• 정보기술과데이타베이스저널
• /
• 제6권2호
• /
• pp.19-28
• /
• 1999

Digital image and video libraries require new algorithms for the automated extraction and indexing of salient image features. Eigen values of an image provide one important cue for the discrimination of image content. In this paper we propose a new approach for automated content extraction that allows efficient database searching using eigen values. The algorithm automatically extracts eigen values from the image matrix represented by the covariance matrix for the image. We demonstrate that the eigen values representing shape information and the skewness of its distribution representing complexity provide good performance in image query response time while providing effective discriminability. We present the eigen value extraction and indexing techniques. We test the proposed algorithm of searching by eigen value and its skewness on a database of 100 images.

• 방송공학회논문지
• /
• 제7권3호
• /
• pp.262-270
• /
• 2002

대부분의 영상색인 기법에서는 영상의 전역 특징값을 이용한다. 그러나 이러한 방법은 영상의 지역적인 변화들을 담아내지 못하기 때문에 만족할 만한 격과를 제공하지 못한다. 본 논문에서는 이러한 문제점을 해결하기 위한 방법으로 영상의 특징점(salient point)과 영상분할을 이용하여 중요영역(important region)을 추출하는 새로운 영역기반 영상검색 시스템을 제안한다. 본 논문에서 제안하는 특징점 추출 기법은 기존의 방법과 비교하여 빠르고 정확한 추출 결과를 보여준다. 선택된 영역에서 추출된 칼라와 질감 정보를 이용하여 검색한 결과는 칼라나 질감 정보의 전력 특징값을 이용한 검색 방법의 결과보다 크게 향상됨을 알 수 있었다.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
• /
• 제14권1호
• /
• pp.81-94
• /
• 2003

목 적：발달성 읽기 장애는 정상적인 읽기 능력의 현저한 발달 저하나 지속적인 오류를 보이는 질환이며, 학령기 아동의 $3{\sim}7$%에서 관찰된다. 기존에 사용되는 기초학습기능검사의 단점을 보완하고 발달성 읽기 장애의 진단과 평가를 위해 단어/비단어 읽기 검사와 글자기호감별검사의 신뢰도와 타당도를 검증하였다. 방 법：DSM-IV의 진단 기준과 임상적인 판단에 근거하여 읽기 장애 아동 63명(평균 연령 10.48세)과 정상 아동 77명(평균 연령 10.33세)을 대상으로 하였다. 이들에게 기초학습기능검사의 읽기 I과 II목을 실시하였고, 단어/비단어 읽기 검사와 글자기호감별검사를 시행하였다. 단어/비단어 읽기 검사는 각 100문항씩의 익숙한 단어와 의미를 갖지 않는 생소한 비단어를 각각 1.2초와 2.4초안에 읽도록 하여, 이를 통해 자동화된 음운 처리 능력과 의식적인 글자-음소 처리 능력을 평가하였다. 글자기호감별검사를 통해 읽기 장애 환자들이 오류를 일으키는 거울상 반전 글자들의 조합을 판별하는 능력을 검사하였다. 이들 검사의 내적 일치도 등의 신뢰도 검사와 공존타당도, 구성타당도, 판별타당도 등을 검증하였다. 결 과：단어/비단어 읽기 검사는 내적 일치도가 0.96으로서 신뢰할 수 있고, 기초학습기능검사와 0.94의 공존타당도를 나타내었으며, 단어와 비단어 모두 발달성 읽기 장애와 정상 아동을 통계적으로 구분할 수 있었고, 판별 분석에서 원집단에 속한 83.0%를 정확하게 판별할 수 있었다. 글자기호감별검사는 내적 일치도가 0.86으로서 신뢰할 수 있고, 기초학습기능검사와 0.86의 공존타당도를 나타내었으며, 요인 분석 결과 안구 운동 거울상 처리, 전반적 정확성, 거울상 반전 오류, 정지상 처리, 전반적 기민성 부족, 부주의-충동성 등의 여섯 요인으로 구성되어 있었다. 글자기호감별검사의 각 항목 별로 발달성 읽기 장애와 정상 아동을 통계적으로 구분할 수 있었으며, 판별분석에서 원집단에 속한 대상의 87.3%를 정확하게 판별할 수 있었다. 결 론：발달성 읽기 장애 아동은 읽기 과정의 자동적인 시각-의미 연결 기전과 의식적인 형태소-음소 상응 규칙 적용 능력 모두에서 장애를 보였으며, 거울상 반전 오류 등 시각적 정보 처리 기능의 장애도 나타내었다. 이들 장애는 단어/비단어 읽기 검사와 글자기호감별검사를 통해 신뢰할 수 있고 타당성 있게 구분하고 평가할 수 있었다.

• 한국의류학회지
• /
• 제21권8호
• /
• pp.1297-1306
• /
• 1997

The purpose of this study was to investigate the difference of visual evaluation about combination of contrary clothing image, Elegance-Casual, Ethnic-Modern. The data were collected using 23 semantic differential hi-polar scale questionnaires from 50 female students majoring in clothing and textile and analyzed by Factor analysis, ANOVA, Discriminant analysis and MDS. The results obtained were summarized as follows; 1. As a result of factor analysis, 4 factors -Attractiveness, Casualness, Moderateness, Modernness-were found out as constructing factors of contrary clothing image. 2. For the visual evaluation of contrary clothing image combined with top and bottom, there were significant differences in all factors. 3. As a result of discriminant analysis, discrimination among images was more closely related to renovated image by combination of contrary clothing image. 4. As a result of MDS, evaluative dimensions of contrary clothing image were identified, and relationship between clothing images and special qualities of design was shown on positioning map.

• Journal of applied mathematics & informatics
• /
• 제9권2호
• /
• pp.793-806
• /
• 2002

Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the highspeed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Maps (SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space. The mapping preserves the topology of the feature vectors. The map is called topological feature map. A topological feature map preserves the mutual relations (similarity) in feature spaces of input data. and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. In topological feature map, there are empty nodes in which no image is classified. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
• /
• pp.127-132
• /
• 2000

Though the increment of using computer vision system, there are lots of difficulties to measure precisely because of measurement error or distortion phenomenon. Among these reasons, the distortion of edge is dominant reason which is occurred by the blurred image. So, the problem of clear judgment about image focal point is very important. We must fix the discrimination criteria which is collected by image recognition of precise focus. To solve these problems, we compare with make processing methods using image intensity gradient, laplacian, and sum -modified laplacian operator. These experimental results showed modified mask processing method is effective.

• 한국생산제조학회지
• /
• 제7권3호
• /
• pp.126-131
• /
• 1998

In computer vision system of modern industry precise measuring has lots of dfficulties because of measurement error due to distortion phenomenon. Among the difficulties, the distortion of edge is regraded as a dominent problem. which is caused by the vlurred image. The blurred image apperar when camera can not discriminate its precise focus. So. it is very important to decide focus of lens and to develop algorithm in order to correct distortion phenomenon. Thus. discrimination criteria obtained by image information of precise focus must be fixed in advance. The gray level histogram of image acquired from blurred edge tends to show a uniform distribution. Bimodal intensity histogram is related with condition of focus, and it is possible to find good condition of focus by using bimodal histogram of entropy.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 1996년도 춘계학술대회 논문집
• /
• pp.52-55
• /
• 1996

Though the increment of using computer vision system in modern industry, there are lots of difficulties to measure precisely because of measurement error distortion phenomenon. Between these reasons, the distortion of edge is dominant reason which is occured by the blurred image. The blurred image is happened when camera can not discriminate its precise focus. To correct and generalize distortion phenomenon is imprrtant. Thus we must fix the discrimination criteria which is collected by image recognition of precise focus. The edge of image means discontinuous point of intensity, and the component of edge is discribed as high frequency component at special domain specturm of image. The good condition of focus means there are much high frequency energy in image. The method of discribing high frequency energy is gradient operater which determines the condition of focus.

• 한국의류학회지
• /
• 제26권7호
• /
• pp.970-981
• /
• 2002

The purpose of the study is to clarify orange image in the modern fashion. So kinds of costume sample being visual power in orange have been selected from photographs in fashion magazines and divided into the tones : mist(Vp, Lgr, L), bright(P, B), vivid(S, V, Dp). The study was measured by using 27 semantic differential hi-polar scales. The subjects were 50 female students majoring in clothing and textiles, The data was analyzed using the statistical SPSS package. The data were collected using self-administred questionnaires and analyzed by Cronbach $\alpha$, Factor analysis, MDS, ANOVA Sheff test and Regression analysis. The major findings of this research were as follows. 1. Factor analysis has extracted 4 factors of orange image in the fashion. These factor are Attractiveness, Audacity, Hardness and Softness, Cuteness. 2. There were significant difference in visual evaluation of tones. 3. The discrimination among tones was related to cuteness and weight of orange. 4. The image effect on Preference, Buying needs, Pleasant and Riches was consist of complicated sensibility.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
• /
• pp.485-487
• /
• 2003

Independent Component Analysis (ICA) is used to generate ICA filter for computing feature vector for image window. Filters that have high discrimination power are selected to classify image from these ICA filters. Proposed classification algorithm is based on probability distribution of feature vector.