• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1057-1068
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• 2022

This paper compares the combination performance of feature point-based matching algorithms as a study to confirm the matching possibility between image taken by a user and a virtual texture image with the goal of developing mobile-based real-time image positioning technology. The feature based matching algorithm includes process of extracting features, calculating descriptors, matching features from both images, and finally eliminating mismatched features. At this time, for matching algorithm combination, we combined the process of extracting features and the process of calculating descriptors in the same or different matching algorithm respectively. V-World 3D desktop was used for the virtual indoor texture image. Currently, V-World 3D desktop is reinforced with details such as vertical and horizontal protrusions and dents. In addition, levels with real image textures. Using this, we constructed dataset with virtual indoor texture data as a reference image, and real image shooting at the same location as a target image. After constructing dataset, matching success rate and matching processing time were measured, and based on this, matching algorithm combination was determined for matching real image with virtual image. In this study, based on the characteristics of each matching technique, the matching algorithm was combined and applied to the constructed dataset to confirm the applicability, and performance comparison was also performed when the rotation was additionally considered. As a result of study, it was confirmed that the combination of Scale Invariant Feature Transform (SIFT)'s feature and descriptor detection had the highest matching success rate, but matching processing time was longest. And in the case of Features from Accelerated Segment Test (FAST)'s feature detector and Oriented FAST and Rotated BRIEF (ORB)'s descriptor calculation, the matching success rate was similar to that of SIFT-SIFT combination, while matching processing time was short. Furthermore, in case of FAST-ORB, it was confirmed that the matching performance was superior even when 10° rotation was applied to the dataset. Therefore, it was confirmed that the matching algorithm of FAST-ORB combination could be suitable for matching between virtual texture image and real image.

• Journal of Dental Rehabilitation and Applied Science
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• v.39 no.4
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• pp.187-194
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• 2023

Purpose: A mismatched size in the post and post space is a common problem during post-fixation. Since this discordance affects the bonding strength of the fiber-reinforced composite resin post (FRC Post), a corresponding luting agent is required. The aim of this study was to evaluate the bonding strength of the FRC post according to the fitness of the fiber post and the type of luting agent. Materials and Methods: Thirty mandibular premolar were endodontic-treated and assigned to two groups according to their prepared post space: Fitting (F) and Mismatching (M). These groups were further classified into three subgroups according to their luting agent: RelyX Unicem (ReX), Luxacore dual (Lux), and Duolink (Duo). A push-out test was performed to measure the push-out bond strengths. The fractured surfaces of each cross-section were then examined, and the fracture modes were classified. Results: In the ReX and Duo subgroups, the F group had a higher mean bond strength; however, the Lux subgroup had no significant difference between the F and M groups. In the analysis of the failure modes, the ReX subgroup had only adhesive failures between the cement and dentin. Conclusion: The result of this study showed that the bond strength of an FRC post was influenced by the type of luting agent and the mismatch between the diameter of the prepared post space and that of the post.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.387-396
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• 2024

Most very high-resolution (VHR) satellite images provide rational polynomial coefficients (RPC) data to facilitate the transformation between ground coordinates and image coordinates. However, initial RPC often contains geometric errors, necessitating correction through matching with ground control points (GCPs). A GCP chip is a small image patch extracted from an orthorectified image together with height information of the center point, which can be directly used for geometric correction. Many studies have focused on area-based matching methods to accurately align GCP chips with VHR satellite images. In cases with seasonal differences or changed areas, edge-based algorithms are often used for matching due to the difficulty of relying solely on pixel values. However, traditional edge extraction algorithms,such as canny edge detectors, require appropriate threshold settings tailored to the spectral characteristics of satellite images. Therefore, this study utilizes deep learning-based edge information that is insensitive to the regional characteristics of satellite images for matching. Specifically,we use a pretrained pixel difference network (PiDiNet) to generate the edge maps for both satellite images and GCP chips. These edge maps are then used as input for normalized cross-correlation (NCC) and relative edge cross-correlation (RECC) to identify the peak points with the highest correlation between the two edge maps. To remove mismatched pairs and thus obtain the bias-compensated RPC, we iteratively apply the data snooping. Finally, we compare the results qualitatively and quantitatively with those obtained from traditional NCC and RECC methods. The PiDiNet network approach achieved high matching accuracy with root mean square error (RMSE) values ranging from 0.3 to 0.9 pixels. However, the PiDiNet-generated edges were thicker compared to those from the canny method, leading to slightly lower registration accuracy in some images. Nevertheless, PiDiNet consistently produced characteristic edge information, allowing for successful matching even in challenging regions. This study demonstrates that improving the robustness of edge-based registration methods can facilitate effective registration across diverse regions.

• Tuberculosis and Respiratory Diseases
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• v.43 no.5
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• pp.763-773
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• 1996

Background : Behçet's syndrome is a chronic multisystemic disease affecting many organs such as skin, mucosa, eye, joint, central nervous system and blood vessels. Lung involvement occurs in 5% of Behçet's syndrome and is thought to be due to the pulmonary vasculitis leading to thromboembolism, aneurysm and arteriobronchial fistula. Pulmonary vasculitis in Behçet's syndrome is a unique clinical feature, differing from other vasculitis affecting the lung and is one of the major causes of death. Therefore, we examined the incidence, the clinical features, the radioloic findings and the clinical courses of the lung involvement in Behçet's syndrome. Methods: We retrospectively reviewed the medical records and radiologic studies of 10 cases of the lung involvement in Behçet's syndrome diagnosed at Yongdong Severance Hospital and Severance Hospital from 1986 to 1995. We analysed the clinical features, the radiological findings, the treatment modalities and the clinical courses. Results: 1) The incidence of the lung involvement in Behçet's syndrome was 2%(10/487). The male to female ratio was 8 : 2 and the mean age was 34 years. The presenting symptom was hemoptysis in 5 of 10 cases, and massive hemoptysis was noted in 2 cases. Other pulmonary symptoms were cough(6/10), dyspnea(4/10), and chest pain(2/10). Other manifestations were oral ulcers(10/10), genital ulcers(9/10), skin lesions(7/10), and eye lesions(6/10). 2) The laboratory findings were nonspecific. The posteroanterior views of chest radiographies showed multiple infiltrates(6/10), nodular or mass-like opacities(4/10), or normal findings(2/10). The chest CT scans showed multifocal consolidations(6/8), and aneurysms of the pulmonary aneries(4/8). The pulmonary angiographies were performed in 3 cases, and showed pulmonary artery aneurysms in 2 cases. The ventilation-perfusion scans in 2 cases of normal chest x-ray showed multiple mismatched findings. 3) The patients were treated with combination therapy consisting of corticosteroids, cyclophosphamide, and colchicine or anticoagulant agents. Surgical resection was performed in one case with a huge aneurysm. 4) We have followed up nine of ten cases. Three cases are well-being with medical therapy, two cases are severely disabled now and four cases died due to massive hemoptysis, massive pulmonary embolism, or sepsis. Conclusion : Pulmonary vasculitis is a main feature of the lung involvement of Behçet's syndrome, causing hemorrhage, aneurysmal formation, and/or thromboemboism. The lung involvement of Behçet's syndrome is uncommon but is one of the most serious prognostic factors of the disease. Therefore, an aggressive diagnostic work-up for early detection and proper treatment are recommended to improve the clinical course and the survival.