• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.411-421
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• 2012

The stagnant growth in 3D market due to 3D movie contents shortage is encouraging development of techniques for production cost reduction. Elimination of vertical disparity generated during image acquisition requires heaviest time and effort in the whole stereoscopic film-making process. This matter is directly related to competitiveness in the market and is being dealt with as a very important task. The removal of vertical disparity, i.e. image rectification has been treated for a long time in the photogrammetry field. While computer vision methods are focused on fast processing and automation, photogrammetry methods on accuracy and precision. However, photogrammetric approaches have not been tried for the 3D film-making. In this paper, proposed is a photogrammetry-based rectification algorithm that enable to eliminate the vertical disparity precisely by reconstruction of geometric relationship at the time of shooting. Evaluation of proposed algorithm was carried out by comparing the performance with two existing computer vision algorithms. The epipolar constraint satisfaction, epipolar line accuracy and vertical disparity of result images were tested. As a result, the proposed algorithm showed excellent performance than the other algorithms in term of accuracy and precision, and also revealed robustness about position error of tie-points.

• The Korean Journal of Nuclear Medicine Technology
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• v.21 no.2
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• pp.31-36
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• 2017

Purpose Recently, the performance of PET/CT scanner has been improved and various techniques have been developed to increase the image quality such as Sensitivity and Resolution. The purpose of this study is to evaluate the usefulness of Q.Clear (a fully convergent iterative reconstruction) technique of GE Discovery IQ equipment to enhance the image quality. Materials and Methods All scans were acquired by Discovery IQ (GE Healthcare, MI, USA). In NEMA IEC Body Phantom test, Background to Hot-sphere (10 mm, 13 mm, 17 mm, 22 mm) ratio was 1:4 and scan time was 3 minutes. The images were reconstructed by VPHDs (VUE Point High-Definition + SharpIR) and Q.Clear to evaluate each Contrast. We injected 18F-FDG 187 M㏃ to PET/SPECT Performance Phantom. And then it was scanned for 4 minutes to evaluate Resolution and Uniformity. T-test statistical analysis was performed on SUVmax of small lesions less than 2 cm in 100 clinical patients regardless of disease type. Results In the NEMA IEC Body Phantom, the Contrast was $63.6{\pm}5.7%$ (VPHDs) and $75{\pm}4.8%$ (Q.Clear). In the PET/SPECT Performance Phantom, the Resolution was 9.2 mm (VPHDs) and 7.3 mm (Q.Clear). Uniformity of Q.Clear was 10.8% better than VPHDs. T-test statistic of the clinical patients showed a significant difference of p value of 0.021. Conclusion Both the phantom test and the clinical results showed that the quality of the image was improved in Q.Clear was applied. The SUVmax was highly measured in Q.Clear and the lesions were clearly distinguished visually. Therefore Q.Clear can be useful in various aspects such as dose-reduction, patients evaluation and image analysis.

• Journal of the Korean Society of Radiology
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• v.83 no.2
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• pp.344-359
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• 2022

Purpose To develop a denoising convolutional neural network-based image processing technique and investigate its efficacy in diagnosing breast cancer using low-dose mammography imaging. Materials and Methods A total of 6 breast radiologists were included in this prospective study. All radiologists independently evaluated low-dose images for lesion detection and rated them for diagnostic quality using a qualitative scale. After application of the denoising network, the same radiologists evaluated lesion detectability and image quality. For clinical application, a consensus on lesion type and localization on preoperative mammographic examinations of breast cancer patients was reached after discussion. Thereafter, coded low-dose, reconstructed full-dose, and full-dose images were presented and assessed in a random order. Results Lesions on 40% reconstructed full-dose images were better perceived when compared with low-dose images of mastectomy specimens as a reference. In clinical application, as compared to 40% reconstructed images, higher values were given on full-dose images for resolution (p < 0.001); diagnostic quality for calcifications (p < 0.001); and for masses, asymmetry, or architectural distortion (p = 0.037). The 40% reconstructed images showed comparable values to 100% full-dose images for overall quality (p = 0.547), lesion visibility (p = 0.120), and contrast (p = 0.083), without significant differences. Conclusion Effective denoising and image reconstruction processing techniques can enable breast cancer diagnosis with substantial radiation dose reduction.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.44-51
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• 2007

For real-time recognizing of model objects in remote position a new Neural Networks algorithm is proposed. The proposed neural networks technique is the real time computation methods through the inter-node diffusion. In the networks, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. The most reliable algorithm derived for real time recognition of objects, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates. Through several simulation experiments, real time reconstruction of the nonlinear image information is processed. 1-D LIPN hardware has been composed and various experiments with static and dynamic signals have been implemented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2086-2097
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• 2021

The current cultural assets are being restored depending on the opinions of experts (craftsmen). We intend to introduce digitalized artificial intelligence techniques, excluding the personal opinions of experts on reconstruction of such cultural properties. The first step toward restoring digitized cultural properties is separation. The restoration of cultural properties should be reorganized based on recorded documents, period historical backgrounds and regional characteristics. The cultural properties in the form of photographs or images should be collected by separating the background. In addition, when restoring cultural properties most of them depend a lot on the tendency of the restoring person workers. As a result, it often occurs when there is a problem in the accuracy and reliability of restoration of cultural properties. In this study, we propose a search method for learning stored digital cultural assets using AI technology. Pagoda was selected for restoration of Cultural Properties. Pagoda data collection was collected through the Internet and various historical records. The pagoda data was classified by period and region, and grouped into similar buildings. The collected data was learned by applying the well-known CNN algorithm for artificial intelligence learning. The pagoda search used Yolo Marker to mark the tower shape. The tower was used a total of about 100-10,000 pagoda data. In conclusion, it was confirmed that the probability of searching for a tower differs according to the number of pagoda pictures and the number of learning iterations. Finally, it was confirmed that the number of 500 towers and the epochs in training of 8000 times were good. If the test result exceeds 8,000 times, it becomes overfitting. All so, I found a phenomenon that the recognition rate drops when the enemy repeatedly learns more than 8,000 times. As a result of this study, it is believed that it will be helpful in data gathering to increase the accuracy of tower restoration.

• The Korean Journal of Nuclear Medicine
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• v.36 no.6
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• pp.344-356
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• 2002

Purpose: RBC blood pool SPECT has been used to diagnose focal liver lesion such as hemangioma owing to its high specificity. However, low spatial resolution is a major limitation of this modality. Recently, ordered subset expectation maximization (OSEM) has been introduced to obtain tomographic images for clinical application. We compared this new modified iterative reconstruction method, OSEM with conventional filtered back projection (FBP) in imaging of liver hemangioma. Materials and Methods: Sixty four projection data were acquired using dual head gamma camera in 28 lesions of 24 patients with cavernous hemangioma of liver and these raw data were transferred to LINUX based personal computer. After the replacement of header file as interfile, OSEM was performed under various conditions of subsets (1,2,4,8,16, and 32) and iteration numbers (1,2,4,8, and 16) to obtain the best setting for liver imaging. The best condition for imaging in our investigation was considered to be 4 iterations and 16 subsets. After then, all the images were processed by both FBP and OSEM. Three experts reviewed these images without any information. Results: According to blind review of 28 lesions, OSEM images revealed at least same or better image quality than those of FBP in nearly all cases. Although there showed no significant difference in detection of large lesions more than 3 cm, 5 lesions with 1.5 to 3 cm in diameter were detected by OSEM only. However, both techniques failed to depict 4 cases of small lesions less than 1.5 cm. Conclusion: OSEM revealed better contrast and define in depiction of liver hemangioma as well as higher sensitivity in detection of small lesions. Furthermore this reconstruction method dose not require high performance computer system or long reconstruction time, therefore OSEM is supposed to be good method that can be applied to RBC blood pool SPECT for the diagnosis of liver hemangioma.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.2
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• pp.132-140
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• 2001

This paper proposes an efficient walktlu-ough animation from two images of the same scene. To make animation easily and fast, Tour Into the Picture(TIP) enables walkthrough animation from single image but lacks the reality of its foreground object when the viewpoint moves from side to side, and view morphing uses only 2D transition between two images but restricts its camera path on the line between two views. By combining advantages of these two image-based techniques, this paper suggests a new virtual navigation technique which enable natural scene transformation when the viewpoint changes in the side-to-side direction as well as in the depth direction. In our method, view morphing is employed only in foreground objects , and background scene which is perceived carelessly is mapped into cube-like 3D model as in TIP, so as to save laborious 3D reconstruction costs and improve visual realism simultaneously. To do this, we newly define a camera transformation between two images from the relationship of the spidery mesh transformation and its corresponding 3D view change. The result animation shows that our method creates a realistic 3D virtual navigation using a simple interface.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.29-40
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• 2005

According as base of digital hologram has been magnified, discussion of compression technology is expected as a international standard which defines the compression technique of 3D image and video has been progressed in form of 3DAV which is a part of MPEG. As we can identify in case of 3DAV, the coding technique has high possibility to be formed into the hybrid type which is a merged, refined, or mixid with the various previous technique. Therefore, we wish to present the relationship between various image/video coding techniques and digital hologram In this paper, we propose an efficient coding method of digital hologram using standard compression tools for video and image. At first, we convert fringe patterns into video data using a principle of CGH(Computer Generated Hologram), and then encode it. In this research, we propose a compression algorithm is made up of various method such as pre-processing for transform, local segmentation with global information of object image, frequency transform for coding, scanning to make fringe to video stream, classification of coefficients, and hybrid video coding. Finally the proposed hybrid compression algorithm is all of these methods. The tool for still image coding is JPEG2000, and the toots for video coding include various international compression algorithm such as MPEG-2, MPEG-4, and H.264 and various lossless compression algorithm. The proposed algorithm illustrated that it have better properties for reconstruction than the previous researches on far greater compression rate above from four times to eight times as much. Therefore we expect that the proposed technique for digital hologram coding is to be a good preceding research.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.313-321
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• 2015

To minimize CT examination for Hip FAI diagnosis and operation plan. also, whether the MRI 3D images can replace Hip Clock face image was evaluated when performing Hip FAI MRI by using additional 3D image. This study analyzed Hip MRI and 3D Hip CT images of 31 patients in this hospital. For the purpose of evaluating the images, one orthopedic surgeon and one radiology specialist reconstructed Clock face, at MR and CT modality, by superior 12 o'clock, labrum front 3 o'clock, and the other side 9 o'clock, centering on Hip joint articular transverse ligament 6 o'clock. Afterwards, by the Likert Scale 5 point scale (independent t-test p<0.005), this study evaluated the check-up of A. retinacular vessel, B. head neck junction at 11 o'clock, A. Epiphyseal line, B. Cam lesion at 12 o'clock, and Cam lesion, Posterior Cam lesion at 1,2,3 and 4 o'clock. As for the verification of reliability among observers, this study verified coincidence by Cohen's weighted Kappa verification. As a result of Likert scale for the purpose of qualitative evaluation about the image, 11 o'clock A. retinacular vessel MR average was $3.69{\pm}1.0$ and CT average was $2.8{\pm}0.78$. B. head neck juncton didn't have a difference between two observers (p <0.416). 12 o'clock A. Epiphyseal line MR average was $3.54{\pm}1.00$ and CT average was $4.5{\pm}0.62$(p<0.000). B. Cam lesion didn't have a difference between two observers (p <0.532). 1,2,3,4 Cam lesion and Posterior Cam lesion were not statistically significant (p <0.656, p <0.658). As a result of weighted Kappa verification, 11 o'clock A.retinacular vessel CT K value was 0.663 and the lowest conformity. As a result of coincidence evaluation on respective item, a very high result was drawn, and two observers showed high reliability.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.239-247
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• 2022

Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.