, a time at which an operation option is taped, a location of the electronic device when an operation option is tapped, unread information in an application corresponding to the application icon, data obtained before the application is suspended, data obtained when the application runs in the background, or a communication object in the application.

Abstract: An eye open or closed state detection method, in addition to an eye opening feature, an iris shape feature and/or a vertical direction feature are added to identify the eye open or closed state, where the eye opening feature is used to represent an eye opening degree, the iris shape feature is used to represent a shape of an iris of an eye, and the vertical direction feature is used to represent a change degree of an eyelid curve.