• Journal of KIISE:Databases
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• v.28 no.4
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• pp.723-731
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• 2001

As XML has become and emerging standard for information exchange on the World Wide Web it has gained attention in database communities of extract information from XML seen as a database model. Data in XML can be mapped to semistructured dta model based on edge-labeled graph and queries can be processed against it Here we propose new query optimization techniques using DTDs(Document Type Definitions) which have the schema information about XML data. Our techniques reduce traditional index techniques Also, as they preserve source database structure, they can process many kinds of complex queries. we implemented our techniques and provided preliminary performance results.

• The KIPS Transactions:PartB
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• v.18B no.3
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• pp.117-130
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• 2011

The purpose of this study is to produce a better way to detect crossroad accidents, which involves an efficient method to produce background images in consideration of object movement and preserve/demonstrate the candidate accident region. One of the prior studies proposed an employment of traffic signal interval within crossroad to detect accidents on crossroad, but it may cause a failure to detect unwanted accidents if any object is covered on an accident site. This study adopted inverse perspective mapping to control the scale of object, and proposed different ways such as producing robust background images enough to resist surrounding noise, generating candidate accident regions through information on object movement, and by using edge information to preserve and delete the candidate accident region. In order to measure the performance of proposed algorithm, a variety of traffic images were saved and used for experiment (e.g. recorded images on rush hours via DVR installed on crossroad, different accident images recorded in day and night rainy days, and recorded images including surrounding noise of lighting and shades). As a result, it was found that there were all 20 experiment cases of accident detected and actual effective rate of accident detection amounted to 76.9% on average. In addition, the image processing rate ranged from 10~14 frame/sec depending on the area of detection region. Thus, it is concluded that there will be no problem in real-time image processing.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.5
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• pp.465-473
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• 2002

Images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in radiography is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in reading. We have proposed adaptive weighted median(AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by homogeneous factor(HF). Homogeneous factor(HF) from the quantum noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the detection systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by visual C++ language on a IBM-PC Pentium 550 for testing purposes, the effects and results of the noise filtering were proposed by comparing with images of the other existing filtering methods.

• Journal of the Korea Computer Graphics Society
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• v.14 no.3
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• pp.1-9
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• 2008

This paper presents a novel optimization-based saliency-preserving method for converting color images to grayscale in a manner consistent with conventional approaches of black-and-white photographers. In black-and-white photography, a colored filter called a contrast filter has been commonly employed on a camera to lighten or darken selected colors. In addition, local exposure controls such as dodging and burning techniques are typically employed in the darkroom process to change the exposure of local areas within the print without affecting the overall exposure. Our method seeks a digital version of a conventional contrast filter to preserve visually-important image features. Furthermore, conventional burning and dodging techniques are addressed, together with image similarity weights, to give edge-aware local exposure control over the image space. Our method can be efficiently optimized on GPU. According to the experiments, CUDA implementation enables 1 megapixel color images to be converted to grayscale at interactive frames rates.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1235-1238
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• 2004

Thresholding has been used to reduce the number of gray values in images. Typically, a single threshold value has been used, resulting in two gray level images. Image reduction of one single threshold value, however, may lose too much of the high-frequency edge information. Thus, dynamic thresholding that uses a different threshold for each pixel is preferred instead of using a single threshold value. Dynamic thresholding can preserve high frequency details as well as reduce the size of images. Since it takes long time to perform existing software dynamic thresholding in an embedded system, this paper proposes and implements a circuit by using a FPGA in order to perform a real-time dynamic thresholding,. The proposed circuit consists of two counters, and threshold look-up table, and control unit. The values of two counters determine each pixel position, the threshold look-up table converts each pixel value into other value, and the control unit generates necessary control signals. On arriving from a camera to the proposed circuit, each pixel is compared with its threshold value and is converted into other gray value. An image processing system by using the proposed circuit will be implemented and some experiments will be performed.

• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.21-29
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• 2007

Anisotropic diffusion is one of the widely used techniques in the field of image segmentation. In the conventional anisotropic diffusion [1]-[6], usually 4-neighborhood directions are used: north, south, west and east, except the image diagonal directions, which results in the loss of image details and causes false contours. Existing methods for image segmentation using conventional anisotroplc diffusion can't preserve contour information, or noises with high gradients become more salient as the umber of times of the diffusion increases, resulting in over-segmentation when applied to watershed. In this paper, to overcome the shortcoming of the conventional anisotropic diffusion method, a new arusotropic diffusion method based on diagonal edges is proposed. And a method of watershed segmentation is applied to the proposed method. Experimental results show that the process time of the proposed method including diagonal edges over conventional methods can be up to 2 times faster and the Circle image quality improvement can be better up to $0.45{\sim}2.33(dB)$. Experiments also show that images are segmented very effectively without over segmentation.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.401-404
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• 2006

Mean shift procedure is applied for the data points in the joint spatial-range domain and achieves a high quality. However, a color image is segmented differently according to the inputted spatial parameter or range parameter and the demerit is that the image is broken into many small regions in case of the small parameter. In this paper, to improve this demerit, we propose the method that groups similar regions using region merging method for over-segmented images. The proposed method converts a over-segmented image in RGB color space into in HSI color space and merges similar regions by hue information. Here, to preserve edge information, the proposed method use by merging constraints to decide whether regions is merged or not. After then, we merge the regions in RGB color space for non-processed regions in HSI color space. Experimental results show the superiority in region's segmentation results.

• Clinical and Experimental Reproductive Medicine
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• v.45 no.1
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• pp.44-47
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• 2018

Onco-testicular sperm extraction is used to preserve fertility in patients with bilateral testicular tumors and azoospermia. We report the case of a testicular tumor in the solitary testis of a patient who had previously undergone successful contralateral orchiectomy and whose sperm was preserved by onco-testicular sperm extraction. A 35-year-old patient presented with swelling of his right scrotum that had lasted for 1 month. His medical history included a contralateral orchiectomy during childhood. Ultrasonography revealed a mosaic echoic area in his scrotum, suggesting a testicular tumor. The lesion was palpated within the normal testicular tissue along its edge and semen analysis showed azoospermia. Radical inguinal orchiectomy and onco-testicular sperm extraction were performed simultaneously. Motile spermatozoa were extracted from normal seminiferous tubules under microscopy and were frozen. Eventual intracytoplasmic sperm injection using the frozen spermatozoa is planned. Onco-testicular sperm extraction is an important fertility preservation method in patients with bilateral testicular tumors or a history of a previous contralateral orchiectomy.

• Archives of Plastic Surgery
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• v.38 no.5
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• pp.649-654
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• 2011

Purpose: Split-or full-thickness skin grafts are used to reconstruct palmar skin and soft tissue defects after trauma or to release burn scar contracture on the hand. Glabrous skin defects should be substituted with similar skin to preserve function and aesthetics. The authors report their experiences with a technique that uses a full-thickness graft taken from glabrous skin on the ulnar edge of the palm for the reconstruction of soft tissue defects of the hand. Methods: During a three-year period from 2007 to 2010, 22 patients with burn scar contracture and 12 patients with post-traumatic skin defects on their hands were treated with full-thickness skin graft operations. The palmar skin and soft tissue defects after release of burn scar contracture or debridement of post-traumatic wounds were reconstructed with full-thickness skin grafts harvested from the ulnar border of their palms. All donor-site wounds were primarily closed. Results: The followup periods ranged from 3 to 25 months. Contractures of the hand were corrected without recurrence, and the grafts showed relatively good contour and color match to the adjacent fields. There were no reported complications such as significant color change or hypertrophic scarring. The grafted skin showed an average 5.9 mm static two-point discrimination obtained in fingertip reconstruction cases, indicating satisfactory reinnervation. Conclusion: Glabrous full-thickness grafts harvested from the palmar ulnar border is a very useful way of reconstructing soft tissue defects on hands, including fingertips, for function restoration, favorable aesthetic results, and low donor-site morbidity.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.471-476
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• 2024

With the spread of various smart devices and computing devices, big data generation is occurring widely. Machine learning is an algorithm that performs reasoning by learning data patterns. Among the various machine learning algorithms, the algorithm that attracts attention is deep learning based on neural networks. Deep learning is achieving rapid performance improvement with the release of various applications. Recently, among deep learning algorithms, attempts to analyze data using graph structures are increasing. In this study, we present a graph generation method for transferring to a deep learning network. This paper proposes a method of generalizing node properties and edge weights in the graph generation process and converting them into a structure for deep learning input by presenting a matricization We present a method of applying a linear transformation matrix that can preserve attribute and weight information in the graph generation process. Finally, we present a deep learning input structure of a general graph and present an approach for performance analysis.