Abstract: A method of recognizing a feature of an image may include receiving an input image including an object; extracting first feature information using a first layer of a neural network, the first feature information indicating a first feature corresponding to the input image among a plurality of first features; extracting second feature information using a second layer of the neural network, the second feature information indicating a second feature among a plurality of second features, the indicated second feature corresponding to the first feature information; and recognizing an element corresponding to the object based on the first feature information and the second feature information.

Abstract: A fingerprint recognition method includes generating an enrollment modified image by modifying a fingerprint image corresponding to a fingerprint to be enrolled; extracting enrollment property information from the fingerprint image; generating mapping information that maps the enrollment modified image to the enrollment property information; and storing the enrollment modified image and the enrollment property information.

Abstract: At least one example embodiment discloses a method of extracting a feature from an input image. The method may include detecting landmarks from the input image, detecting physical characteristics between the landmarks based on the landmarks, determining a target area of the input image from which at least one feature is to be extracted and an order of extracting the feature from the target area based on the physical characteristics and extracting the feature based on the determining.

Abstract: Authentication methods and apparatuses are disclosed. An authentication method may include generating a quality profile of an authentication image, and determining an effective region in the authentication image based on the generated quality profile.

Abstract: A facial recognition method includes identifying a first makeup pattern in a region of interest (ROI) of a first image, applying one of the first makeup pattern and a candidate makeup pattern to a ROI of a second image corresponding to the ROI of the first image to generate a third image and recognizing a face based on the first image and the third image.

Abstract: A fingerprint recognition method includes determining a code corresponding to a query image based on features of blocks in the query image, obtaining information corresponding to the determined code from a lookup table, and verifying the query image based on the obtained information.

Abstract: At least one example embodiment discloses a method of extracting a feature from an input image. The method may include detecting landmarks from the input image, detecting physical characteristics between the landmarks based on the landmarks, determining a target area of the input image from which at least one feature is to be extracted and an order of extracting the feature from the target area based on the physical characteristics and extracting the feature based on the determining.

Abstract: A method of preprocessing an image including biological information is disclosed, in which an image preprocessor may set an edge line in an input image including biological information, calculate an energy value corresponding to the edge line, and adaptively crop the input image based on the energy value.

Abstract: A fingerprint recognition method includes determining a code corresponding to a query image based on features of blocks in the query image, obtaining information corresponding to the determined code from a lookup table, and verifying the query image based on the obtained information.

Abstract: A method and an apparatus for adjusting a pose in a face image are provided. The method of adjusting a pose in a face image involves detecting two-dimensional (2D) landmarks from a 2D face image, positioning three-dimensional (3D) landmarks in a 3D face model by determining an initial pose of the 3D face model based on the 2D landmarks, updating the 3D landmarks by iteratively adjusting a pose and a shape of the 3D face model, and adjusting a pose in the 2D face image based on the updated 3D landmarks.

Abstract: A fingerprint recognition method includes receiving an input partial image corresponding to a partial image of a fingerprint of a first user; partitioning the input partial image into a plurality of blocks; performing a comparison operation based on the plurality of blocks and the enrolled partial images corresponding to partial images of an enrolled fingerprint; and recognizing the fingerprint of the first user based on a result of the comparison operation.

Abstract: At least some example embodiments disclose a method and apparatus for facial recognition. The facial recognition method includes detecting initial landmarks from a facial image, first normalizing the facial image using the initial landmarks, updating a position of at least one of intermediate landmarks based on the first normalizing, the intermediate landmarks being landmarks transformed from the initial landmarks through the first normalizing, second normalizing the facial image after the updating and recognizing a face using a feature of the second normalized facial image.

Abstract: A fingerprint recognition-based control method may include acquiring, by a fingerprint sensor, sensor data in response to a contact between a physical object and a sensing area of the fingerprint sensor; receiving an input through a first input receiver from among one or more input receivers, the first input receiver being located in a vicinity of the fingerprint sensor; verifying the sensor data to be an input fingerprint; and sensing a motion of the physical object based on the acquired sensor data and the received input, in response to a positive result of the verifying.

Abstract: A method of preprocessing an image including biological information is disclosed, in which an image preprocessor may set an edge line in an input image including biological information, calculate an energy value corresponding to the edge line, and adaptively crop the input image based on the energy value.

Abstract: A device and method of recognizing an iris is provided. An iris recognition device may determine a threshold brightness using a histogram of a reference area from an iris image and exclude a target pixel from iris recognition in a candidate area based on the determined threshold brightness.

Abstract: An authentication method and corresponding apparatus includes obtaining iris images, and constituting an enroll set including iris codes and mask codes corresponding to the iris images. The authentication method and corresponding apparatus also include generating a synthesized code including a synthesized iris code and a synthesized mask code based on correlations between the iris codes included in the enroll set in block units.

Abstract: A fingerprint recognition method includes receiving an input partial image corresponding to a partial image of a fingerprint of a first user; partitioning the input partial image into a plurality of blocks; performing a comparison operation based on the plurality of blocks and the enrolled partial images corresponding to partial images of an enrolled fingerprint; and recognizing the fingerprint of the first user based on a result of the comparison operation.

Abstract: Disclosed is a user recognition apparatus and method, the apparatus configured to determine a validity of an iris area for each frame, to perform an iris recognition when the iris area is valid, and to extract a facial feature for a fusion recognition when the iris area is invalid.

Abstract: A method and apparatus for extracting an iris region is disclosed. The apparatus may generate a classification map associated with an iris region from an eye image using a trained neural network model, estimate a geometric parameter associated with the iris region using the generated classification map, and extract the iris region from the eye image based on the estimated geometric parameter.

Abstract: At least one example embodiment discloses a method of converting a vector corresponding to an input image. The method includes receiving first-dimensional vector data associated with an input image, the input image including an object and converting the received first-dimensional vector data to second-dimensional vector data based on a projection matrix with an associated rank. A first dimension of the first-dimensional vector data is higher than a second dimension of the second-dimensional vector data.