• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.7
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• pp.1456-1461
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• 2003

Recently, the quantity of using information go on increasing geometric-progression. At the same time, the management of information is effected on the most organization's effective operation so that many user call for the powerful equipment which expound. access more information. As information searching technology is concentrated about the object of information based on a letter mainly, an effective searching technology for the object of multimedia such as a still image, a video and a sound must be studied. As a monitor of computer is 2-D, it difficult for one to grasp the whole aspect at a look glance like a library. Accordingly, some condition is necessary. First, it acquired the virtual video, turning a camera around by 30 degrees with a camera of 15mm lens, giving a warping and distortion. Second, it improved the books for user to search easily, adding to the video in existing books information system. The original text suggests some way which can embody the video searching technology under the base of personal computer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1073-1080
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• 2011

In this paper, we propose a novel digital watermarking method by virtual optics which secures multimedia information such as images, videos and sounds. To secure the multimedia data, we use Fresnel transform which describes the diffraction phenomena of the waves. Also, this method attaches the random phase function to Fresnel transform so that original image and watermark image would be gaussian random vectors. The complex numbers of watermark by Fresnel transform are separated the real part and the imaginary part. The former is embedded in original image as a encoding key imperceptibly and the latter is used for detecting the watermark as a decoding key. This method for digital watermarking ensures that watermark can be successfully registered and extracted from the watermarked image. Further, it provides the robustness to signal processing operation and geometric distortion and proves the strong resilience against cropping attack. The performance evaluation of the experiment is carried out with PSNR, and the numerical simulation results show the efficiency of the proposed method.

• Korean Journal of Geomatics
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• v.2 no.1
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• pp.37-46
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• 2002

Accurate classification of water area is an preliminary step to accurately analyze the flooded area and damages caused by flood. This step is especially useful for monitoring the region where annually repeating flood is a problem. The accurate estimation of flooded area can ultimately be utilized as a primary source of information for the policy decision. Although SAR (Synthetic Aperture Radar) imagery with its own energy source is sensitive to the water area, its shadow effect similar to the reflectance signature of the water area should be carefully checked before accurate classification. Especially when we want to identify small flood area with mountainous environment, the step for removing shadow effect turns out to be essential in order to accurately classify the water area from the SAR imagery. In this paper, the flood area was classified and monitored using multi-temporal RADARSAT SAR images of Ok-Chun and Bo-Eun located in Chung-Book Province taken in 12th (during the flood) and 19th (after the flood) of August, 1998. We applied several steps of geometric and radiometric calculations to the SAR imagery. First we reduced the speckle noise of two SAR images and then calculated the radar backscattering coefficient $(\sigma^0)$. After that we performed the ortho-rectification via satellite orbit modeling developed in this study using the ephemeris information of the satellite images and ground control points. We also corrected radiometric distortion caused by the terrain relief. Finally, the water area was identified from two images and the flood area is calculated accordingly. The identified flood area is analyzed by overlapping with the existing land use map.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.346-349
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• 2011

In this paper, we design a perceptually invisible dot pattern layout and its recognition scheme, and we apply the recognition scheme into a smart self learning aid for interactive learning aid. To increase maximum information capacity and also increase robustness to the noises, we design a ECC (error correcting code) based dot pattern with directional vector indicator. To make a smart self-learning aid, we embed the micro dot pattern (20 information bit + 15 ECC bits + 9 layout information bit) using K ink (CMYK) and extract the dot pattern using IR (infrared) LED and IR filter based camera, which is embedded in the smart pen. The reason we use K ink is that K ink is a carbon based ink in nature, and carbon is easily recognized with IR even without light. After acquiring IR camera images for the dot patterns, we perform layout adjustment using the 9 layout information bit, and extract 20 information bits from 35 data bits which is composed of 20 information bits and 15 ECC bits. To embed and extract information bits, we use topology based dot pattern recognition scheme which is robust to geometric distortion which is very usual in camera based recognition scheme. Topology based pattern recognition traces next information bit symbols using topological distance measurement from the pivot information bit. We implemented and experimented with sample patterns, and it shows that we can achieve almost 99% recognition for our embedding patterns.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.289-301
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• 2023

Due to the development and dissemination of modern technology, anyone can easily communicate using services such as social network service (SNS) through a personal computer (PC) or smartphone. The development of these technologies has caused many beneficial effects. At the same time, bad effects also occurred, one of which was the spam problem. Spam refers to unwanted or rejected information received by unspecified users. The continuous exposure of such information to service users creates inconvenience in the user's use of the service, and if filtering is not performed correctly, the quality of service deteriorates. Recently, spammers are creating more malicious spam by distorting the image of spam text so that optical character recognition (OCR)-based spam filters cannot easily detect it. Fortunately, the level of transformation of image spam circulated on social media is not serious yet. However, in the mail system, spammers (the person who sends spam) showed various modifications to the spam image for neutralizing OCR, and therefore, the same situation can happen with spam images on social media. Spammers have been shown to interfere with OCR reading through geometric transformations such as image distortion, noise addition, and blurring. Various techniques have been studied to filter image spam, but at the same time, methods of interfering with image spam identification using obfuscated images are also continuously developing. In this paper, we propose a deep learning-based spam image detection model to improve the existing OCR-based spam image detection performance and compensate for vulnerabilities. The proposed model extracts text features and image features from the image using four sub-models. First, the OCR-based text model extracts the text-related features, whether the image contains spam words, and the word embedding vector from the input image. Then, the convolution neural network-based image model extracts image obfuscation and image feature vectors from the input image. The extracted feature is determined whether it is a spam image by the final spam image classifier. As a result of evaluating the F1-score of the proposed model, the performance was about 14 points higher than the OCR-based spam image detection performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2A
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• pp.319-326
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• 2006

A new enhanced 8-node hybrid/mixed plane stress elements based on assumed stress fields and modifed shape functions has been presented. The assumed stress fields are derived from the non-conforming displacement modes, which are less sensitive to geometric distortion. Explicit expression of shape functions is modifed so that it can represent any quadratic fields in Cartesian coordinates under the same condition as 9-node isoparametric element. The newly developed element has been designated as 'HQ8-$14{\beta}$'. The presented element is compared with existing elements to establish its accuracy and efficiency. Over a wide range of mesh distortions, the element presented here is found to be exceptionally accurate in predicting displacements.

• Current Optics and Photonics
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• v.8 no.3
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• pp.215-224
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• 2024

In medium- and long-range optical imaging systems, atmospheric turbulence causes blurring and distortion of images, resulting in loss of image information. An image-restoration method based on an adaptive feature-fusion multi-input-multi-output (MIMO) dense U-shaped network (Unet) is proposed, to restore a single image degraded by atmospheric turbulence. The network's model is based on the MIMO-Unet framework and incorporates patch-embedding shallow-convolution modules. These modules help in extracting shallow features of images and facilitate the processing of the multi-input dense encoding modules that follow. The combination of these modules improves the model's ability to analyze and extract features effectively. An asymmetric feature-fusion module is utilized to combine encoded features at varying scales, facilitating the feature reconstruction of the subsequent multi-output decoding modules for restoration of turbulence-degraded images. Based on experimental results, the adaptive feature-fusion MIMO dense U-shaped network outperforms traditional restoration methods, CMFNet network models, and standard MIMO-Unet network models, in terms of image-quality restoration. It effectively minimizes geometric deformation and blurring of images.

• The Korean Journal of Nuclear Medicine
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• v.31 no.1
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• pp.73-82
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• 1997

Regional myocardial blood flow (rMBF) can be noninvasively quantified using N-13 ammonia and dynamic positron emission tomography (PET). The quantitative accuracy of the rMBF values, however, is affected by the distortion of myocardial PET images caused by finite PET image resolution and cardiac motion. Although different methods have been developed to correct the distortion typically classified as partial volume effect and spillover, the methods are too complex to employ in a routine clinical environment. We have developed a refined method incorporating a geometric model of the volume representation of a region-of-interest (ROI) into the two-compartment N-13 ammonia model. In the refined model, partial volume effect and spillover are conveniently corrected by an additional parameter in the mathematical model. To examine the accuracy of this approach, studies were performed in 9 coronary artery disease patients. Dynamic transaxial images (16 frames) were acquired with a GE $Advance^{TM}$ PET scanner simultaneous with intravenous injection of 20 mCi N-13 ammonia. rMBF was examined at rest and during pharmacologically (dipyridamole) induced coronary hyperemia. Three sectorial myocardium (septum, anterior wall and lateral wall) and blood pool time-activity curves were generated using dynamic images from manually drawn ROIs. The accuracy of rMBF values estimated by the refined method was examined by comparing to the values estimated using the conventional two-compartment model without partial volume effect correction rMBF values obtained by the refined method linearly correlated with rMBF values obtained by the conventional method (108 myocardial segments, correlation coefficient (r)=0.88). Additionally, underestimated rMBF values by the conventional method due to partial volume effect were corrected by theoretically predicted amount in the refined method (slope(m)=1.57). Spillover fraction estimated by the two methods agreed well (r=1.00, m=0.98). In conclusion, accurate rMBF values can be efficiently quantified by the refined method incorporating myocardium geometric information into the two-compartment model using N-13 ammonia and PET.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1A
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• pp.1-10
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• 2012

Along with the development of coasts, islands and mountains, the demand of long-span bridges increases which, in turn, brings forth the construction of cable-supported bridges like suspension and cable-stayed bridges. There are various types of statically indeterminate structures widely applied that supported the main girder with stay cables, main cables, hanger cables with aesthetic structural appearance. As to the cable-supported bridges, the health monitoring of a bridge can be identified by measuring tension force on cable repeatedly. The tension force on cable is measured either by direct measurement of stress of cable using load cell or hydraulic jack, or by vibration method estimating tension force using cable shape and measured dynamic characteristics. In this study, a method to estimate dynamic characteristics of hanger cables by using a digital image processing is suggested. Digital images are acquired by a portable digital camcorder, which is the sensor to remotely measure dynamic responses considering convenient and economical aspects for use. A digital image correlation(DIC) technique is applied for digital image processing, and an image transform function(ITF) to correct the geometric distortion induced from the deformed images is used to estimate subpixel. And, the correction of motion of vision-based measurement system using a fixed object in an image without installing additional sensor can be enhanced the resolution of dynamic responses and modal frequencies of hanger cables.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.3
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• pp.233-238
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• 2005

3-D virtual city model is becoming increasingly important for a number of GIS applications. For reconstruction of 3D building in urban area aerial images, satellite images, LIDAR data have been used mainly and most of researches related to 3-D reconstruction focus on development of method for extraction of building height and reconstruction of building. In case of automatically extracting and reconstructing of building height using only aerial images or satellite images, there are a lot of problems, such as mismatching that result from a geometric distortion of optical images. Therefore, researches of integrating optical images and existing digital map (1/1,000) has been in progress. In this paper, we focused on extracting of building height by means of interest points and vertical line locus method for reducing matching points. Also we used digital plotter in order to validate for the results in this study using aerial images (1/5,000) and existing digital map (1/1,000).