• The Journal of Korea Assosiation for Disability and Oral Health
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• v.8 no.1
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• pp.15-21
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• 2012

Extraction of all nonrestorable teeth prior to bone marrow transplantation is the major dental management of the patient being prepared for the transplantation. But, there are four principal causes for excessive bleeding in the immediate postextraction phase ; (1) Vascular wall alteration (wound infection, scurvy, chemicals, allergy) (2) Disorders of platelet function (3) Thrombocytopenic purpuras (4) Disorders of coagulation (liver disease, anticoagulation drug-heparin, coumarin, aspirin, plavix) If the hemorrhage from postextraction wound is unusually aggressive, the socket must be packed with local hemostatic agent and wound closure & pressure dressing are applied. But, in dental alveoli, local hemostatic agent (gelfoam, surgcel etc) may absorb oral microorganisms and cause alveolar osteitis (infection). This is a case report of bleeding and infection control by suture, pressure packing and iodoform gauze drainage on infected active bleeding extraction socket under sedation and local anesthesia in a 57-years-old multiple disabled patient with anticoagulation drug.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.653-655
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• 2005

More than 70 percent of terrestrial territory of Korea is mountainous areas where degradation becomes serious year by year due to illegal tombs, expanding golf courses and stone mine development. We elaborate the potential usage of high resolution image for the monitoring of the phenomena. We made the classification of tombs and the statistical radiometric characteristics of graves were identified from this project. The graves could be classified to 4 groups from the field survey. As compared with grouping data after clustering and discriminant analysis, the two results coincided with each other. Object-oriented classification algorithm for feature extraction was theoretically researched in this project. And we did a pilot project, which was performed with mixed methods. That is, the conventional methods such as unsupervised and supervised classification were mixed up with the new method for feature extraction, object-oriented classification method. This methodology showed about $60\%$ classification accuracy for extracting tombs from satellite imagery. The extraction of tombs' geographical coordinates and graves themselves from satellite image was performed in this project. The stone mines and golf courses are extracted by NDVI and GVI. The accuracy of classification was around 89 percent. The location accuracy showed extraction of tombs from one-meter resolution image is cheaper and quicker way than GPS method. Finally we interviewed local government officers and made analyses on the current situation of mountainous area management and potential usage of KOMPSAT-II images. Based on the requirement analysis, we developed software, which is to management and monitoring system for mountainous area for local government.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.647-650
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• 1999

In this Paper, we propose an optimal feature extraction for multiclass problems through proper choice of initial feature vectors. Although numerous feature extraction algorithms have been proposed, those algorithms are not optimal for multiclass problems. Recently, an optimal feature extraction algorithm for multiclass problems has been proposed, which provides a better performance than the conventional feature extraction algorithms. In this paper, we improve the algorithm by choosing good initial feature vectors. As a result, the searching time is significantly reduced. The chance to be stuck in a local minimum is also reduced.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.111-122
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• 2021

Building footprint extraction is an active topic in the domain of remote sensing, since buildings are a fundamental unit of urban areas. Deep convolutional neural networks successfully perform footprint extraction from optical satellite images. However, semantic segmentation produces coarse results in the output, such as blurred and rounded boundaries, which are caused by the use of convolutional layers with large receptive fields and pooling layers. The objective of this study is to generate visually enhanced building objects by directly extracting the vertices of individual buildings by combining instance segmentation and keypoint detection. The target keypoints in building extraction are defined as points of interest based on the local image gradient direction, that is, the vertices of a building polygon. The proposed framework follows a two-stage, top-down approach that is divided into object detection and keypoint estimation. Keypoints between instances are distinguished by merging the rough segmentation masks and the local features of regions of interest. A building polygon is created by grouping the predicted keypoints through a simple geometric method. Our model achieved an F1-score of 0.650 with an mIoU of 62.6 for building footprint extraction using the OpenCitesAI dataset. The results demonstrated that the proposed framework using keypoint estimation exhibited better segmentation performance when compared with Mask R-CNN in terms of both qualitative and quantitative results.

• Journal of Dental Anesthesia and Pain Medicine
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• v.23 no.6
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• pp.347-355
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• 2023

Background: Eye movement desensitization and reprocessing (EMDR) therapy has been reported to be very efficacious for treating post-traumatic stress disorder (PTSD) and other anxiety-related conditions. However, a review of the literature reveals the sparse use of this therapy in the field of pediatric dentistry. This study aimed to evaluate anxiety trends in pediatric dental patients during local anesthesia and extraction with and without EMDR therapy. Methods: Children in the age range of 8-12 years who required dental extractions were assigned randomly into two groups: an EMDR group (group 1) and a routine behavior management therapy group (group 2; receiving more traditional interventions such as tender love and care behavioral modeling, and distraction). Anxiety scores were recorded at four levels using the visual facial anxiety scale (VFAS) preoperatively, after therapy, after the administration of local anesthesia (LA), and after extraction. Results: Reduced anxiety was observed after the delivery of EMDR therapy, after LA administration, and post-extraction in the EMDR group compared to pre-operative anxiety scores of anxiety (P < 0.001; unpaired Student's t and Mann-Whitney U tests). In the control group, mild reductions in anxiety after routine behavior management therapy were observed, accompanied by spikes in anxiety levels after LA and extractions. Conclusion: EMDR therapy was found to be valuable for reducing anxiety among pediatric dental patients during tooth extraction procedures.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.404-406
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• 2002

In this paper, the method of image feature extraction is proposed. This method employ the energy field analysis, outlier removal algorithm and ring projection. Using this algorithm, we achieve rotation-translation-scale invariant feature extraction. The force field are exploited to automatically locate the extrema of a small number of potential energy wells and associated potential channels. The image feature is acquired from relationship of local extrema using the ring projection method.

• Economic and Environmental Geology
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• v.54 no.4
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• pp.427-439
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• 2021

On the base of the aggregate extraction statistics, this study tried to analyse the demand and supply of aggregate resources of each local government and provide directions for the stable and sustainable supply and demand of aggregate resources in the future. In 2019, aggregates were produced in 148 cities, about 65% of the 229 cities of Korea, but in 7 metropolitan cities with 74 local governments, only 19 cities developed the aggregate. It means that aggregate extraction is taking place in almost all regions in Korea. Sand and gravel were produced in 110 districts and 132 districts, respectively. By aggregate source, river aggregates were extracted in 4 local governments, land aggregates in 42 local governments, forest aggregates in 75 local governments, crushed aggregates in 105 local governments, and washing aggregates in 15 local governments. In other words, 81 district in Korea have not extracted land-based aggregate at all. 71 local governments produced only one type of aggregate, and 55 local governments developed two types of aggregate, and 22 local governments developed more that three types of aggregate. In 2019, the leading producing local government were, in descending order of volume, Ulju-gun, followed by Hwaseong-si, Cheongju-si, Pocheon-si, Paju-si, Yongin-si, Gimhae-si, Gwangju-si in Gyeonggi-do. 41 local governments have developed aggregates of more than 1 million m³, and the combined production of the 41 cities accounted for about 70% of national total. This shows that the aggregate extraction trend of local governments is becoming larger and more concentrated.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.2
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• pp.14-20
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• 2003

This paper presents a text extraction method of camera based document image. It is more difficult to recognize camera based document image in comparison with scanner based image because of segmentation problem due to variable lighting condition and versatile fonts. Both document binarization and character extraction are important processes to recognize camera based document image. After converting color image into grey level image, gray level normalization is used to extract character region independent of lighting condition and background image. Local adaptive binarization method is then used to extract character from the background after the removal of noise. In this character extraction step, the information of the horizontal and vertical projection and the connected components is used to extract character line, word region and character region. To evaluate the proposed method, we have experimented with documents mixed Hangul, English, symbols and digits of the ETRI database. An encouraging binarization and character extraction results have been obtained.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.1-9
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• 2003

In this paper, we propose a new fingerprint feature extraction method using the convex structure. A fingerprint minutiae flows along the uniform direction and is regarded as a sinusoidal signal across the normal direction. Local maxima of the signal represent coarse thinned one-pixel-wide ridges in which the convex region of the signal correspond to ridges. The proposed fingerprint feature extraction method detects the convex structure and local maxima. Finally fingerprint features are extracted from one-pixel-wide ridges. Because it has no parameter, it is efficient for various fingerprint identification systems.

• International Journal of Contents
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• v.8 no.1
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• pp.30-38
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• 2012

Text extraction and binarization are the important pre-processing steps for text recognition. The performance of text binarization strongly related to the accuracy of recognition stage. In our proposed method, the first stage based on line detection and shape feature analysis applied to locate the position of a business card and detect the shape from the complex environment. In the second stage, several local regions contained the possible text components are separated based on the projection histogram. In each local region, the pixels grouped into several connected components based on the connected component labeling and projection histogram. Then, classify each connect component into text region and reject the non-text region based on the feature information analysis such as size of connected component and stroke width estimation.