• 한국실내디자인학회논문집
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• 제17권6호
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• pp.178-187
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• 2008

This study aims to analyze general features and forms of spatial structure of major space in museums and for the scope of this study, set up major space and the surrounding areas structured around major space and for the target of analysis, selected 10 museums of overseas examples from 19th century to 2006. And this study on focus, on the circulation structure and visual structure will be analyzed in qualitative method by focusing on the floor plan and section structures; deepening process of analysis, visual structure will turn into numerical value to analyze the spatial structure of the major space. The results of this study are as follow. First, vertical elements should be critically considered in a circulation plan for functional performance of dimensional circulation distribution in a major space. Second, a plan by location of vertical and horizontal moving elements related to a major space affects a circulation relation more than a connection type between a major space and an exhibition area. Third, it could be categorized into 4 types by considering the features of spatial structure followed by connecting relationship between areas. Fourth, comparable figures were drawn out among large space and surrounding areas but it couldn't draw out types.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2004년도 추계 종합학술대회 논문집
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• pp.251-256
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• 2004

본 논문은 레스터 기반 위성영상에서 공간정보를 추출하기 위한 공간 관계 연산 방법과 예를 보인다. 복잡하고 다양한 현실 세계를 지리 정보 시스템은 추상화하고 단순화한 형상을 기반으로 구축한다. 추상화된 지형지물은 지리 객체와 지리필드로 구체화한다. 지리객체와 지리필드는 각각 벡터와 레스터로 표현한다. 레스터 자료형 위성영상은 원격탐사 응용에 이용한다. 원격탐사 공간 정보 추출을 위하여 위상 연산과 기하연산을 한다. 레스터형인 위성영상을 유연성이 뛰어난 벡터화된 객체로 변환하고 이로부터 공간 정보를 추출한다. 원격탐사에 위성영상의 활용이 증가하고 있으며, GIS와 접목함으로써 위성영상 활용의 극대화에 기여 할 것이다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권10호
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• pp.3390-3405
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• 2022

Long Short-Term Memory (LSTM) combined with attention mechanism is extensively used to generate semantic sentences of images in image captioning models. However, features of salient regions and spatial information are not utilized sufficiently in most related works. Meanwhile, the LSTM also suffers from the problem of underutilized information in a single time step. In the paper, two innovative approaches are proposed to solve these problems. First, the Synergy-Gated Attention (SGA) method is proposed, which can process the spatial features and the salient region features of given images simultaneously. SGA establishes a gated mechanism through the global features to guide the interaction of information between these two features. Then, the Recurrent Fusion LSTM (RF-LSTM) mechanism is proposed, which can predict the next hidden vectors in one time step and improve linguistic coherence by fusing future information. Experimental results on the benchmark dataset of MSCOCO show that compared with the state-of-the-art methods, the proposed method can improve the performance of image captioning model, and achieve competitive performance on multiple evaluation indicators.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.321-324
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• 2005

In these days, the management and visualization of 3D geo-spatial information is regarded as one of an important issue in GiS and remote sensing fields. 3D GIS is considered with the database issues such as handling and managing of 3D geometry/topology attributes, whereas 3D visualization is basically concerned with 3D computer graphics. This study focused on the design and implementation for the OpenGL API-based rendering system for the complex types of 3D geo-spatial features. In this approach 3D features can be separately processed with the functions of authoring and manipulation of terrain segments, building segments, road segments, and other geo-based things with texture mapping. Using this implementation, it is possible to the generation of an integrated scene with these complex types of 3D features. This integrated rendering system based on the feature-based 3D-GIS model can be extended and effectively applied to urban environment analysis, 3D virtual simulation and fly-by navigation in urban planning. Furthermore, we expect that 3D-GIS visualization application based on OpenGL API can be easily extended into a real-time mobile 3D-GIS system, soon after the release of OpenGLIES which stands for OpenGL for embedded system, though this topic is beyond the scope of this implementation.

• 반도체디스플레이기술학회지
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• 제13권2호
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• pp.45-52
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• 2014

This paper proposes an efficient photo retrieval system that automatically indexes for searching of relevant images, using a combination of geo-coded information, direction/location of image capture device and content-based visual features. A photo image is labeled with its GPS (Global Positioning System) coordinates and direction of the camera view at the moment of capture, and the label leads to generate a geo-spatial index with three core elements of latitude, longitude and viewing direction. Then, content-based visual features are extracted and combined with the geo-spatial information, for indexing and retrieving the photo images. For user's querying process, the proposed method adopts two steps as a progressive approach, filtering the relevant subset prior to use a content-based ranking function. To evaluate the performance of the proposed scheme, we assess the simulation performance in terms of average precision and F-score, using a natural photo collection. Comparing the proposed approach to retrieve using only visual features, an improvement of 20.8% was observed. The experimental results show that the proposed method exhibited a significant enhancement of around 7.2% in retrieval effectiveness, compared to previous work. These results reveal that a combination of context and content analysis is markedly more efficient and meaningful that using only visual feature for image search.

• 정보보호학회논문지
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• 제31권6호
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• pp.1171-1179
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• 2021

본 논문에서는 저품질 이미지에 적용된 미디언 필터링를 검출하는 기법을 제안하고자 한다. 이러한 미디언 필터링검출은 이미지 포렌식 기법에 사용되고 있는 것으로 제안된 방법에서는 원본 이미지와 미디언 필터링된 이미지를 구분하기 위하여 공간 영역에서 통계적 특징 정보를 추출하고 확장시킨다. 확장된 특징 정보는 마르코프 모델을 사용하고 강인한 특징 집합을 생성하기 위하여 다중 방향 배열을 사용한다. 제안된 방법에서는 검출 정확도를 높이기 위하여 텍스처 연산자를 사용하고 SVM 분류기를 통하여 분류 모델을 훈련시킨다. 실험 결과에서는 JPEG 압축을 사용한 저품질 이미지에서 제안한 방법의 우수함을 보인다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2078-2093
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• 2019

Visual smoke recognition is a challenging task due to large variations in shape, texture and color of smoke. To improve performance, we propose a novel smoke recognition method by combining dual-encoded features that are extracted from both spatial and Curvelet domains. A Curvelet transform is used to filter an image to generate fifty sub-images of Curvelet coefficients. Then we extract Local Binary Pattern (LBP) maps from these coefficient maps and aggregate histograms of these LBP maps to produce a histogram map. Afterwards, we encode the histogram map again to generate Dual-encoded Local Binary Patterns (Dual-LBP). Histograms of Dual-LBPs from Curvelet domain and Completed Local Binary Patterns (CLBP) from spatial domain are concatenated to form the feature for smoke recognition. Finally, we adopt Gaussian Kernel Optimization (GKO) algorithm to search the optimal kernel parameters of Support Vector Machine (SVM) for further improvement of classification accuracy. Experimental results demonstrate that our method can extract effective and reasonable features of smoke images, and achieve good classification accuracy.

• 한국실내디자인학회논문집
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• 제25권4호
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• pp.80-89
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• 2016

The analysis of spatial search direction and its concentration through eye movement can produce some useful data in that it enables to know the features of space elements and their effects on one another. The results by analysing the search features and concentration of spatial sections through the eye-tracking in shops in a department store makes it possible to define the followings. First, the features of 'eye's in & out' could be estimated through the division of sections by the characteristics of those shops and the extraction of central point based on the decision of continuative observation. The decision of continuative observations enabled to analyse the frequency of observation data which can be considered to be 'things watched longtime' and the stared points that is equivalent to 'things seen very often', by which the searching characteristics of spatial sections could be estimated. Second, as with the eye's [in], the right shops had 0.6 times more (3.5%) than those left and as with the eye's [out] the left ones had 0.6 times more (3.5%). It indicates that [in, out] of the right and the left shops had the same difference, which lets us know that with starting point of the middle space, [in] and [out] were paid more attention to the right shops and the left shops respectively. Third, as with the searching directions by section, the searching times [2.9 times] from [B] to [A] were than that [2.6 times] from [A] to [B]. It was also found that the left shops had more searching direction toward [C, D] than the right ones and that those searching activities at the left shops were more active. Fourth, when the searching directions by section are reviewed, the frequency of searching from [B] to [A] was 2.9 and that of the other way 2.6. Also the left shops were found to have more searching direction toward [C, D] than the right ones and those searching activities at the left shops were estimated to be more active.

• 한국통신학회논문지
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• 제35권11C호
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• pp.929-939
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• 2010

멀티미디어 기술이 발전함에 따라 대용량의 데이터베이스의 관리와 불법 복제물 검출을 위한 동영상 검색의 필요성이 커지고 있다. 본 논문에서는 이러한 요구에 맞춰 대용량 데이터베이스에서 고속 동영상 검색을 수행할 수 있는 방법을 제안한다. 고속 동영상 검색 방법은 프레임의 휘도 분포를 이용하여 공간적 특징을 추출하고, 동영상의 시간적 유사성 지도를 생성하여 시간적 특정을 추출한다. 동영상의 공간적 특정과 시간적 특정을 식별자로 구성하고 단계적인 정합 방법을 수행한다. 실험에서는 원본 동영상과 밝기 변화, 압축률 변환, 자막/로고 삽입과 같은 다양한 변형을 이용하여 정확성, 추출 및 정합 속도, 식별자 크기를 측정하여 성능을 평가하였다. 또한, 제안한 방법의 파라미터를 실험적으로 선택한 과정을 기술하고 비교 알고리즘과 공간적 특정만을 이용한 단순 정합 결과를 제시하였다. 정확성, 경색 속도 식별자 크기의 모든 결과에서, 제안한 고속 검색 방법이 대용량 데이터베이스의 동영상 경색에 가장 적합한 기술임을 보였다.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제5권5호
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• pp.628-638
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• 1999

본 논문에서는 색상-공간 특징을 사용하여 24bpp RGB 칼라 이미지를 검색하는 방법을 제안한다. 각 이미지는 RGB 색상공간에서 인지적 균등 색상공간인 CIE L*u*v* 색상공간으로의 변환을 거친 후 색상 유사도를 사용하여 여러 개의 영역으로 나누어진다. 크기가 작은 영역은 무시할 수 있으며, 큰 영역은 공간 특징을 추출하기 어려우므로, 영역 분할 시 영역의 크기에 제약을 가하였다. 분할 된 각 영역의 평균 색상과 중점을 색상-공간 특징으로 추출하게 된다. 검색 과정에서는 질의의 색상-공간 특징과 데이타베이스 이미지의 색상-공간 유사도를 검사하여 검색하게 된다. 사용자 그래픽 질의와 예제 이미지에 의한 검색이 가능한 내용기반 이미지 검색 시스템을 구현하였다. 실험한 결과 Recall/Precision이 0.80/0.84였다.