• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.493-497
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• 2016

Infrared (IR) imaging is capable of detecting targets that are not visible at night, thus it has been widely used for the security and defense system. However, the quality of the IR image is often degraded by low resolution and noise corruption. This paper addresses target segmentation with the IR image. Multiple regions of interest (ROI) are extracted by the multi-level segmentation and targets are segmented from the individual ROI. Each level of the multi-level segmentation is composed of a k-means clustering algorithm an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering algorithm initializes the parameters of the Gaussian mixture model (GMM) and the EM algorithm iteratively estimates those parameters. Each pixel is assigned to one of clusters during the decision. This paper proposes the selection and the merging of the extracted ROIs. ROI regions are selectively merged in order to include the overlapped ROI windows. In the experiments, the proposed method is tested on an IR image capturing two pedestrians at night. The performance is compared with conventional methods showing that the proposed method outperforms others.

• The Plant Pathology Journal
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• v.40 no.2
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• pp.106-114
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• 2024

Fusarium head blight (FHB), predominantly caused by Fusarium graminearum and F. asiaticum, is a significant fungal disease impacting small-grain cereals. The absence of highly resistant cultivars underscores the need for vigilant FHB surveillance to mitigate its detrimental effects. In 2023, a notable FHB outbreak occurred in the southern region of Korea. We assessed FHB disease severity by quantifying infected spikelets and grains. Isolating fungal pathogens from infected samples often encounters interference from various microorganisms. We developed a cost-effective, selective medium, named BGT (Burkholderia glumae Toxoflavin) medium, utilizing B. glumae, which is primarily known for causing bacterial panicle blight in rice. This medium exhibited selective growth properties, predominantly supporting Fusarium spp., while substantially inhibiting the growth of other fungi. Using the BGT medium, we isolated F. graminearum and F. asiaticum from infected wheat and barley samples across Korea. To further streamline the process, we used a direct PCR approach to amplify the translation elongation factor 1-α (TEF-1α) region without a separate genomic DNA extraction step. Phylogenetic analysis of the TEF-1α region revealed that the majority of the isolates were identified as F. asiaticum. Our results demonstrate that BGT medium is an effective tool for FHB diagnosis and Fusarium strain isolation.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.767-774
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• 2002

Conventional research on image restoration has focused on restoring degraded images resulting from image formation, storage and communication, mainly in the signal processing field. Related research on recovering original image information of caption regions includes a method using BMA(block matching algorithm). The method has problem with frequent incorrect matching and propagating the errors by incorrect matching. Moreover, it is impossible to recover the frames between two scene changes when scene changes occur more than twice. In this paper, we propose a method for recovering original images using EBMA(Extended Block Matching Algorithm) and a region compensation method. To use it in original image recovery, the method extracts a priori knowledge such as information about scene changes, camera motion and caption regions. The method decides the direction of recovery using the extracted caption information(the start and end frames of a caption) and scene change information. According to the direction of recovery, the recovery is performed in units of character components using EBMA and the region compensation method. Experimental results show that EBMA results in good recovery regardless of the speed of moving object and complexity of background in video. The region compensation method recovered original images successfully, when there is no information about the original image to refer to.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.55-68
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• 2012

In this paper, we propose a novel method to solve the problem of excessive segmentation out of the method of segmenting regions from an image using Homogeneity Threshold($H_T$). The algorithm of the previous image segmentation based on $H_T$ was carried out region growth by using only the center pixel of selected window. Therefore it was caused resulting in excessive segmented regions. However, before carrying region growth, the proposed method first of all finds out whether the selected window is homogeneity or not. Subsequently, if the selected window is homogeneity it carries out region growth using the total pixels of selected window. But if the selected window is not homogeneity, it carries out region growth using only the center pixel of selected window. So, the method can reduce remarkably the number of excessive segmented regions of image segmentation based on $H_T$. In order to show the validity of the proposed method, we carried out multiple experiments to compare the proposed method with previous method in same environment and conditions. As the results, the proposed method can reduce the number of segmented regions above 40% and doesn't make any difference in the quality of visual image when we compare with previous method. Especially, when we compare the image united with regions of descending order by size of segmented regions in experimentation with the previous method, even though the united image has regions more than 1,000, we can't recognize what the image means. However, in the proposed method, even though image is united by segmented regions less than 10, we can recognize what the image is. For these reason, we expect that the proposed method will be utilized in various fields, such as the extraction of objects, the retrieval of informations from the image, research for anatomy, biology, image visualization, and animation and so on.

• Korean Journal of Food Science and Technology
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• v.28 no.3
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• pp.411-416
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• 1996

Supercritical fluid extraction of ${\beta}$-carotene from carrot was optimized to maximize ${\beta}$-carotene (Y) extraction yield. A central composite design involving extraction pressure ($X_1$ 200-,100 bar), temperature ($X_2,\;35-51^{\circ}C$) and time ($X_1$$ 60-200min) was used. Three independent factors ($X_1,\;X_2,\;X_3$) were chosen to determine their effects on the various responses and the function was expressed in terms of a quadratic polynomial equation,$Y={\beta}_0+{\beta}_1X_1+{\beta}_2X_2+{\beta}_3X_3+{\beta}_11X_12+{\beta}_22X_3^2+{\beta}_-12X_1X_2+{\beta}_12X_1X_2+{\beta}_13X_1X_3+{\beta}_23X_2X_3,$ which measures the linear, quadratic and interaction effects. Extraction yields of ${\beta}$-carotene were affected by pressure, time and temperature in the decreasing order, and linear effect of tenter point (${\beta}_11$) and pressure (${\beta}_1$) were significant at a level of 0.001(${\alpha}$). Based on the analysis of variance, the model fitted for ${\beta}_11$-carotene (Y) was significant at 5% confidence level and the coefficient of determination was 0.938. According to the response surface of ${\beta}$-carotene by cannoical analysis, the stationary point for quantitatively dependent variable (Y) was found to be the maximum point for extraction yield. Response area for ${\beta}$-carotene (Y) in terms of interesting region was estimated over $10,611{\mu}g$ Per 100 g raw carrot under extraction.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.1062-1075
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• 2010

In the medical image application the difference of intensity is widely used for the image segmentation and feature extraction, and a well known method is the threshold technique that determines a threshold value and generates a binary image based on the threshold. A frequently-used threshold technique is the Otsu algorithm that provides efficient processing and effective selection criterion for choosing the threshold value. However, we cannot get good segmentation results by applying the Otsu algorithm to chest X-ray images. It is because there are various organic structures around lung regions such as ribs and blood vessels, causing unclear distribution of intensity levels. To overcome the ambiguity, we propose in this paper an effective algorithm to extract pulmonary regions that utilizes the Otsu algorithm after removing the background of an X-ray image, constructs intensity-level maps, and uses them for segmenting the X-ray image. To verify the effectiveness of our method, we compared it with the existing 1-dimensional and 2-dimensional Otsu algorithms, and also the results by expert's naked eyes. The experimental result showed that our method achieved the more accurate extraction of pulmonary regions compared to the Otsu methods and showed the similar result as the naked eye's one.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.1-9
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• 2008

In this paper, to extract object regions in stereo image, we propose an enhanced algorithm that extracts objects combining both of brightness information and disparity information. The approach that extracts objects using both has been studied by Ping and Chaohui. In their algorithm, the segmentation for an input image is carried out using the brightness, and integration of segmented regions in consideration of disparity information within the previously segmented regions. In the regions where the brightness values between object regions and background regions are similar, however, the segmented regions probably include both of object regions and background regions. It may cause incorrect object extraction in the merging process executed in the unit of the segmented region. To solve this problem, in proposed method, we adopt the merging process which is performed in pixel unit. In addition, we perform the bi-directional stereo matching process to enhance reliability of the disparity information and supplement the disparity information resulted from a single directional matching process. Further searching for disparity is decided by edge information of the input image. The proposed method gives good performance in the object extraction since we find the disparity information that is not extracted in the traditional methods. Finally, we evaluate our method by experiments for the pictures acquired from a real stereoscopic camera.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.221-221
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• 2013

Vertical LED (VLED) has been recognized as a way to obtain the high-power LED due to their advantages [1]. However, approximately 4% of the light generated from the active region is extracted, if the light extraction from side walls and back side is neglected because of Fresnel reflection (FR) and total internal reflection (TIR) [2,3]. In this study, the optical simulation of the VLED with the various microstructures was performed. Among them, the microlens having the diameter of 3 ${\mu}m$ and the height of 1.5 ${\mu}m$ shown the best result was chosen, and then, optimized microlens was formed on a GaN template using conventional semiconductor process. Various microstructures were proposed to improve the light extraction efficiency (LEE) of the VLED for the simulation. The LEE was simulated using LightTools based on a Monte Carlo ray tracing. The microstructures with hemisphere, cone, truncated and cylinder pattern having diameter of 3 ${\mu}m$ were employed on the top layer of the VLED respectively. The improvement of the LEE by using the microstructure is 87% for the hemisphere, 77% for the cone, 53% for the truncated, 21% for the cylinder, compared with the LEE of the flat surface at the reflectance of 85%. The LEE was increased by 88% at the height of 1.5 ${\mu}m$, compared with the LEE of the flat surface. We found that the microlens on the top layer is the most suitable for increasing the LEE. In order to apply the proposed microlens on n-GaN surface, we fabricated microlens on a GaN template. A photoresist array having hexagonal-closed packed microlens was fabricated on the GaN template. Then, optimization of etching the GaN template was performed using a dry etching process with ICP-RIE. The dry etching carried out using a gas mixture of Cl2 and Ar, each having a flow rate of 16 sccm and 10 sccm, respectively with RF power of 50 W, ICP power of 900 W and chamber pressure of 2 mTorr was the optimum etching condition as shown in Fig. 2(a).

• The Journal of the Korean dental association
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• v.15 no.3
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• pp.199-204
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• 1977

The patient, 19 years old female, complained of protrusion of upper and lower anterior teeth. Teeth lining was good except slight crowding in lower anterior teeth. Teeth lining was good except slight crowding in lower incisors, but distocclusion in the region of right buccal segment was present. Cephalometric analysis revealed normal relation between maxilla and cranial base. The labial inclination of upper and lower anterior teeth was severe, so diagnosed as bialveolar protrusion case. She was treated by means of multibanded system under the extraction of four first bicuspids. After 1 year and 4 months. She gained good interdigitation of buccal segments and attractive facial profile because the labioversion of incisors was reduced properly.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.721-723
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• 2004

최근 가상환경에서 아바타의 활용이 빠르게 증가하면서 아바타 애니메이션에 대한 연구가 활발히 진행되고 있다. 특히 아바타의 사람과 같은 자연스러운 얼굴 애니메이션(Facial Animation)은 사용자에게 아바타가 살아 있는 듯한 느낌(Life-likeness)과 사실감(Believability)을 심어주어 보다 친숙한 인터페이스로 활용될 수 있다. 이러한 얼굴 애니메이션 생성을 위해 얼굴의 특징 점을 추출하는 기법이 끊임없이 이루어져 왔다. 그러나 지금까지의 연구는 실시간으로 사람 얼굴로부터 모션을 생성하고 이를 바로 3D 얼굴 모델에 적용 및 모션 라이브러리를 구축하기 위한 최적화된 알고리즘 개발에 대한 연구가 미흡하였다. 본 논문은 실제 사랑 얼굴 모델로부터 실시간으로 특징 점 인식을 통한 애니메이션 적용 및 라이브러리 생성 기법에 대친 제안한다. 제안 기법에서는 빠르고 정확한 특징 점 추출을 위하여 색 정보를 가공하여 얼굴 영역을 추출해내고 이를 영역 분할하여 필요한 특징 점을 추출하였으며, 자연스러운 모션 생성을 위하여 에러 발생 시 대칭점을 이용한 복구 알고리즘을 개발하였다. 본 논문에서는 이와 같은 색 정보 기반의 영역분할 및 영역 대칭 기법을 제시하여 실시간으로 끊김이 없고 자연스러운 얼굴 모션 라이브러리를 생성 및 적용하였다.