• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.2
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• pp.16-24
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• 2002

Classification of the land cover characteristics is a major application of remote sensing. The goal of this study is to propose an optimal classification process for electro-optical camera(EOC) of Korea Multi-Purpose Satellite(KOMPSAT). The study was carried out on Landsat TM, high spectral resolution image and KOMPSAT EOC, high spatial resolution image of Miho river basin, Korea. The study was conducted in two stages: one was image fusion of TM and EOC to gain high spectral and spatial resolution image, the other was land cover classification on fused image. Four fusion techniques were applied and compared for its topographic interpretation such as IHS, HPF, CN and wavelet transform. The fused images were classified by radial basis function neural network(RBF-NN) and artificial neural network(ANN) classification model. The proposed RBF-NN was validated for the study area and the optimal model structure and parameter were respectively identified for different input band combinations. The results of the study propose an optimal classification process of KOMPSAT EOC to improve the thematic mapping and extraction of environmental information.

• Korean Journal of Environment and Ecology
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• v.22 no.3
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• pp.289-300
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• 2008

This study aims to discriminate differences in natural landscapes between the Cairngorms National Park in Scotland and the Jirisan National Park in Korea, using functions of content-based image retrieval such as texture, shape, and color. Digital photographs of each National Park were taken and selected. The low-level functions of photographic images were reduced to orthogonally rotated five factors. Based on the reduced factors, a linear decision boundary was obtained between Cairngorms landscapes and Jirisan landscapes. As a result, the discriminant function significantly delineated two groups, resulting in $x^2=63.40$ with df=5(p<0.001). Both the eigenvalue 2.417 and the value of wilks' lambda 0.29 supported that the most proportion of total variability came from the differences between the means of discriminant function of groups. It was estimated that four independent variables explained about 70.7% of total variance of dependent variable. The variable with the largest effect on landscapes was far region-related factor(r=1.07), followed by near region-related factor (r=0.90). A total of 90.7% of cross-validated grouped cases were correctly classified. It was interpreted that far distant regions, as well as near distant regions, had sufficient discrimination power for landscape classification between the Cairngorms National Park and the Jirisan National Park, so that landscape identity of the National Park over cultures was revealed by skylines in a most effective way. Relatively fewer factors making visual landscapes were effectively used to classify natural landscapes of the National Parks which had different semantics.

• Journal of the Korea Computer Graphics Society
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• v.20 no.3
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• pp.1-8
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• 2014

We propose a method to compose a foreground object into a background image, where the foreground object is a part (or a region) of an image taken by a front-facing camera and the background image is a whole image taken by a back-facing camera in a smart phone at the same time. Recent high-end cell-phones have two cameras and provide users with preview video before taking photos. We extract the foreground object that is moving along with the front-facing camera using the optical flow during the preview. We compose the extracted foreground object into a background image using a simple image composition technique. For better-looking result in the composed image, we apply a border smoothing technique using a weighted-border mask to blend transparency from background to foreground. Since constructing and grouping pixel-level dense optical flow are quite slow even in high-end cell-phones, we compute a mask to extract the foreground object in low-resolution image, which reduces the computational cost greatly. Experimental result shows the effectiveness of our extraction and composition techniques, with much less computational time in extracting the foreground object and better composition quality compared with Poisson image editing technique which is widely used in image composition. The proposed method can improve limitedly the color bleeding artifacts observed in Poisson image editing using weighted-border blending.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.45-54
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• 2006

This paper proposed color matching technique, including display characterization, chromatic adaptation model, and gamut mapping and extension, to generate consistent colors for the same input signal in each display device. It is necessary to characterize the relationship between input and output colors for display device, to apply chromatic adaptation model considering the difference of reference white, and to compensate for the gamut which display devices can represent for reproducing consistent colors on DTV display devices. In this paper, 9 channel-independent GOG model, which is improved from conventional 3 channel GOG(gain, offset gamma) model, is used to consider channel interaction and enhance the modeling accuracy. Then, the input images have to be adjusted to compensate for the limited gamut of each display device. We proposed the gamut mapping and extension method, preserving lightness and hue of an original image and enhancing the saturation of an original image in xy chromaticity diagram. Since the hmm visual system is more sensitive to lightness and hue, these values are maintained as the values of input signal, and the enhancement of saturation is changed to the ratio of input and output gamut. Also the xy chromaticity diagram is effective to reduce the complexity of establishing gamut boundary and the process of reproducing moving-pictures in DTV display devices. As a result, reproducing accurate colors can be implemented when the proposed method is applied to LCD and PDP display devices

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.117-124
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• 2013

In this paper, we present a new method which efficiently estimates a face direction from a sequences of input video images in real time fashion. For this work, the proposed method performs detecting the facial region and major facial features such as both eyes, nose and mouth by using the Haar-like feature, which is relatively not sensitive against light variation, from the detected facial area. Then, it becomes able to track the feature points from every frame using optical flow in real time fashion, and determine the direction of the face based on the feature points tracked. Further, in order to prevent the erroneously recognizing the false positions of the facial features when if the coordinates of the features are lost during the tracking by using optical flow, the proposed method determines the validity of locations of the facial features using the template matching of detected facial features in real time. Depending on the correlation rate of re-considering the detection of the features by the template matching, the face direction estimation process is divided into detecting the facial features again or tracking features while determining the direction of the face. The template matching initially saves the location information of 4 facial features such as the left and right eye, the end of nose and mouse in facial feature detection phase and reevaluated these information when the similarity measure between the stored information and the traced facial information by optical flow is exceed a certain level of threshold by detecting the new facial features from the input image. The proposed approach automatically combines the phase of detecting facial features and the phase of tracking features reciprocally and enables to estimate face pose stably in a real-time fashion. From the experiment, we can prove that the proposed method efficiently estimates face direction.

• Tunnel and Underground Space
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• v.30 no.5
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• pp.462-472
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• 2020

Rock classification is fundamental discipline of exploring geological and geotechnical features in a site, which, however, may not be easy works because of high diversity of rock shape and color according to its origin, geological history and so on. With the great success of convolutional neural networks (CNN) in many different image-based classification tasks, there has been increasing interest in taking advantage of CNN to classify geological material. In this study, a feasibility of the deep CNN is investigated for automatically and accurately identifying rock types, focusing on the condition of various shapes and colors even in the same rock type. It can be further developed to a mobile application for assisting geologist in classifying rocks in fieldwork. The structure of CNN model used in this study is based on a deep residual neural network (ResNet), which is an ultra-deep CNN using in object detection and classification. The proposed CNN was trained on 10 typical rock types with an overall accuracy of 84% on the test set. The result demonstrates that the proposed approach is not only able to classify rock type using images, but also represents an improvement as taking highly diverse rock image dataset as input.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.59.4-60
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• 2018

To investigate the impact of the high-redshift quasars on cosmic reionization, the faint end slope of the quasars luminosity function has to be determined precisely. More quasars with low luminosity are needed to constrain the contribution to reionization in the early universe. However, finding these quasars has been regarded as tough process owing to the improper shallow depth of imaging data. In recent days, the release data of Subaru Hyper Suprime-Cam (HSC) Strategic Program survey which provide the deep images reaching ~ 25 mag facilitates searching the faint quasars candidates. To find faint quasar candidates in ELAIS-N1 field, along with the HSC data, two near-infrared (NIR) data sets also be used : The Infrared Medium-deep Survey (IMS) and The UKIRT Infrared Deep Sky Survey (UKIDSS) - Deep Extragalactic Survey (DXS). Quasar candidates selected from the multi-band color cut were observed by the SED camera for QUasars in EArly uNiverse (SQUEAN) instrument. To trace the redshifted Lyman break efficiently, appropriate medium bands comparable to targeted redshift range are chosen. The most reliable quasar candidates are finally determined through SED fitting. Using this less luminous quasars candidates, we can speculate the relation between the quasar growth and the host galaxy unbiasedly and estimate the contribution to the cosmic reionization.

• Journal of the Korea Computer Graphics Society
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• v.24 no.1
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• pp.9-16
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• 2018

In this paper, we introduce a visualization framework for cell image data obtained from optical diffraction tomography (ODT), including a method for representing cell morphology in 3D virtual environment and a color mapping protocol. Unlike commonly known volume data sets, such as CT images of human organ or industrial machinery, that have solid structural information, the cell image data have rather vague information with much morphological variations on the boundaries. Therefore, it is difficult to come up with consistent representation of cell structure for visualization results. To obtain desired visual representation of cellular structures, we propose an interactive visualization technique for the ODT data. In visualization of 3D shape of the cell, we adopt a volume rendering technique which is generally applied to volume data visualization and improve the quality of volume rendering result by using empty space jittering method. Furthermore, we provide a layer-based independent rendering method for multiple transfer functions to represent two or more cellular structures in unified render window. In the experiment, we examined effectiveness of proposed method by visualizing various type of the cell obtained from the microscope which can capture ODT image and fluorescence image together.

• Journal of the korean academy of Pediatric Dentistry
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• v.33 no.3
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• pp.429-437
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• 2006

The purpose of this study was to evaluate the shade of primary incisors. One hundred and nineteen children 394 maxillary anterior primary incisors were assessed. Digital shade analysing system ($ShadeScan^{TM}$, Cynovad, Canada) was used for measuring the shades This system enabled to improve the accuracy and objectivity The images of the teeth were taken with $ShadeScan^{TM}$ and shade maps of the teeth were obtained with $ShadeScan^{TM}$ software. The shades of three regions (cervical third middle third, incisal third) of the teeth were evaluated. The results were as follows : 1. In cervical third of primary incisors, D2 and D3 were the major shades and D2 was the most frequent shade. 2. In middle third of primary incisors, C1, D2, and B1 were the major shades and C1 was the most frequent shade. 3. In incisal third of primary incisors, A2 was the most frequent shade and D2 shade followed.

• Fashion & Textile Research Journal
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• v.6 no.3
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• pp.336-340
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• 2004

This is the result of the comparison of the number of jeans, colors, images, opinions when it was purchased, shapes according to the gender of persons in jeans. According to the gender, male students had 1.64 jeans(46.3%) and female students had 2.09 jeans(53.7%) on the average. Male students selected colors of jeans which they don't have, but want to wear once in the order of blue(3.7%), red(21.0%), white(24.1%), black(25.6%), and others(25.6%). Female students selected colors in the order of blue(3.2%), black(15.6%), red(24.8%), white(27.7%) and others(25.6%). In case of the general image about jeans, male students thought the jeans as masculine(1.2%), sexy(3.1%), unisexual(3.2%), active(23.6%), young(29.8%), and comfortable(36.5%) and female students thought it as masculine(0.3%), sexy(3.5%), unisexual(10.4%), young(21.9%), comfortable(28.1%) and active(35.8%). Male students considered torn or holed jeans ill-mannered(10.7%), delinquent, (20.7%)trendy(21.0%), comfortable(22.9%), and dandy(24.7%). Female students think it ill-mannered(3.4%), delinquent7.1%, trendy(17.4%), comfortable(21.1%), and dandy(50.9%). When they purchase jeans, male students choose according to trends(17.9%), don't consider design(19.5%) and look for their own styles(62.6%), female students didn't consider design(5.2%), choose according to trends(22.0%), and look for their own styles(72.5%). The designs of jeans which they usually wear were bell bottom(1.5%), wide-shaped(7.4%), baggy(17.5%), straight-shaped(73.6%) in case of male students. on the other hand, in case of female students, baggy(10.2%), wide-shaped(11.0%), bell bottom(17.0%), and straight-shaped(61.8%). The designs of jeans which they didn't have but want to wear once are wide-shaped(10.1%), bell bottom(13.2%), baggy(20.9%), and straight-shaped(55.2%) in case of male students. On the other hand, females students want to wear baggy(11.6%), wide-shaped(15.0%), straight-shaped(27.6%), and bell bottom(45.8%). The above-mentioned findings illustrated that both male and female students regarded blue as the original color of jeans, but they wanted to wear jeans in colors other than blue. In the past, jeans were considered masculine and unisex, but they viewed jeans as an apparel that was comfortable to wear and made it easier to move. Female students had a higher tendency to be fashionable than male students, and their preference for jeans was consequently different. Jeans manufacturers should take those characteristics into account to produce products in different colors and form.