Samsung Electronics Co., Ltd.

Korea Advanced Institute of Science and Technology

University of California

Electronics and Telecommunications Research Institute

Curitel Communications, Inc.

Research & Industrial Cooperation Group

Information and Communications University Educational Foundation

Heinrich-hertz-institut Fur Nachrichtentechnik Berlin Gesellschaft MIT Beschrankter Haftung

Yong-man Ro

Changick Kim

Min-Soo Hahn

Keewon Seo

Jae-young Choi

Yang-lim Choi

Woo-sup Han

Bangalore S Manjunath

Hyun-doo Shin

Seong-Tae Kim

Dokwan Oh

Do-kwan Oh

Woosup Han

Byeong-won Lee

Min-cheol Park

Choong Hwan Choi

Choong-hwan Choi

Seong-ho Chang

Dae-hoe Kim

Yong-Geun Won

Tae-Meon Bae

Mun-churl Kim

Jin-woong Kim

A method of and apparatus for changing lesion classification data, the method including determining whether at least one mass is included in an image of an object, determining whether the at least one mass corresponds to a lesion by using first data including at least one first information, selecting a false negative (FN) mass which has been determined as not corresponding to the lesion among the at least one mass, based on a first input, and changing the first data to second data by using second information of the selected FN mass.

Lesion classification apparatus, and method of modifying lesion classification data

Disclosed is a method for intelligently displaying a sports game video for a multimedia mobile terminal, the method including the steps of: determining if a camera shot existing in the sports game video is a long-shot; when the camera shot is determined as a long-shot, determining a ROI within an image frame of the sports game video; and when the camera shot is determined as a non-long-shot, displaying the image frame on the mobile terminal, and, when the camera shot is determined as a long-shot, enlarging and displaying the ROI on the mobile terminal.

Method for intelligently displaying sports game video for multimedia mobile terminal

An apparatus for estimating a malignant tumor includes: a segmentor configured to segment a first medical image of an object into a first ROI including a mass and a second medical image of the object into a second ROI including a mass; an interest region determiner configured to acquire a first matched ROI and a second matched ROI, which is matched to the first matched ROI based on location information of the first ROI and the second ROI, respectively; a feature extractor configured to extract a similar feature indicating a degree of similarity between the first matched ROI and the second matched ROI, from the first matched ROI and the second matched ROI; and a classifier configured to generate malignant tumor information indicating whether the mass included in the first matched ROI and the second matched ROI is the malignant tumor, based on the extracted similar feature.

Apparatus and method for estimating malignant tumor

Disclosed is a system and method for encryption of a scalable video coding (SVC) bitstream, which is the next-generation coding technology. The encryption method encrypts Network Abstraction Layer (NAL) data identified according to multidimensional scalability for space, time, and quality with respect to a bitstream created after an SVC encoding, thereby providing a multidimensional scalability function for space, time, and quality even after the encryption, so that the scalability is also maintained even in a bitstream extraction process after the encryption. According to such a scalable encryption method, a specific portion of an encrypted bitstream is removed in a bitstream extraction process, and user access to the bitstream is limited based on a combination of keys for accessing a specific scalability. Therefore, it is possible to protect scalable video content and to access the video content based on scalabilities.

Method and system for encryption/decryption of scalable video bitstream for conditional access control based on multidimensional scalability in scalable video coding

A texture description method in a frequency domain for extracting texture features by transforming and Gabor-filtering an input image into an image of the frequency domain, and a texture-based retrieval method thereof are provided. The texture description method in the frequency domain includes: a first step of transforming an image of a time domain into an image of the frequency domain; a second step of filtering the transformed image using a Gabor filter having N&#xd7;M filter regions, where N and M are respective predetermined positive integers; a third step of extracting feature values of the image that has been Gabor-filtered in respective channels of the frequency domain division layout corresponding to the N&#xd7;M filter regions of the Gabor filter; and a fourth step of deciding a texture descriptor of the image on the basis of the feature values of the image.

Texture description method and texture-based image retrieval method using Gabor filter in frequency domain

Growing community of inventors

Daejeon, South Korea

Yong-man Ro