Electronics and Telecommunications Research Institute

Yun Su Chung

Ki Young Moon

Sung Uk Jung

Yongjin Lee

Kyo Il Chung

Jang Hee Yoo

Jang-Hee Yoo

Kil Taek Lim

Hyun Woo Kang

Soo In Lee

Yong Jin Lee

In Soo Kim

Eun Chang Choi

Moon Sung Park

Hyung Keun Jee

Dae Sung Moon

Woo Yong Choi

Kwang Yong Kim

Hye Kyu Kim

So-Hee Park

Song Li

Yong Joon Lee

Yun Won Choi

Su Yong An

Jang Woon Baek

Byung Gil Han

Hea-Min Lee

Mi Seon Kang

Dongyeop Kang

Kyu Bo Cho

Pyong Kun Kim

Byeong Woon Jin

Wookyong Kwon

Kwang Ju Kim

Jin Suk Kim

Byung Jun Kang

Jong Taek Lee

A method and an apparatus for recognition a position and generating a path for autonomous driving of a mobile robot in an orchard environment are provided. The method converts three-dimensional (3D) point cloud data for the orchard environment into a 2D grid map, obtains a position of the mobile robot by performing local scan matching and global scan matching on the 2D grid map, and extracts a tree from the 2D grid map based on occupancy of each grid of the 2D grid map. Then, an effective line based on center points of extracted trees is obtained, a destination based on the obtained effective line is generated, and a driving path according to the generated destination and the position of the mobile robot is generated.

Method and apparatus for autonomous driving of mobile robot in orchard environment

Provided is a method of separating a foreground and a background by extracting a depth image through a stereo camera, generating an occupancy grid map on the basis of the depth image, predicting a free space, and computing a membership value, the method including setting a threshold value of a foreground object existing in a free space boundary region of the predicted free space, determining whether the membership value reaches the threshold value of the foreground object while the membership value is computed, terminating the computing of the membership value when it is determined that the membership value being computed reaches the threshold value of the foreground object in the determining, and separating a foreground and a background through the computed membership value.

Method and apparatus for accelerating foreground and background separation in object detection using stereo camera

Provided is a technology for recognizing vehicle license plate information which includes detecting a position of a license plate from a vehicle image obtained by imaging a vehicle, extracting individual character images by separating a plurality of characters from a region of the detected license plate in the vehicle image and extracting a license plate type of the license plate according to a predetermined criterion, recognizing a license plate character string on the basis of the extracted individual character images and the license plate type and outputting the recognized license plate character string.

System and method for recognizing vehicle license plate information

Provided is an electrical system including an intelligent learning terminal to analyze biometric information associated with a user and calculate an intensity of electrical stimulation for the user based on a result of the analyzing, and at least one wireless electrical stimulator to provide electrical stimulation to the user based on the calculated intensity of electrical stimulation, wherein the intelligent learning terminal is connected to the at least one wireless electrical stimulator based on wired or wireless communication.

Electrical stimulation system and control method of electrical stimulation system

A method and apparatus for detecting and recognizing an object using a vector histogram based on a local binary pattern are disclosed. The apparatus of detecting and recognizing an object using a local binary pattern includes: a feature map creator configured to extract an object area in which a moving object exists from an input image, to create a local binary pattern by designating a local area in the object area, and to create a vector component map including information about magnitude vector components and direction vector components using the local binary pattern; a feature map configuring unit configured to divide the object area into a plurality of blocks and to create a feature vector map through a histogram using the vector component map in a unit of the block; and an object detector configured to detect and classify the moving object based on the feature vector map.

Method and apparatus for detecting and recognizing object using local binary patterns

A method for detecting a forged face using an infrared image includes: acquiring an infrared image and a photorealistic image captured by one or two cameras; extracting a face region from the photorealistic image; determining, based on analysis of quality characteristics of the infrared image, whether a current face is a forged face or not; and performing face recognition on the extracted face region if it is determined that the current face is a non-forged face. The method further includes capturing an infrared image and a photorealistic image again through the camera without performing face recognition if it is determined that the current face is a forged face.

Method and apparatus for detecting forged face using infrared image

A forged face detecting method includes: acquiring a photorealistic image and an infrared image of a subject on which line beams are projected; extracting face features from the infrared image based on characteristics of a pattern of the line beams projected on the acquired infrared image; and detecting whether or not the infrared image is a forged face based on the extracted face features. Said detecting whether or not the infrared image is a forged face includes: checking whether the extracted face features falls within a preset permission range of face features; determining the infrared image to have the forged face if the extracted face features fall out of the range to acquire an infrared image of the subject again; and determining the infrared image to have a non-forged face if the extracted face features falls within the range to perform face recognition for the photorealistic image.

Forged face detecting method and apparatus thereof

A biometric register includes: a feature extraction unit for performing preprocessing for a fingerprint to extract a feature point m for the fingerprint; a transformation function generation unit for generating a transformation function which is composed of an arbitrary rotation matrix and an arbitrary vector; and a template generation unit for transforming a coordinate of the feature point m using the generated transformation function, and organizing a fuzzy vault using a randomly generated fake feature point and a feature point mapplied by the transformed coordinate, thereby generating a one-time template.

Apparatus and method for biometric registration and authentication

A method of detecting a facial image includes pre-processing an image; and detecting a face region from the pre-processed image to create facial records of the detected face region. Further, the method of detecting the facial image includes detecting the facial image by creating coordinates of the face and eyes in the input image by using the facial records.

Apparatus and method for detecting facial image

Provided is a biometric authentication method. A biometric authentication method in accordance with an aspect of the present invention includes generating a first one-time authentication template from biometric information using one-time transform information, and requesting authentication, comparing the first one-time authentication template with a one-time registration template, updating the one-time registration template and the one-time transform information when authentication is achieved according to a result of the comparison, wherein the updated one-time transform information is used to generate a second one-time authentication template to be authenticated according to the result of the comparison with the updated one-time registration template when successive authentication is requested.

Biometric authentication method

Provided a secure pattern recognition method. The method includes: receiving data and generating a probe by converting the received data into a template for pattern recognition; accessing a gallery that is a template registered and stored in advance; determining a region to which the probe belongs and obtaining the center point of the region; obtaining a hash value of the center point and coordinate of the probe; and determining whether or not the hash value of the center point and a hash value stored in the gallery are equal and determining whether or not the probe and the gallery are classified into the same class by calculating whether or not the coordinate of the probe is inside a decision boundary configured with thresholds on the basis of the coordinates of the center point.

Pattern recognition method and apparatus for data protection

Provided are a method and an apparatus for accurately detecting positions of eyes in an input face image. The method includes extracting a symmetric face region from a face image based on magnitude and phase of gradient in each pixel of the face image; detecting available eye positions based on brightness information of the extracted face region; verifying regions around each of the detected eye positions with a classifier which determines whether an input image is an eye image using information obtained by supervised learning on sample images. According to the present invention, faulty eye detection is prevented by removing obscuring elements such as illumination, glasses and hair from an input face image. Also, eye coordinates can be extracted more accurately using an eye classifier.

Method and apparatus for detecting eyes in face region

A face recognition and apparatus are provided. According to the method, an SVM classifier is created through machine learning on the basis of a degree of similarity of a divided facial image, and a facial image to be authenticated is normalized to a predetermined size using a center between two eyes. The normalized image is divided into more than one image in horizontal and vertical directions, respectively. Next, predetermined characteristic vectors from the divided images are extracted and a similarity vector based on a degree of similarity with respect to a registered characteristic vector is created. The similarity vector is input to the SVM classifier, so that authentication is performed.

Face recognition by dividing an image and evaluating a similarity vector with a support vector machine

Provided are a method and apparatus of detecting an eye using symmetrical and moment characteristics of an object. According to the method, an eye band is extracted from a facial image, and eye candidates each having symmetry are detected by extracting symmetrical component from the eye band. After that, a moment line integral is calculated on the basis of contrast of the eye band image and a coordinate of each of the eye candidates is inputted, so that each of the detected eye candidates is verified.

Method and apparatus of detecting eye using symmetry and moment characteristics of object

In a system for identifying an object having a bar code symbology, a measurement and input unit measure a height and a length of the object and input the measured values into the system. An object image and search region image storage unit stores an image of the object and images of at least two sub blocks from the object. A search region setting unit sets a size of the sub blocks. A region of interest (ROI) generation unit sets a weight and a characteristic value of the sub block. A bar code symbology identification unit searches vertically a bar code region from the ROI and generates a bar code edge region. An information interpretation unit interprets object information corresponding to the bar code edge region. A result process and storage unit processes and stores the interpreted object information.

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Daejeon, South Korea

Yun Su Chung