• 한국컴퓨터정보학회논문지
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• 제21권9호
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• pp.11-18
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• 2016

In this paper, we propose a gas classification method using combined features for an electronic nose system that performs well even when some loss occurs in measuring data samples. We first divide the entire measurement for a data sample into three local sections, which are the stabilization, exposure, and purge; local features are then extracted from each section. Based on the discrimination analysis, measurements of the discriminative information amounts are taken. Subsequently, the local features that have a large amount of discriminative information are chosen to compose the combined features together with the global features that extracted from the entire measurement section of the data sample. The experimental results show that the combined features by the proposed method gives better classification performance for a variety of volatile organic compound data than the other feature types, especially when there is data loss.

• 말소리와 음성과학
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• 제8권4호
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• pp.103-113
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• 2016

This paper aims to propose articulatory features as novel predictors for automatic pronunciation assessment of English produced by Korean learners. Based on the distinctive feature theory, where phonemes are represented as a set of articulatory/phonetic properties, we propose articulatory Goodness-Of-Pronunciation(aGOP) features in terms of the corresponding articulatory attributes, such as nasal, sonorant, anterior, etc. An English speech corpus spoken by Korean learners is used in the assessment modeling. In our system, learners' speech is forced aligned and recognized by using the acoustic and pronunciation models derived from the WSJ corpus (native North American speech) and the CMU pronouncing dictionary, respectively. In order to compute aGOP features, articulatory models are trained for the corresponding articulatory attributes. In addition to the proposed features, various features which are divided into four categories such as RATE, SEGMENT, SILENCE, and GOP are applied as a baseline. In order to enhance the assessment modeling performance and investigate the weights of the salient features, relevant features are extracted by using Best Subset Selection(BSS). The results show that the proposed model using aGOP features outperform the baseline. In addition, analysis of relevant features extracted by BSS reveals that the selected aGOP features represent the salient variations of Korean learners of English. The results are expected to be effective for automatic pronunciation error detection, as well.

• 전기학회논문지
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• 제58권5호
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• pp.1025-1034
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• 2009

In steel making production line, steel slabs are given a unique identification number. This identification number, Slab management number(SMN), gives information about the use of the slab. Identification of SMN has been done by humans for several years, but this is expensive and not accurate and it has been a heavy burden on the workers. Consequently, to improve efficiency, automatic recognition system is desirable. Generally, a recognition system consists of text localization, text extraction, character segmentation, and character recognition. For exact SMN identification, all the stage of the recognition system must be successful. In particular, the text localization is great important stage and difficult to process. However, because of many text-like patterns in a complex background and high fuzziness between the slab and background, directly extracting text region is difficult to process. If the slab region including SMN can be detected precisely, text localization algorithm will be able to be developed on the more simple method and the processing time of the overall recognition system will be reduced. This paper describes about the slab region localization using SIFT(Scale Invariant Feature Transform) features in the image. First, SIFT algorithm is applied the captured background and slab image, then features of two images are matched by Nearest Neighbor(NN) algorithm. However, correct matching rate can be low when two images are matched. Thus, to remove incorrect match between the features of two images, geometric locations of the matched two feature points are used. Finally, search rectangle method is performed in correct matching features, and then the top boundary and side boundaries of the slab region are determined. For this processes, we can reduce search region for extraction of SMN from the slab image. Most cases, to extract text region, search region is heuristically fixed [1][2]. However, the proposed algorithm is more analytic than other algorithms, because the search region is not fixed and the slab region is searched in the whole image. Experimental results show that the proposed algorithm has a good performance.

• 한국산학기술학회논문지
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• 제8권4호
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• pp.952-960
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• 2007

현재의 대부분의 웹사이트에서는 본인확인을 위한 로그인 절차를 수행하고 있다. 그러나 아이디와 패스워드와 같은 간단한 특징은 도용의 우려가 많아서 본인 확인의 신뢰를 할 수 없다. 이 때문에 청소년들은 타인의 아이디와 패스워드를 가지고 불법매체 사이트를 쉽게 접근할 수 있다. 그래서 본 논문에서는 사용자 인증 시스템을 설계할 때, 적용 가능한 특징들을 알아보고, 이를 바탕으로 인증 시스템 설계를 제안한다. 인증 시스템은 저 수준 인증 방법과 고수준 인증 방법으로 나누었다. 저 수준 인증 방법은 핸드폰을 통한 인증번호 부여 방법과 요즘 많이 쓰이고 있는 공인 인증서를 이용하는 방법이다. 고수준 인증 방법은 아이디와 패스워드를 지문 인식, 문자 인식, 음성 인식, 영상 인식에서의 특징들과 결합하여 인증하는 방법이다. 이를 위해서 본 논문에서 알아본 특징은 지문인식, 얼굴인식, 홍채인식, 문자인식, 정맥인식, 음성인식에 사용 가능한 특징들이다. 이 특징들 중, 지문 인식, 문자 인식, 음성 인식, 영상인식은 보편화된 개인용 컴퓨터에 저가의 장비만 있으면 인증 시스템을 구현할 수 있다. 이러한 다중특징을 이용하여 웹사이트를 구축하면 본인 확인에 대한 신뢰도를 한층 높일 수 있다.

• 대한원격탐사학회지
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• 제22권3호
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• pp.221-228
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• 2006

In this study, an integrated 3D modeling and rendering system dealing with 3D urban landscape features such as terrain, building, road and user-defined geometric ones was designed and implemented using $OPENGL\;{|}\;ES$ (Embedded System) API for mobile devices of PDA. In this system, the authoring functions are composed of several parts handling urban landscape features: vertex-based geometry modeling, editing and manipulating 3D landscape objects, generating geometrically complex type features with attributes for 3D objects, and texture mapping of complex types using image library. It is a kind of feature-based system, linked with 3D geo-based spatial feature attributes. As for the rendering process, some functions are provided: optimizing of integrated multiple 3D landscape objects, and rendering of texture-mapped 3D landscape objects. By the active-synchronized process among desktop system, OPENGL-based 3D visualization system, and mobile system, it is possible to transfer and disseminate 3D feature models through both systems. In this mobile 3D urban processing system, the main graphical user interface and core components is implemented under EVC 4.0 MFC and tested at PDA running on windows mobile and Pocket Pc. It is expected that the mobile 3D geo-spatial information systems supporting registration, modeling, and rendering functions can be effectively utilized for real time 3D urban planning and 3D mobile mapping on the site.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1857-1862
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• 2016

Human activity recognition using depth information is an emerging and challenging technology in computer vision due to its considerable attention by many practical applications such as smart home/office system, personal health care and 3D video games. This paper presents a novel framework of 3D human body detection, tracking and recognition from depth video sequences using spatiotemporal features and modified HMM. To detect human silhouette, raw depth data is examined to extract human silhouette by considering spatial continuity and constraints of human motion information. While, frame differentiation is used to track human movements. Features extraction mechanism consists of spatial depth shape features and temporal joints features are used to improve classification performance. Both of these features are fused together to recognize different activities using the modified hidden Markov model (M-HMM). The proposed approach is evaluated on two challenging depth video datasets. Moreover, our system has significant abilities to handle subject's body parts rotation and body parts missing which provide major contributions in human activity recognition.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.940-943
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• 1996

In teleoperating, as seeing the monitor screen obtained from a camera instituted in the working environment, human operator generally controls the slave arm. Because we can see only 2-D image in a monitor, human operator does not know the depth information and can not work with high accuracy. In this paper, we proposed a traded control method using an visual sensor for the purpose of solving this problem. We can control a teleoperation system with precision when we use the proposed algorithm. Not only a human operator command but also an autonomous visual sensor feedback command is given to a slave arm for the purpose of coincidence current image features and target image features. When the slave arm place in a distant place from the target position, human operator can know very well the difference between the desired image features and the current image features, but calculated visual sensor command have big errors. And when the slave arm is near the target position, the state of affairs is changed conversely. With this visual sensor feedback, human does not need coincide the detail difference between the desired image features and the current image features and proposed method can work with higher accuracy than other method without, sensor feedback. The effectiveness of the proposed control method is verified through series of experiments.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제14권3호
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• pp.336-340
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• 2008

최근 감정 분류에 대한 관심이 높아져 연구가 활발히 진행되고 있다. 문서 전체에 관한 감정의 분류도 중요하지만, 문서를 이루고 있는 문장에 관한 분류도 점차 그 필요성이 높아지고 있다. 본 논문에서는 한국어 감정 분류 시스템 구축을 위해서 추출된 한국어 감정 자질을 이용한 한국어 문장 및 문서 감정 분류에 관해 연구한다. 한국어 감정 분류의 시작은 감정을 내포한 대표적인 어휘로부터 시작하며, 이와 같은 감정 자질들은 문장 및 문서의 감정을 분류하는데 결정적인 관여를 한다. 한국어 감정 자질의 추출을 위하여 영어 단어 시소러스 정보를 이용하여 자질들을 확장하고, 영한사전을 통해 확장된 자질들을 번역함으로써 감정 자질들을 추출하였다. 추출된 감정 자질들을 사용하여, 단어 벡터로 표현된 입력문서를 이진 분류기인 지지벡터 기계(SVM: Support Vector Machine)를 이용하여 문장과 문서에 내포된 감정을 판단하고 평가하였다.

• 한국산업정보학회논문지
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• 제6권1호
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• pp.33-38
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• 2001

본 논문에서는 영상의 형태 특징을 이용한 영상 검색 시스템을 제안한다. 형태특징을 얻기 위해서 먼저 체인코드를 이용하여 경계선 추출을 추출하였다. 형태특징으로 객체의 경계선과 무게중심까지의 합, 표준편차 그리고 객체의 장축과 단축 비율 등을 추출하였다. 이러한 형태특징 정보를 이용하여 데이터 베이스에 저장된 영상과 질의 영상을 비교하여 유사도 순위에 따라 후보 영상들을 검색하였다. 본 실험의 결과 크기, 회전 이동 등의 변화에 둔감하였다. 약 170개의 폐곡선을 이루는 영상에 대한 검색 실험을 통하여 모양 정보에 대한 정확도를 측정하였다. 실험 결과 평균 Recall/Precision이 0.72/0.83를 보임으로써 제안된 방법이 유용함을 보였다.

• 한국멀티미디어학회논문지
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• 제10권9호
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• pp.1220-1228
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• 2007

본 논문에서는 기존의 서명 비교방법인 픽셀비교 (point-to-point) 방식과 부분비교(segment-to-segment) 방식의 단점을 보완한 효율적인 온라인 서명 인증 방법을 제안한다. 기존의 연구에서는 각각의 비교 방식에 알맞은 특징들이 추출되어서 서명 인증 시스템이 구현되어 왔었다. 본 논문에서는 두 비교방식의 장점을 결합하였다. 제안된 기법은 서명의 제적방향이 변화되는 지점인 변곡점을 이용해서 서명을 비교하고, 학습을 통하여 진서명간의 유사도는 높이고 진서명과 위조서명간의 상이도를 높이는 필자고유특징을 찾아낸다. 본 논문에서 제안된 방식을 사용한 경우, 필자고유특징을 사용하지 않는 경우와 비교해서 서명 인증율이 96.33%로 향상되었다.