• Journal of Food Hygiene and Safety
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• v.33 no.1
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• pp.71-76
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• 2018

Norovirus is a leading cause of sporadic pathogenic non-bacterial gastroenteritis worldwide. For the detection of norovirus, reverse transcription real-time PCR (RT qPCR) has quickly become a major tool due to its sensitivity and specificity. However, accurate viral RNA extraction methods are essential for RT qPCR analysis. TRIzol reagents are used to extract RNA from biological materials and are therefore widely used for norovirus RNA extraction. In this study, the yield of viral RNA extraction using TRIzol from genogroup II (GII) among the human norovirus genogroup I (GI) and GII, and murine norovirus (GV) depended on the pH of the virus sample solution. The yield of RNA extraction was higher at the alkaline pH than in the acidic region compared with the Ct (threshold cycle) value of the real-time PCR. From the results of this study, it was found that the pH condition is very important for the quantitative analysis of norovirus by extracting GII RNA using TRIzol.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.49-57
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• 2011

Extraction of regions of interest (ROIs) is the first and important step for the applications in computer vision and affects the rest of the application process. However, ROI extraction can be easily affected by the environment such as illumination, camera, etc. Many applications adopt problem-specific knowledge and/or post-processing to correct the error occurred in ROI extraction. In this paper, proposed is a robust framework that could overcome the environmental change and is independent from the rest of the process. The proposed framework uses a differential image and a color distribution to extract ROIs. The color distribution can be learned on-line, which make the framework to be robust to environmental change. Even more, the components of the framework are independent each other, which makes the framework flexible and extensible. The usefulness of the proposed framework is demonstrated with the application of hand region extraction in an image sequence.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.181-188
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• 2012

An effective extraction method for extracting a coated tongue is proposed in this paper, which is used as the diagnostic criteria in the tongue diagnosis. Proposed method uses the fluorescence response characteristics of the coated tongue that is occurred by using the ultraviolet light. Specially, this method can solved the previous problems including the issue in the limits of the diagnosis environment and in the objectivity of the diagnosis results. In our method, original tongue image is acquired by using the ultraviolet light, and binarization is performed by thresholding a valley-points in the histogram that corresponds to the color difference of tongue body and tongue coating. Final view image is presented to the oriental doctor, after applying the canny-edge algorithm to the binary image, and edge image is added to the original image. In order to evaluate the performance of the our proposed method, after building a various tongue image, we compared the true region of coated tongue by the oriental doctor's hand with the extracted region by the our method. As a result, the proposed method showed the average 87.87% extraction ratio. The shape of the extracted coated tongue region showed also significantly higher similarity.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.39-46
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• 2007

Research on human identification in ubiquitous environment has recently attracted a lot of attention. As one of those research, gait recognition is an efficient method of human identification using physical features of a walking person at a distance. In this paper, we present a human shape extraction and tracking for gait recognition using geodesic active contour models(GACMs) combined with mean shift algorithm The active contour models (ACMs) are very effective to deal with the non-rigid object because of its elastic property. However, they have the limitation that their performance is mainly dependent on the initial curve. To overcome this problem, we combine the mean shift algorithm with the traditional GACMs. The main idea is very simple. Before evolving using level set method, the initial curve in each frame is re-localized near the human region and is resized enough to include the targe region. This mechanism allows for reducing the number of iterations and for handling the large object motion. The proposed system is composed of human region detection and human shape tracking modules. In the human region detection module, the silhouette of a walking person is extracted by background subtraction and morphologic operation. Then human shape are correctly obtained by the GACMs with mean shift algorithm. In experimental results, the proposed method show that it is extracted and tracked efficiently accurate shape for gait recognition.

• Korean Journal of Materials Research
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• v.15 no.10
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• pp.626-631
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• 2005

GaN-related compound semiconductors were grown on the corrugated interface substrate using a metalorganic chemical vapor deposition system to increase the optical power of white LEDs. The patterning of substrate for enhancing the extraction efficiency was processed using an inductively coupled plasma reactive ion etching system and the surface morphology of the etched sapphire wafer and that of the non-etched surface were investigated using an atomic force microscope. The structural and optical properties of GaN grown on the corrugated interface substrate were characterized by a high-resolution x-ray diffraction, transmission electron microscopy, atomic force microscope and photoluminescence. The roughness of the etched sapphire wafer was higher than that of the non-etched one. The surface of III-nitride films grown on the hemispherically patterned wafer showed the nano-sized pin-holes that were not grown partially. In this case, the leakage current of the LED chip at the reverse bias was abruptly increased. The reason is that the hemispherically patterned region doesn't have (0001) plane that is favor for GaN growth. The lateral growth of the GaN layer grown on (0001) plane located in between the patterns was enhanced by raising the growth temperature ana lowering the reactor pressure resulting in the smooth surface over the patterned region. The crystal quality of GaN on the patterned substrate was also similar with that of GaN on the conventional substrate and no defect was detected in the interface. The optical power of the LED on the patterned substrate was $14\%$ higher than that on the conventional substrate due to the increased extraction efficiency.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.5
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• pp.493-500
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• 2009

An ultrasonic signal processing algorithm was developed for extracting the information of cracks generated around the keyway of a turbine rotor disk. B-scan images were obtained by using keyway specimens and an ultrasonic scan system with x-y position controller. The B-scan images were used as input images for 2-Dimensional signal processing, and the algorithm was constructed with four processing stages of pre-processing, crack candidate region detection, crack region classification and crack information extraction. It is confirmed by experiments that the developed algorithm is effective for the quantitative evaluation of cracks generated around the keyway of turbine rotor disk.

• Journal of Food Hygiene and Safety
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• v.18 no.1
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• pp.6-13
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• 2003

Various kinds of genetically modified organisms (GMO) and processed foods have been developed during recent years. Genetically modified organisms can be classified into several groups as their development methods. Generally, GMO has three foreign DNA regions such as gene expression adjustment region(Promoter), termination region (terminator) and structure gene. Detection of these regions can be done particularly by polymerase chain reaction (PCR). PCR-based detection can virtually be performed for any GMO within short of time. The most important prerequisite for the application of PCR-based detection is to decide abstraction method of efficient nucleic acids. Specially, in the case of processed food, because nucleic acids of foodstuffs are damaged by heat treatment (sterilization), pressure and fermentation, DNA must be extracted ken the samples prior to PCR analysis. Although many DNA extraction protocols are available, they have rarely been compared in a comprehensive method. In this study low widely used commercial and non-commercial DNA extraction methods-DNeasy$^{TM}$, Wizard$^{TM}$, CTAB, phenol/chloroform system-were compared with respect to the quality and yield of nucleic acids and insertion genes.nes.

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.509-516
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• 2002

This paper proposes an efficient algorithm which recognizes the mixed document image consisting of the images, texts, tables, and straight lines. This system is composed of three steps. The first step is the detection of rotation angle for complementing skewed images, the second is detection of erasing an unnecessary background region and last is the classification of each component included in document images. This algorithm performs preprocessing of detecting rotation angles and correcting documents based on the detected rotation angles in order to minimize the error rate by skewness of the documentation. We detected the rotation angie using only horizontal and vertical components in document images and minimized calculation time by erasing unnecessary background region in the detecting process of component of document. In the next step, we classify various components such as image, text, table and line area included in document images. we applied this method to various document images in order to evaluate the performance of document recognition system and show the successful experimental results.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1323-1331
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• 2017

Despite the fact that the copyright has grown into a large-scale business, there are many constant problems especially in image copyright. In this study, we propose an automatic object extraction and classification system for the scanned educational book image by combining document image processing and intelligent information technology like deep learning. First, the proposed technology removes noise component and then performs a visual attention assessment-based region separation. Then we carry out grouping operation based on extracted block areas and categorize each block as a picture or a character area. Finally, the caption area is extracted by searching around the classified picture area. As a result of the performance evaluation, it can be seen an average accuracy of 83% in the extraction of the image and caption area. For only image region detection, up-to 97% of accuracy is verified.

• The Journal of the Acoustical Society of Korea
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• v.22 no.4
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• pp.286-292
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• 2003

Voice activity detection (VAD) is a process that separates the noise region from silence or noise region of input speech signal. Since unvoiced consonant signals have very similar characteristics to those of noise signals, it may result in serious distortion of unvoiced consonants, or in erroneous noise estimation to can out VAD without paying special attention on unvoiced consonants. In this paper, we propose a method to extract in an explicit way the boundaries between unvoiced consonant and noise in fluent speech so that more exact VAD could be performed. The proposed method is based on histogram in frequency domain which was successfully used by Hirsch for noise estimation, and a1so on similarity measure of frequency components between adjacent frames, To evaluate the performance of the proposed method, experiments on unvoiced consonant boundary extraction was performed on seven kinds of noisy speech signals of 10 ㏈ and 15 ㏈ SNR respectively.