• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.931-946
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• 2017

The purpose of this study is to observe and analyze soil moisture conditions with high resolution and to evaluate its application feasibility to agriculture. For this purpose, we used three Landsat-8 OLI (Operational Land Imager)/TIRS (Thermal Infrared Sensor) optical and thermal infrared satellite images taken from May to June 2015, 2016, and 2017, including the rural areas of Jeollabuk-do, where 46% of agricultural areas are located. The soil moisture conditions at each date in the study area can be effectively obtained through the SPI (Standardized Precipitation Index)3 drought index, and each image has near normal, moderately wet, and moderately dry soil moisture conditions. The temperature vegetation dryness index (TVDI) was calculated to observe the soil moisture status from the Landsat-8 OLI/TIRS images with different soil moisture conditions and to compare and analyze the soil moisture conditions obtained from the SPI3 drought index. TVDI is estimated from the relationship between LST (Land Surface Temperature) and NDVI (Normalized Difference Vegetation Index) calculated from Landsat-8 OLI/TIRS satellite images. The maximum/minimum values of LST according to NDVI are extracted from the distribution of pixels in the feature space of LST-NDVI, and the Dry/Wet edges of LST according to NDVI can be determined by linear regression analysis. The TVDI value is obtained by calculating the ratio of the LST value between the two edges. We classified the relative soil moisture conditions from the TVDI values into five stages: very wet, wet, normal, dry, and very dry and compared to the soil moisture conditions obtained from SPI3. Due to the rice-planing season from May to June, 62% of the whole images were classified as wet and very wet due to paddy field areas which are the largest proportions in the image. Also, the pixels classified as normal were analyzed because of the influence of the field area in the image. The TVDI classification results for the whole image roughly corresponded to the SPI3 soil moisture condition, but they did not correspond to the subdivision results which are very dry, wet, and very wet. In addition, after extracting and classifying agricultural areas of paddy field and field, the paddy field area did not correspond to the SPI3 drought index in the very dry, normal and very wet classification results, and the field area did not correspond to the SPI3 drought index in the normal classification. This is considered to be a problem in Dry/Wet edge estimation due to outlier such as extremely dry bare soil and very wet paddy field area, water, cloud and mountain topography effects (shadow). However, in the agricultural area, especially the field area, in May to June, it was possible to effectively observe the soil moisture conditions as a subdivision. It is expected that the application of this method will be possible by observing the temporal and spatial changes of the soil moisture status in the agricultural area using the optical satellite with high spatial resolution and forecasting the agricultural production.

• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.21-29
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• 2016

Cell segmentation is an important but time-consuming and laborious task in biological image analysis. An automated, robust, and fast method is required to overcome such burdensome processes. These needs are, however, challenging due to various cell shapes, intensity, and incomplete boundaries. A precise cell segmentation will allow to making a pathological diagnosis of tissue samples. A vast body of literature exists on cell segmentation in microscopy images [1]. The majority of existing work is based on input images and predefined feature models only - for example, using a deformable model to extract edge boundaries in the image. Only a handful of recent methods employ data-driven approaches, such as supervised learning. In this paper, we propose a novel data-driven cell segmentation algorithm for bright-field microscopy images. The proposed method minimizes an energy formula defined by two dictionaries - one is for input images and the other is for their manual segmentation results - and a common sparse code, which aims to find the pixel-level classification by deploying the learned dictionaries on new images. In contrast to deformable models, we do not need to know a prior knowledge of objects. We also employed convolutional sparse coding and Alternating Direction of Multiplier Method (ADMM) for fast dictionary learning and energy minimization. Unlike an existing method [1], our method trains both dictionaries concurrently, and is implemented using the GPU device for faster performance.

• Cartoon and Animation Studies
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• s.33
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• pp.503-529
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• 2013

The commemorative AR postage stamps which are the world first presented at The YEOSU EXPO 2012 has had meaning of communicating with future in this present from a convergence that the most analog medium is using now and that the AR is cutting edge of digital technology. The AR stamps printed 10 kind out of 33 commemorative stamps. These have great significance that is artistic value than that is world first. The applied AR images are not only expressed 3D real images but also artic represented and signifying each stamp images from visualized creativity process, and build 'new art space' that is new concept between on real(analog) and virtual(digital). This study analyzes meaning of images and then makes concept of AR contents design. The processing is designed and considered the meaning of architectures and environments, and the regional specific feature of the Yeosu with surrealistic graphic concept. The 10 of deducted images were expressed after AR coding such as visual arts. This study realized markerless 3D image tracking AR stamps and deducted research result are; the first, it was able to figure out how to realize AR in the process of registering the reference images, coordinating transformation, and hybriding AR on the stamps for the mobile devices. The second, it was able to be seeked a possibility of new virtual exhibition space. The third, it was able to know possibility of satisfaction of immersing with visual formativeness and usability with informativity.

• Archives of design research
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• v.13
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• pp.45-53
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• 1996

After the callapse of the 80's bubble economy. consumers tend to consider the fundamental values of a product such as price, usage, and quality more significantly than ever before. Due to this change in attitude. the most important factor in a consumer's decision for choosing a product becomes the quality of a product that safisfies consumer's practical values whith convincing features and logical differentiations devoted to fundamental values. Under the circumstances. Factor Oriented Process and Multi-Sequential Process are proposede not just as merely defining concept through study of consumers' needs. but as methods of gaining competitive edge and eatablishing corporate identity in market, competition by bringing out consumers' various wants and needs to lead them to a specific product. Factor Oriented Process emphasizes the analysis of factors within the process itself, especially the synthesis of factors which would bring about new solutions as its special feature and acts as a logical element for further design development. Thus, the synthesis process consists of re-organizing analyzed factors, andduring this process, analyzing correlation between the restrictions of factors would lead to discovery of 'dominant factors'. Afterward, design basis may be formed with design concepts proposed by several concept codes made up of one dominant factor and other associate factors. Multi-Sequential Process is an extensive approach to discover differentiated design proposals through careful examination of dominant factors within the product, and furthermor, to discount 'anterior factor' (directional factors that decide design directions based on multi-value criteria) for self-determined decision of design directions.

• Journal of Internet Computing and Services
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• v.4 no.3
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• pp.57-67
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• 2003

Software product lines are to attain the rapid development of qualify applications by concretizing the general components populated in software assets and assembling them according to the predefined architectures. For supporting the construction of the software product lines, this paper proposes a component code generation techniques based on GenVoca architecture and XML/XSLT technologies, In addition, CompGenX(Component Generator using XML), a component code generation system, is proposed on the basis of this techniques. By providing reconfigurability of component at the time of code generation, CompGenX allows the reusers to create the component source code that is appropriate to their purpose, In this system, the process of the component development is divided into two tasks which are the component family construction task and the component reuse task, For the component family construction, CompGenX provides the feature modeling tool for domain analysis and the domain architecture definition tool. Also, it provides the tool for building the component configuration know1edge specification and the code templates, For the component reuse task, it offers the component family search tool. the component customizing tool and the component code generator. Component code generation techniques and system in this paper should be applicable as basic technology to build the component-based software product lines.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.2
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• pp.111-119
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• 2013

It is essential and fundamental to extract boundary information of target object via massive three-dimensional point data acquired from laser scanner. Especially extracting boundary information of manmade features such as buildings is quite important because building is one of the major components consisting complex contemporary urban area, and has artificially defined shape. In this research, extended ${\chi}$-algorithm using geometry information of point data was proposed to extract boundary information of building from three-dimensional point data consisting building. The proposed algorithm begins with composing Delaunay triangulation process for given points and removes edges satisfying specific conditions process. Additionally, to make whole boundary extraction process efficient, we used Sweep-hull algorithm for constructing Delaunay triangulation. To verify the performance of the proposed extended ${\chi}$-algorithm, we compared the proposed algorithm with Encasing Polygon Generating Algorithm and ${\alpha}$-Shape Algorithm, which had been researched in the area of feature extraction. Further, the extracted boundary information from the proposed algorithm was analysed against manually digitized building boundary in order to test accuracy of the result of extracting boundary. The experimental results showed that extended ${\chi}$-algorithm proposed in this research proved to improve the speed of extracting boundary information compared to the existing algorithm with a higher accuracy for detecting boundary information.

• Journal of KIISE:Software and Applications
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• v.35 no.11
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• pp.671-680
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• 2008

Motion capture devices have been utilized in producing several contents, such as movies and video games. However, since motion capture devices are expensive and inconvenient to use, motions segmented from captured data was recycled and synthesized to utilize it in another contents, but the motions were generally segmented by contents producers in manual. Therefore, automatic motion segmentation is recently getting a lot of attentions. Previous approaches are divided into on-line and off-line, where ow line approaches segment motions based on similarities between neighboring frames and off-line approaches segment motions by capturing the global characteristics in feature space. In this paper, we propose a graph-based high-level motion segmentation method. Since high-level motions consist of repeated frames within temporal distances, we consider similarities between neighboring frames as well as all similarities among all frames within the temporal distance. This is achieved by constructing a graph, where each vertex represents a frame and the edges between the frames are weighted by their similarity. Then, normalized cuts algorithm is used to partition the constructed graph into several sub-graphs by globally finding minimum cuts. In the experiments, the results using the proposed method showed better performance than PCA-based method in on-line and GMM-based method in off-line, as the proposed method globally segment motions from the graph constructed based similarities between neighboring frames as well as similarities among all frames within temporal distances.

• Journal of Broadcast Engineering
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• v.14 no.6
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• pp.661-675
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• 2009

The carelessly and illegally copied contents are raising serious social problem as internet and multimedia technologies are advancing. Therefore, development of video copy detection system must be settled without delay. In this paper, we propose the hierarchical video copy detection method that estimates similarity using statistical characteristics between original video and manipulated(transformed) copy video. We rank according to luminance value of video to be robust to spacial transformation, and choose similar videos categorized as candidate segments in huge amount of database to reduce processing time and complexity. The copy videos generally insert black area in the edge of the image, so we remove rig black area and decide copy or not by using statistical characteristics of original video and copied video with center part of frame that contains important information of video. Experiment results show that the proposed method has similar keyframe accuracy to reference method, but we use less memory to save feature information than reference's, because the number of keyframes is less 61% than that of reference's. Also, the proposed method detects if the video is copied or not efficiently despite expansive spatial transformations such as blurring, contrast change, zoom in, zoom out, aspect ratio change, and caption insertion.

• Journal of KIISE:Software and Applications
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• v.27 no.7
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• pp.731-741
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• 2000

This paper proposes a method to detect a facial region and extract facial features which is crucial for visual recognition of human faces. In this paper, we extract the MER(Minimum Enclosing Rectangle) of a face and facial components using projection analysis on both edge image and binary image. We use an active contour model(snakes) for extraction of the contours of eye, mouth, eyebrow, and face in order to reflect the individual differences of facial shapes and converge quickly. The determination of initial contour is very important for the performance of snakes. Particularly, we detect Minimum Enclosing Rectangle(MER) of facial components and then determine initial contours using general shape of facial components within the boundary of the obtained MER. We obtained experimental results to show that MER extraction of the eye, mouth, and face was performed successfully. But in the case of images with bright eyebrow, MER extraction of eyebrow was performed poorly. We obtained good contour extraction with the individual differences of facial shapes. Particularly, in the eye contour extraction, we combined edges by first order derivative operator and zero crossings by second order derivative operator in designing energy function of snakes, and we achieved good eye contours. For the face contour extraction, we used both edges and grey level intensity of pixels in designing of energy function. Good face contours were extracted as well.

• Archives of design research
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• v.15 no.1
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• pp.59-67
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• 2002

In accordance with the fast changing circumstance, universities are now reaching, beyond the education place of simple delivery of knowledge and exchange of information, to a place of developing a specialty program related with the region and industry to achieve a competitive edge in education. Through these academic-industrial collaboration program, special knowledge and human resources in the university are utilized in the society and it may contribute to the development of industry and breed of career people based upon the real job site can be achieved. In addition, through the practical operation of such developed program, university may contribute to the enhancement of the competitiveness of the corporation to the activation and acceleration of the regional economy and finally to the enhancement of competitiveness of national industry in international level. This study tries to develop 3 technical instruction and support program related with the legion and industry which may conform to the ideals of university and its goal of education and can provide a platform for the education that is closely related with the regional industry and real job site iud may cope actively with the upcoming knowledge society and fast changing regional circumstances. This study will make research and analyze needs of design support from the industry in order to develop a academic-industrial cooperative design support program for the furniture industry which conforms to the regional characteristic and feature and develop and present contents of program in three area of development of furniture design technology, build-up of furniture design information system and establishment of order based education system. The proposed program is supposed to be operated practically and effectively and contribute to the development of new product, to enhancement of company image and finally to the maximization of corporate profit. Also this study is epected to be used as an important material for establishment of order-based education system which confirms to the job site needs that may be analysed from feedback of product results and for practical learning.