• Korean Institute of Interior Design Journal
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• v.17 no.6
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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.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.251-256
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• 2004

This paper will show examples and methods of spatial relationship operations that extract spatial information from satellite images. Geographical information system phenomena of complex and variant real world can abstract and implement simple features. The abstract features classify geo_objects and geo_field. The geo_object and the geo_field can represent vector and raster respectively. The raster based satellite image can use remote sensing applications. This paper needs topology operations and geometric operations for extracting the remote sensing. The spatial information transforms the raster based image to the vector based object, and extract from the spatial information. The extracted information will contribute on the application of the remote sensing satellite images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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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.

• Proceedings of the KSRS Conference
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• 2005.10a
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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.

• Journal of the Semiconductor & Display Technology
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• v.13 no.2
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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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1171-1179
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• 2021

Image forensic is performed to check image limpidness. In this paper, a robust scheme is discussed to detect median filtering in low quality images. Detection of median filtering assists in overall image forensic. Improved spatial statistical features are extracted from the image to classify pristine and median filtered images. Image array data is rescaled to enhance the spatial statistical information. Features are extracted using Markov model on enhanced spatial statistics. Multiple difference arrays are considered in different directions for robust feature set. Further, texture operator features are combined to increase the detection accuracy and SVM binary classifier is applied to train the classification model. Experimental results are promising for images of low quality JPEG compression.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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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.

• Korean Institute of Interior Design Journal
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• v.25 no.4
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11C
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• pp.929-939
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• 2010

The growth of multimedia technology forces the development of video detection for large database management and illegal copy detection. To meet this demand, this paper proposes a fast video detection method to apply to a large database. The fast video detection algorithm uses spatial features using the gray value distribution from frames and temporal features using the temporal similarity map. We form the video signature using the extracted spatial feature and temporal feature, and carry out a stepwise matching method. The performance was evaluated by accuracy, extraction and matching time, and signature size using the original videos and their modified versions such as brightness change, lossy compression, text/logo overlay. We show empirical parameter selection and the experimental results for the simple matching method using only spatial feature and compare the results with existing algorithms. According to the experimental results, the proposed method has good performance in accuracy, processing time, and signature size. Therefore, the proposed fast detection algorithm is suitable for video detection with the large database.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.5
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• pp.628-638
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• 1999

In this paper, we presents a method of retrieving 24 bpp RGB images based on color-spatial features. For each image, it is subdivided into regions by using similarity of color after converting RGB color space to CIE L*u*v* color space that is perceptually uniform. Our segmentation algorithm constrains the size of region because a small region is discardable and a large region is difficult to extract spatial feature. For each region, averaging color and center of region are extracted to construct color-spatial features. During the image retrieval process, the color and spatial features of query are compared with those of the database images using our similarity measure to determine the set of candidate images to be retrieved. We implement a content-based color image retrieval system using the proposed method. The system is able to retrieve images by user graphic or example image query. Experimental results show that Recall/Precision is 0.80/0.84.