Abstract: Provided is a gesture recognition apparatus. The gesture recognition apparatus includes a human detection unit, a gesture region setting region, an arm detection unit and a gesture determination unit. The human detection unit detects a face region of a user from an input image. The gesture region setting unit sets a gesture region, in which a gesture of the user's arm occurs, with respect to the detected face region. The arm detection unit detects an arm region of the user in the gesture region. The gesture determination unit analyzes a position, moving directionality and shape information of the arm region in the gesture region to determine a target gesture of the user. Such a gesture recognition apparatus may be used as a useful means for a human-robot interaction in a long distance where a robot has difficulty in recognizing a user's voice.

Abstract: A user recognizing system and method is provided. According to the user recognizing system and method, user ID and predetermined user feature information are stored, first and second user feature information are extracted from the user image data transmitted from the image input unit, and first and second probabilities that the extracted first and second user feature information determine the predetermined user are respectively generated based on the information stored at the user information database, the first user feature information being absolutely unique biometric information and the second user feature information being unique semibiometric information under a predetermined condition, and ID of the input image is finally determined by combining the first probability and the second probability. According to the user recognizing system and method, a user identity can be authenticated even when the user freely moves.

Abstract: A system and method for verifying the face of a user using a light mask are provided. The system includes a facial feature extraction unit for extracting a facial feature vector from a facial image received from a camera. A non-user Gaussian Mixture Model (GMM) configuration unit generates a non-user GMM from a facial image stored in a non-user database (DB). A user GMM configuration unit generates a user GMM by applying light masks to a facial image stored in a user DB. A log-likelihood value calculation unit inputs the facial feature vector both to the non-user GMM and to the user GMM, thus calculating log-likelihood values. A user verification unit compares the calculated log-likelihood values with a predetermined threshold, thus verifying whether the received facial image is a facial image of the user.

Abstract: A speaker recognition method and apparatus are provided. In the speaker recognition method, basic data and voice data of a speaker are received using contents that constantly request the speaker to constantly response using the speaker's voice. Then, a voice of the speaker is extracted from voice data, and a feature vector for recognition is extracted from the voice of the speaker. Based on the extracted feature vector, a speaker model is created. Then, a speaker stored in a speaker model is recognized based on information analyzed from input voice.

Abstract: A method and apparatus for recognizing a gesture in an image processing system. In the apparatus, an input unit receives an image obtained by capturing a gesture of a user using a camera. A detector detects a face area in the input image, and detects a hand area in gesture search areas. The gesture search areas being set by dividing the image into predetermined areas with reference to a predetermined location of the detected face area. A controller sets the gesture search areas, determines whether a gesture occurs in the detected hand area, and selects a detection area with respect to the gesture to generate a control command for controlling an image device. A calculator calculates skin-color information and differential-area information for checking a gesture in the detected hand area. Accordingly, a hand area can be accurately detected, and a gesture can be separated from peripheral movement information, so that mal-functioning caused by gesture recognition can be reduced.

Abstract: Disclosed is a method of segmenting handwritten touching numeral strings having a non-vertical segmentation line.

Abstract: A user recognizing system and method is provided. According to the user recognizing system and method, user ID and predetermined user feature information are stored, first and second user feature information are extracted from the user image data transmitted from the image input unit, and first and second probabilities that the extracted first and second user feature information determine the predetermined user are respectively generated based on the information stored at the user information database, the first user feature information being absolutely unique biometric information and the second user feature information being unique semibiometric information under a predetermined condition, and ID of the input image is finally determined by combining the first probability and the second probability. According to the user recognizing system and method, a user identity can be authenticated even when the user freely moves.

Abstract: Disclosed is a method of segmenting touching numeral strings contained in handwritten touching numeral strings, and recognizing the numeral strings by use of feature information and recognized results provided by inherent structure of digits.

Abstract: Disclosed is a method of segmenting handwritten touching numeral strings having a non-vertical segmentation line.

Abstract: A method for analyzing structure of a treatise type of document image in order to detect a title, an author and an abstract region and recognize the content in each of the regions is provided. In order to analyze the structure of a treatise type of document, first, the document image divided into a number of regions and the divided regions are classified into text regions and non-text regions according to attributes of the regions. And then, the candidate regions representing an abstract and an introduction is selected, thereafter word regions are extracted from the candidate regions, and an abstract content portion is determined. Thereafter, the title and the author are separated by using the basic form and the type definition representing an arrangement of each of journals. Finally, the content of the separated regions is recognized to generate said table of contents.

Abstract: Disclosed is a method for recognizing multi-language printed documents, a method for extracting character features according to the present invention, the method comprising the steps of: a) normalizing characters to a fixed size; b) converting the size-fixed characters into mesh-type characters; c) extracting stroke features of each of the mesh-type characters; d) extracting non-stroke features of each of the mesh-type characters; and e) extracting the character features using the stroke features and the non-stroke features. The present invention provides a high recognition rate irrespective of the size and modification of the characters, by extracting the character feature from the stroke and non-stroke in the mesh block.

Abstract: Disclosed is a method of segmenting touching numeral strings contained in handwritten touching numeral strings, and recognizing the numeral strings by use of feature information and recognized results provided by inherent structure of digits.

Abstract: A method for region analysis of a document image applied to region analysis system of a document image, the method includes the steps of: a) analyzing a connected component though a reduced documentimage; b) classifying the connected component by generating a tree according to analysis result of the connected component; c) grouping text components from the classified connected component according to a spatial connection; and d) refining a text block by repeating segmentation and merge of the connected component after the grouping.