• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.522-532
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• 2011

In Oriental medicine, the status of a tongue is the important indicator to diagnose the condition of internal organs in a body. A tongue diagnosis is not only convenient but also non-invasive, and therefore widely used in Oriental medicine. But tongue diagnosis has some problems that should be objective and standardized, it also exhaust the diagnosis tool that can help for oriental medicine doctor's decision-making. In this paper, to solve the this problem we propose a method that calculates the tongue geometry information for effective tongue diagnosis analysis. Our method is to extract the tongue region for using improved snake algorithm, and calculates the geometry information by using convex hull and In-painting. In experiment, our method has stable performance as 7.2% by tooth plate and 8.5% by crack in region difference ratio.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.409-418
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• 2003

Object tracking in video is one of subject that computer vision and several practical application field have interest in several years. This paper proposes real time object tracking and face region extraction method that can be applied to security and supervisory system field. For this, in limited environment that camera is fixed and there is seldom change of background image, proposed method detects position of object and traces motion using difference between input image and background image. The system creates adaptive background image and extracts pixels in object using line scan method for more stable object extraction. The real time object tracking is possible through establishment of MBR(Minimum Bounding Rectangle) using extracted pixels. Also, effectiveness for security and supervisory system is improved due to extract face region in established MBR. And through an experiment, the system shows fast real time object tracking under limited environment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.45-50
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• 2004

In this paper, we propose a new PCA-based LDA Mixture Algorithm(PLMA) for real-time face recognition system. This system greatly consists of the two parts: 1) face extraction part; 2) face recognition part. In the face extraction part we applied subtraction image, color filtering, eyes and mouth region detection, and normalization method, and in the face recognition part we used the method mixing PCA and LDA in extracted face candidate region images. The existing recognition system using only PCA showed low recognition rates, and it is hard in the recognition system using only LDA to apply LDA to the input images as it is when the number of image pixels ire small as compared with the training set. To overcome these shortcomings, we reduced dimension as we apply PCA to the normalized images, and apply LDA to the compressed images, therefore it is possible for us to do real-time recognition, and we are also capable of improving recognition rates. We have experimented using self-organized DAUface database to evaluate the performance of the proposed system. The experimental results show that the proposed method outperform PCA, LDA and ICA method within the framework of recognition accuracy.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.231-236
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• 2014

In this paper, we propose a processing speed improvement by adding a parallel processing based on device(graphic card) into a road region extraction by host(PC) based serial processing. The OpenCV CUDA supports the many functions of parallel processing method by interworking a conventional OpenCV with CUDA. Also, when interworking the OpenCV and CUDA, OpenCV functions completed a configuration are optimized the User's device(Graphic Card) specifications. Thus, OpenCV CUDA usage provides an algorithm verification and easiness of simulation result deduction. The proposed method is verified that the proposed method has a about 3.09 times faster processing speed than a conventional method by using OpenCV CUDA and graphic card of NVIDIA GeForce GTX 560 Ti model through experimentation.

• The Journal of Korean Academy of Prosthodontics
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• v.55 no.4
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• pp.403-409
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• 2017

In the case of an extraction in the maxillary anterior region, immediate placement of implant-supported fixed prosthesis can be considered as a treatment option. Fewer surgical operations, reduced treatment time, and optimal availability of existing bone are obvious advantages of the method; however, when applied in the continuous maxillary anterior region, inter-implant distance must be carefully considered, as well as accurate diagnosis and treatment planning for predictable outcome. In this case report, immediate placement of two implants in the continuous maxillary anterior along with bone graft following the extraction of root rests, and the restoration of provisional and implant-supported fixed prosthesis on a 63-year-old patient had resulted in both esthetically and functionally satisfactory clinical outcomes.

• Preventive Nutrition and Food Science
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• v.19 no.3
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• pp.145-155
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• 2014

Vascular dementia is characterized by white matter lesions involving the demyelination and activation of astrocytes and microglia. In a previous study, we showed that the supernatant of a laboratory-scale, hot water extract of ground whole wheat (TALE) attenuated white matter injury and astrocytic activation in a rat model of bilateral common carotid artery occlusion (BCCAO). In the present study, we made several modifications to the hot water extraction process to remove starch and enable large-scale production. We used wheat bran (WB), which contains less starch, instead of ground whole wheat. In addition, we removed starch granules with a decanter before hot water extraction. The final product, wheat bran extract (WBE), contained 2.42% arabinose, a surrogate marker of arabinoxylan, which is an active constituent of WBE. Supplementation of the rat model of BCCAO with WBE (400 mg/kg/day) for 33 days attenuated white matter injury, which was assessed by Luxol Fast Blue staining, in the corpus callosum (cc) and optic tract (opt) regions. Attenuation of white matter injury in the opt region was accompanied by improvement of the pupillary light reflex. Immunochemical staining revealed that supplementation with WBE reduced astrocytic activation in the cc and opt regions and reduced microglial activation in the opt region. These findings indicate that supplementation with WBE is effective at attenuating white matter injury accompanied by the inhibition of astrocytic and microglial activation. Therefore, extracts from WB, a cheap by-product of wheat milling, can be developed as a nutraceutical to prevent vascular dementia, a disease for which there is no approved pharmaceutical treatment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.12
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• pp.1437-1450
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• 1992

This paper describes the feature extraction of the interdigital regions of palm, and proposes a personal verification algorithm using the extracted features and the pattern types of those. The procedures of the feature extraction are as follows : first, the interdigital region is partitioned into several subregions, examining the phase of rigdes in each subregion, deciding the direction of that phase, and making the direction matrix of the region, we analyze this direction matrix to contain a feature pattern, and then, yield the first core. Second, applying the thinning to around the first core and tracing the thinned ridges, we yield the feature pattern types and second cores. Finally, the feature patterns coordinates included all of them are built. Then, distances and directions from each second core reaching to all the others are yielded from that coordinates. These informations are used to make a feature parameter. In our verification algorithm, such pattern types, the numbers of feature patterns, theses positions and feature parameters are used to analyze.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.41-47
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• 2011

Processing of the raw LiDAR data requires the high-end processor, because data form is a vector. In contrast, if LiDAR data is converted into a regular grid pattern by filltering, that has advantage of being in a low-cost equipment, because of the simple structure and faster processing speed. Especially, by using grid data classification, such as Quadtree, some of trees and cars are removed, so it has advantage of modeling. Therefore, this study presents the algorithm for automatic extraction of ground points using Quadtree and refion growing method from LiDAR data. In addition, Error analysis was performed based on the 1:5000 digital map of sample area to analyze the classification of ground points. In a result, the ground classification accuracy is over 98%. So it has the advantage of extracting the ground points. In addition, non-ground points, such as cars and tree, are effectively removed as using Quadtree and region growing method.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.1
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• pp.49-55
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• 2008

The face extraction is very important to provide the images of the roads and road sides without the problem of privacy. For face extraction form roadside images, we detected the skin color area by using HSI and YCrCb color models. Efficient skin color detection was achieved by using these two models. We used a connectivity and intensity difference for grouping, skin color regions further we applied shape conditions (rate, area, number and oval condition) and determined face candidate regions. We applied thresholds to region, and determined the region as the face if black part was over 5% of the whole regions. As the result of the experiment 28 faces has been extracted among 38 faces had problem of privacy. The reasons which the face was not extracted were the effect of shadow of the face, and the background objects. Also objects with the color similar to the face were falsely extracted. For improvement, we need to adjust the threshold.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.3
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• pp.317-327
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• 2016

The extraction of significant feature points from a video is directly associated with the suggested method's function. In particular, the occlusion regions in trees or people, or feature points extracted from the background and not from objects such as the sky or mountains are insignificant and can become the cause of undermined matching or recognition function. This paper classifies the feature points required for building recognition by using multi-frames in order to improve the recognition function(algorithm). First, through SIFT(scale invariant feature transform), the primary feature points are extracted and the mismatching feature points are removed. To categorize the feature points in occlusion regions, RANSAC(random sample consensus) is applied. Since the classified feature points were acquired through the matching method, for one feature point there are multiple descriptors and therefore a process that compiles all of them is also suggested. Experiments have verified that the suggested method is competent in its algorithm.