• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
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• pp.33-36
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• 2000

To create a more realistic soccer game derived from TV images, we are developing an image synthesis system that generates 3D image sequence from TV images. We propose the method for the team and the pose recognition of players in TV images. The representation includes camera calibration method, team recognition method and pose recognition method. To find the location of a player on the field, a field model is constructed and a player's field position is transformed by 4-feature points. To recognize the team information of players, we compute RGB mean values and standard deviations of a player in TV images. Finally, to recognize pose of a player, this system computes the velocity and the ratio of player(height/width). Experimental results are included to evaluate the performance of the team and the pose recognition.

• Journal of information and communication convergence engineering
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• 제9권2호
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• pp.207-211
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• 2011

This paper presents a method for facial feature representation and recognition from the Covariance Matrices of the Gabor-filtered images. Gabor filters are a very powerful tool for processing images that respond to different local orientations and wave numbers around points of interest, especially on the local features on the face. This is a very unique attribute needed to extract special features around the facial components like eyebrows, eyes, mouth and nose. The Covariance matrices computed on Gabor filtered faces are adopted as the feature representation for face recognition. Geodesic distance measure is used as a matching measure and is preferred for its global consistency over other methods. Geodesic measure takes into consideration the position of the data points in addition to the geometric structure of given face images. The proposed method is invariant and robust under rotation, pose, or boundary distortion. Tests run on random images and also on publicly available JAFFE and FRAV3D face recognition databases provide impressively high percentage of recognition.

• 반도체디스플레이기술학회지
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• 제12권1호
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• pp.1-7
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• 2013

Grey-level statistical models have been widely used in many applications for object location and identification. However, conventional models yield some problems in model refinement when training images are not properly aligned, and have difficulties for real-time recognition of arbitrarily rotated models. This paper presents improved grey-level statistical models that align training images using image or feature matching to overcome problems in model refinement of conventional models, and that enable real-time recognition of arbitrarily rotated objects using efficient hierarchical search methods. Edges or features extracted from a mean training image are used for accurate alignment of models in the search image. On the aligned position and orientation, fitness measure based on grey-level statistical models is computed for object recognition. It is demonstrated in various experiments in PCB inspection that proposed methods are superior to conventional methods in recognition accuracy and speed.

• The Journal of Korean Physical Therapy
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• 제23권2호
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• pp.77-84
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• 2011

Purpose: This study was designed to investigate the level of recognition and utilization of Korean physical therapists for assistive technology. Methods: The subjects of this study were 218 physical therapists who worked in various institutions in Seoul, Kyonggi-do, and Choongchung area. A questionnaire was developed using a related article. Simple descriptive statistics were used for respondent characteristics, and for the level of recognition and utilization. Results: The physical therapists reported having a less-than-average level of recognition and utilization for assistive technology. They were cognizant that the use of assistive technology devices were used mainly for specific outcome such as mobility, seating and position, and ADL. Conclusion: Our findings indicate that physical therapists need more opportunities for training in assistive technology. For effective clinical applications of assistive technology, there should be continuous support, such as college education, continued education, and related seminars.

• 전자공학회논문지B
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• 제30B권6호
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• pp.76-85
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• 1993

In this paper, we propose a stroke matching method for the off-line recognition of handprinted Hangul. In this method, the preprocessing steps such as position normalization, contour tracing and thinning are carried out first. Then, after extracting features such as the firection component distribution of contour, the direction component distribution of skeleton, and the distribution of structural feature points, strokes are extracted and matched based on the midpont distribution of the direction and the length of each stroke. In order to reduce the recognition time, a preliminary classification based on the direction component distribution features of the contour is performed. In order to domonstrate the performance of the proposed method, experiments with 520 most frequently used Hangul were performed, and 90.7% of correct recognition rate and 0.46second of recognition time per one character has been obtained. This results reveal that the proposed method can absorb effectively the noise in input character and the variations of stroke slant.

• 한국멀티미디어학회논문지
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• 제16권4호
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• pp.430-443
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• 2013

운전자에게 차량의 현재 위치 및 도로 주변 상황 인지는 안전하고 쾌적한 운전 환경 조성을 위해 반드시 필요한 정보들이다. 본 논문에서는 도로시설물 및 도로표지 등의 도로정보를 모니터링 하고 시각적으로 알리기 위해 도로주행영상 내 좌표정보 결합 및 시점변환 기법을 이용한 도로주행환경 자동인식 기술을 제안한다. 제안한 방법은 차량 내 탑재된 카메라와 GPS를 이용하여 공간정보가 반영된 도로주행영상을 생성한 후, 생성 영상의 시점 변환 및 정합, 도로정보 검출을 수행하여 사용자에게 도로정보를 시각적으로 제공할 수 있도록 한다. 제안한 방법을 도로 주행 영상에서 실험한 결과, 도로주행영상 내 GPS 좌표정보의 결합 시간은 66.5ms, 교통 표지판 검출율은 95.83%, 프레임당 표지판 검출 처리 시간은 평균 227.45ms 이었다. 따라서 15프레임/초 이하의 입력 동영상에 대하여 효과적으로 도로주행환경을 자동으로 인식하는 것이 가능함을 확인하였다.

• 한국통신학회논문지
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• 제40권1호
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• pp.226-232
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• 2015

스마트기기 시대가 도래함에 따라, 최근 스마폰과 관련한 많은 응용 서비스들이 개발되고 있으며, LBS(Location Based Service) 기술은 위치 기반 서비스를 제공하기 위해 가장 중요한 기술 중의 하나로 인식되고 있다. 일반적으로 스마트폰의 위치인식은 GPS(Global Positioning System), G-Sensor와 같은 위치 인식 시스템 및 센서를 이용하여 위치 정보를 획득하게 된다. 그러나 실내에서는 위성으로부터의 GPS 신호를 수신하기가 거의 불가능하므로 실내 환경을 위한 새로운 LBS 기술이 필요하다. 본 논문에서는 이러한 문제를 해결하기 위해 LED 조명과 스마트폰의 카메라 센서를 이용한 위치정보 송수신기를 제안한다. 제안 위치 인식 시스템의 실용성 검증을 위해 실험실 환경에서의 실험을 통해 그 가능성을 입증하였다.

• Journal of Information Processing Systems
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• 제20권4호
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• pp.491-500
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• 2024

In hopes of resolving the issue of poor quality of information input for teaching spoken English online, the study creates an English teaching assistance model based on a recognition algorithm named dynamic time warping (DTW) and relies on automated voice recognition technology. In hopes of improving the algorithm's efficiency, the study modifies the speech signal's time-domain properties during the pre-processing stage and enhances the algorithm's performance in terms of computational effort and storage space. Finally, a simulation experiment is employed to evaluate the model application's efficacy. The study's revised DTW model, which achieves recognition rates of above 95% for all phonetic symbols and tops the list for cloudy consonant recognition with rates of 98.5%, 98.8%, and 98.7% throughout the three tests, respectively, is demonstrated by the study's findings. The enhanced model for DTW voice recognition also presents higher efficiency and requires less time for training and testing. The DTW model's KS value, which is the highest among the models analyzed in the KS value analysis, is 0.63. Among the comparative models, the model also presents the lowest curve position for both test functions. This shows that the upgraded DTW model features superior voice recognition capabilities, which could significantly improve online English education and lead to better teaching outcomes.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.934-937
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• 2003

In this paper, authors use a stereo vision system based on the visual model of human and establish inexpensive method that recognizes moving distance using characteristic points around the robot. With the stereovision. the changes of the coordinate values of the characteristic points that are fixed around the robot are measured. Self-displacement and self-localization recognition system is proposed from coordination reconstruction with those changes. To evaluate the proposed system, several characteristic points that is made with a LED around the robot and two cheap USB PC cameras are used. The mobile robot measures the coordinate value of each characteristic point at its initial position. After moving, the robot measures the coordinate values of the characteristic points those are set at the initial position. The mobile robot compares the changes of these several coordinate values and converts transformation matrix from these coordinate changes. As a matrix of the amount and the direction of moving displacement of the mobile robot, the obtained transformation matrix represents self-displacement and self-localization by the environment.

• 한국음향학회지
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• 제13권5호
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• pp.24-31
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• 1994

본 논문에서는 단어 조음결합의 음성학적 모델을 이용한 한국어 연속음성 인식에 관해 연구한다. 조음결합 현상에 의한 성능 감소를 줄이기 위해 단어내에서의 전이뿐만 아니라 단어간의 전이를 모델링하는 context-dependent (CD)단위를 사용한다. 모든 경우에서 각 단어의 첫 음소는 앞에 올 수 있는 모든 단어의 마지막 음소에 의해 지정되며, 각 단어의 마지막 음소도 유사한 방법으로 지정된다. Hidden Markov model (HMM) 파라미터들의 강인성을 개선하기 위해 공분산 행렬을 평활화한다. 또한 음성 단위들 사이의 분별력을 높이기 위해 position-dependent 단위를 사용한다. 실험 결과들은 개선된 조음결합 모델을 사용함으로서 intra-word 단위만을 사용하는 기본 인식 시스템에 비해 성능을 상당히 개선할 수 있음을 보여 주었다.