Kim, Sung-Jin;Chung, Chin-Wan;Lee, Seok-Lyong;Kim, Deok-Hwan
Journal of KIISE:Databases
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v.36
no.6
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pp.434-445
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2009
Content-based image retrieval(CBIR) is the retrieval technique which uses the contents of images. However, in contrast to text data, multimedia data are ambiguous and there is a big difference between system's low-level representation and human's high-level concept. So it doesn't always mean that near points in the vector space are similar to user. We call this the semantic-gap problem. Due to this problem, performance of image retrieval is not good. To solve this problem, the relevance feedback(RF) which uses user's feedback information is used. But existing RF doesn't consider user's region-of-interest(ROI), and therefore, irrelevant regions are used in computing new query points. Because the system doesn't know user's ROI, RF is proceeded in the image-level. We propose a new ROI RF method which guides a user to select ROI from relevant images for the retrieval of complex satellite image, and this improves the accuracy of the image retrieval by computing more accurate query points in this paper. Also we propose a pruning technique which improves the accuracy of the image retrieval by using images not selected by the user in this paper. Experiments show the efficiency of the proposed ROI RF and the pruning technique.
For coronary procedures, X-ray angiogram images are useful for diagnosing and assisting procedures. It is challenging to accurately segment a coronary artery using only a single segmentation model in 2D X-ray images due to a complex structure of three-dimensional coronary artery, especially from phenomenon of vessels being broken in the middle or end of coronary artery. In order to solve these problems, the initial segmentation is performed using an existing single model, and the candidate regions for the sophisticate correction is estimated based on the initial segment, and the local patch-based correction is performed in the candidate regions. Through this research, not only the broken coronary arteries are re-connected, but also the distal part of coronary artery that is very thin is additionally correctly found. Further, the performance can be much improved by combining the proposed correction method with any existing coronary artery segmentation method. In this paper, the U-net, a fully convolutional network was chosen as a segmentation method and the proposed correction method was combined with U-net to demonstrate a significant improvement in performance through X-ray images from several patients.
There have been many applications to observe Earth using synthetic aperture radar (SAR) since it could acquire Earth observation data without reference to weathers or local times. However researches about digital map generation using SAR have hardly been performed due to complex raw data processing. In this study, we suggested feasibility of producing digital map using SAR stereo images. We collected two sets, which include an ascending and a descending orbit acquisitions respectively, of KOMPSAT-5 stereo dataset. In order to suggest the feasibility of digital map generation from SAR stereo images, we performed 1) rational polynomial coefficient transformation from radar geometry, 2) digital resititution using KOMPSAT-5 stereo images, and 3) validation using digital-map-derived reference points and check points. As the results of two models, root mean squared errors of XY and Z direction were less than 1m for each model. We discussed that KOMPSAT-5 stereo image could generated 1:25,000 digital map which meets a standard of the digital map. The proposed results would contribute to generate and update digital maps for inaccessible areas and wherever weather conditions are unstable such as North Korea or Polar region.
The naturally opened Han river estuary is a place where the flows of the Han river, Imjin river, Yaesung river meet with West Sea of Korea, so the hydrodynamic mechanism(Impact-Response) structure of Han river estuary is complex. Continuous observation and measurement due to the morphological characteristics at the estuary are required to maintain the estuary environment and river management facilities. However, the Sannam wetland(the study area) is in the military operation area. Therefore, Sannam wetland has the limited access under the control from military office. In 2020, there had a natural disaster due to flooding in August and COVID-19, and it made a survey hard. The noncontact survey technique, the analysis of LANDSAT images at Sannam wetland, was applied to analyze riverbed fluctuation and morphological transformation around Sannam wetland. LANDSAT images obtained from EarthExplorer, USGS and analyzed by QGIS. The analysis was performed based on the area and the distance near Sannam wetland. As a result, an erosion was happened on the downstream of the study area, and the upstream of the study area did not have any serious sediment transport. Considering the resolution of LANDSAT images, this noncontect survey technique is applicable to manage the study area. From the analysis of LANDSAT images, it is assumed that the tidal effect is greater than the inflow from the upstream. The pattern change of tidal response causes the damage of the river facilities near the Hangang river estuary.
Magnetic resonance imaging (MRI) is a key technology that has been seeing increasing use in studying the structural and functional innerworkings of the brain. Analyzing the variability of brain connectome through tractography analysis has been used to increase our understanding of disease pathology in humans. However, there lacks standardization of analysis methods for small animals such as mice, and lacks scientific consensus in regard to accurate preprocessing strategies and atlas-based neuroinformatics for images. In addition, it is difficult to acquire high resolution images for mice due to how significantly smaller a mouse brain is compared to that of humans. In this study, we present an Allen Mouse Brain Atlas-based image data analysis pipeline for structural connectivity analysis involving structural region segmentation using mouse brain structural images and diffusion tensor images. Each analysis method enabled the analysis of mouse brain image data using reliable software that has already been verified with human and mouse image data. In addition, the pipeline presented in this study is optimized for users to efficiently process data by organizing functions necessary for mouse tractography among complex analysis processes and various functions.
International conference on construction engineering and project management
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2009.05a
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pp.30-31
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2009
Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.
Journal of the Korean Association of Geographic Information Studies
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v.21
no.1
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pp.35-45
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2018
Image data collected by an airborne hyperspectral camera system have a great usability in coastal line mapping, detection of facilities composed of specific materials, detailed land use analysis, change monitoring and so forh in a complex coastal area because the system provides almost complete spectral and spatial information for each image pixel of tens to hundreds of spectral bands. A few approaches after classifying by a few approaches based on SAM(Spectral Angle Mapper) supervised classification were applied for extracting optimal land cover information from hyperspectral images acquired by CASI-1500 airborne hyperspectral camera on the object of a coastal area which includes both land and sea water areas. We applied three different approaches, that is to say firstly the classification approach of combined land and sea areas, secondly the reclassification approach after decompostion of land and sea areas from classification result of combined land and sea areas, and thirdly the land area-only classification approach using atmospheric correction images and compared classification results and accuracies. Land cover classification was conducted respectively by selecting not only four band images with the same wavelength range as IKONOS, QuickBird, KOMPSAT and GeoEye satelllite images but also eight band images with the same wavelength range as WorldView-2 from 48 band hyperspectral images and then compared with the classification result conducted with all of 48 band images. As a result, the reclassification approach after decompostion of land and sea areas from classification result of combined land and sea areas is more effective than classification approach of combined land and sea areas. It is showed the bigger the number of bands, the higher accuracy and reliability in the reclassification approach referred above. The results of higher spectral resolution showed asphalt or concrete roads was able to be classified more accurately.
Journal of the Institute of Electronics and Information Engineers
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v.53
no.6
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pp.110-121
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2016
The primary aim of the color constancy algorithm is to estimate illuminant chromaticity. There are various statistical-based, learning-based and combinational-based color constancy algorithms already exist. However, the statistical-based algorithms can only perform well on images that satisfy certain assumptions, learning-based methods are complex methods that require proper preprocessing and training data, and combinational-based methods depend on either pre-determined or dynamically varying weights, which are difficult to determine and prone to error. Therefore, this paper presents a new optimization based illuminant estimation method which is free from complex preprocessing and can estimate the illuminant under different environmental conditions. A strong color cast always has an odd standard deviation value in one of the RGB channels. Based on this observation, a cost function called the degree of illuminant tinge(DIT) is proposed to determine the quality of illuminant color-calibrated images. This DIT is formulated in such a way that the image scene under standard illuminant (d65) has lower DIT value compared to the same scene under different illuminant. Here, a swarm intelligence based particle swarm optimizer(PSO) is used to find the optimum illuminant of the given image that minimizes the degree of illuminant tinge. The proposed method is evaluated using real-world datasets and the experimental results validate the effectiveness of the proposed method.
A method and results of computations are presented for the 2-D seismic migration process in the frequency-wavenumber domain for the laterally and vertically inhomogeneous medium. In order to take the intrinsic attenuation effect into account in the migration process the complex-valued wave velocity is used in the wavefield extrapolation operator, improving the generalized frequency-wavenumber migration technique. The imaginary part of the complex-valued wave velocity includes the seismic quality factor Q value. In derivation of the solution of the wave equation for the medium of inhomogeneous wave velocity and anelasticity, the inhomogeneous medium is mathematically converted to an equivalent system which consists of a homogeneous medium of averaged slowness and an inhomogeneous distribution of hypothetical wave source. The strength of the hypothetical wave source depends on the deviation of squared slowness from the averaged value of the medium. Results of numerical computation using the technique show more distinct geologic images than those using the convensional generalized frequency-wavenumber migration. Especially, the obscured images due to the wave attenuation by anelasticity are restored to show sharp boundaries of structures. The method will be useful in the imaging of the reflection data obtained in the regions of possible petroleum or natural gas reservoir and of fractured zone.
Due to the remarkable changes in the early twentieth century, the new invention and technology impacted peoples' everyday lives and people started to use the word, modern, to apply specifically to what pertained to present times and to designate a movement in what was new and not old-fashioned-a condition of newness. In the present day, however, the fantastic cultural changes of a century ago have now become commonplace, and what was once considered radically new is no longer a reason to marvel. This paper considers what it mean to be modern, once the new is no longer new. This question seems to remain as complicated and inappropriate to ponder because the consideration and impact of modernity cannot simply end with the end of an era. This paper investigates how the interconnected nature of popular culture provides apt illustrations to reveal the ambivalent nature of modernity and postmodernity. In doing so, first of all, this paper pays attentions to the notion of modernity and popular culture which emerged together in the early twentieth century when technology and mass consumer culture were promoted over the world. Also, it examines how popular culture represents a complex of mutually-interdependent perspectives and values that influence society and its institutions in various ways as the image of modernity continues to build in a postmodern era. That is, popular culture is identified as a large amount of intertextuality or collective experiences due to its intermingling of complementary distribution sources and techonology. Thus, this paper explores that popular culture devotes itself other images or narratives instead of referring to the real world and its output revisits the contemporary or past times in other places, being a means to produce and reproduce the accumulated images of the modern which shapes ceaseless simulacra of modernity over complexities of modernity. In order to find a critical juncture of the complex networks of modernity and popular culture, this paper considers two places, Chicago and Gyeongsung in the 1920s and 1930s in which the rapid modern experience took place and the modern movement forced the two societies to join the mass consumer culture whether willingly or not. Next, this paper considers two movies released in 2002 and 2008 that exemplify the complexities of modernity in Chicago and Gyeongung of the 1920s and 30s: Chicago and Modern Boy. Both films have common themes of the 1920s and 30s such as violence, adultery, femme fatal, and criminal themes with the forms of musical, dance, drama, and romance. Through the textual analysis of both Chicago and Modern Boy, two films are compared in observing the similar and different ways in which two films deal with the theme of modernity when they are represented from the contemporary perspectives. More specifically, this paper questions how modernity is present in contemporary cultural forms such as commercial and hybrid genre films; and how these movies create a new image of modern by embodying the double coding. Ultimately, this paper aims at realizing the paradox of double edged modernity and its ongoing discourse that controls people's consciousness through the medium of popular culture.
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