Abstract:
An apparatus and method for recognizing characters of an image captured using a camera in a mobile terminal are provided, wherein an image of a signboard is captured, a text area is extracted from the captured image of the signboard, characters are recognized from the extracted text area, similar characters up to a predetermined priority level are generated for each recognized character of the extracted text area, location information of an area within a predetermined range from a current position of a user is acquired, store names are extracted from the location information, text is generated by combining the similar characters according to weights, the text are compared with the extracted store names, and a comparison result is output.
Abstract:
Disclosed are a user input device and a method for rapidly selecting an operation mode in a mobile terminal having a touch screen input panel and a fingerprint recognition sensor. The user input method includes setting operation modes for at least one fingerprint data and input pattern, each comprised of keys necessary to implement a corresponding operation mode; detecting fingerprint data inputted from the fingerprint recognition sensor, and confirming an operation mode set for the inputted fingerprint data; and displaying an input pattern corresponding to the confirmed operation mode on the touch screen input panel.
Abstract:
A method and apparatus for performing microphone beamforming. The method includes recognizing a speech of a speaker, searching for a previously stored image associated with the speaker, searching for the speaker through a camera based on the image, recognizing a position of the speaker, and performing microphone beamforming according to the position of the speaker.
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:
Disclosed are an apparatus and a method for beamforming in consideration of characteristics of an actual noise environment. The apparatus includes a microphone array having at least microphone, the microphone array outputting a signal input through the microphone; a coherence function generation unit for calculating coherences for input signals according to each space between microphones, calculating averages of the coherences for the same distance, and filtering the calculated averages of the coherences and outputting the resultant values, when an input signal is input; a spatial filter factor calculation unit for calculating and outputting a spatial filter factor by using the filtered average coherences; and a beamforming execution unit for performing a beamforming for the input signals by using the spatial filter factor, thereby outputting a noise-processed signal.
Abstract:
Disclosed is an audio/video data synchronization apparatus for directly transmitting decoded audio/video data to an external device, without compressing the data, using UWB communication. The apparatus synchronizes video and audio data stored in a terminal without compressing the data and simultaneously transmits the data to an external device using UWB communication, so that users can enjoy high-quality images and sounds. In addition, the receiving end does not necessarily incorporate a separate function for decoding moving images, because it receives uncompressed video/audio data. This makes the apparatus simple and convenient.
Abstract:
A terminal with a keypad enables a user to input an alphabet character through the keypad at high speed without modification of the keypad. The terminal comprises receiving a first input character in an alphabet input mode; waiting for a key input for at least one second input character succeeding the first input character; upon receiving a key input for the second input character, searching for a priority table in which a displaying order of a succeeding alphabet character is designated; and controlling a displaying order of the second input character according to the priority table.
Abstract:
An apparatus and a method for managing a spam number in a mobile communication terminal are provided. The method includes determining a spam index for each of at least one phone number using a reception record by phone number, and determining spam number registration or non-registration for each phone number depending on the spam index.
Abstract:
Disclosed herein is a process of producing high purity and high yield dimethylnaphthalene by dehydrogenating a dimethyltetralin isomer using a metal catalyst for dehydrogenation. The metal catalyst contains a carrier selected from alumina (Al2O3), silica (SiO2), a silica-alumina mixture and zeolite. The metal catalyst also contains 0.05 to 2.5% by weight of platinum (Pt), 0.1 to 3.0% by weight of tin (Sn) or indium (In), 0.5 to 15.0% by weight of at least one selected from the group consisting of potassium (K), magnesium (Mg) and cesium (Cs), 0.3 to 3.0% by weight of chlorine, and 0.01 to 3.0 % by weight of zinc (Zn) or gallium (Ga) as active components based on an element weight of the final catalyst.
Abstract:
A face recognition system based on adaptive learning includes a specific person detection and tracking unit for detecting and tracking a specific person from a moving image. A facial feature extraction unit extracts a plurality of facial feature vectors from the detected and tracked specific person. A face recognition unit searches for a given registration model by comparing the extracted facial feature vectors with facial feature vectors of the registration models previously stored in a user registration model database. A learning target selection unit selects a facial feature vector to be added to a record of the given registration model from among the extracted facial feature vectors. A registration model learning unit adds and updates the selected facial feature vector to the record of the given registration model.