• Journal of Conservation Science
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• v.37 no.3
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• pp.220-231
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• 2021

The use of digital copies of film-based analog images and the introduction of digital radiographic imaging systems using image plates gradually replace the non-destructive radiationirradiation method of Cultural Heritage. The quality of images obtained from this technique is affected by conditions such as tube voltage, tube current, and exposure time, type of image acquisition medium, distance of the artifacts from the image acquisition medium, and thickness of artifacts. In this study, we evaluated the grayscale image obtained using GE's Computed Radiograhpy (CR) imaging system, the transmission characteristics of the X-ray source for each tree type (pine, chestnut, sawtooth oak, ginkgo) used in wooden Cultural Heritage, and the signal-to-noise ratio (SNR) and contrast. The GE's CR imaging were analyzed using the Duplex wire image quality indicator, line-pair gauges.

• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.21-28
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• 2009

Color polarity classification is a process to determine whether the color of text is bright or dark and it is prerequisite task for text extraction. In this paper we propose a color polarity method to extract text region. Based on the observation for the text and background regions, the proposed method uses the ratios of sizes and standard deviations of bright and dark regions. At first, we employ Otsu's method for binarization for gray scale input region. The two largest segments among the bright and the dark regions are selected and the ratio of their sizes is defined as the first measure for color polarity classification. Again, we select the segments that have the smallest standard deviation of the distance from the center among two groups of regions and evaluate the ratio of their standard deviation as the second measure. We use these two ratio features to determine the text color polarity. The proposed method robustly classify color polarity of the text. which has shown by experimental result for the various font and size.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.67-77
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• 2016

In this paper, we propose an algorithm for open/closed eye detection based on modified Hausdorff distance. The proposed algorithm consists of two parts, face detection and open/closed eye detection parts. To detect faces in an image, MCT (Modified Census Transform) is employed based on characteristics of the local structure which uses relative pixel values in the area with fixed size. Then, the coordinates of eyes are found and open/closed eyes are detected using MHD (Modified Hausdorff Distance) in the detected face region. Firstly, face detection process creates an MCT image in terms of various face images and extract criteria features by PCA(Principle Component Analysis) on offline. After extraction of criteria features, it detects a face region via the process which compares features newly extracted from the input face image and criteria features by using Euclidean distance. Afterward, the process finds out the coordinates of eyes and detects open/closed eye using template matching based on MHD in each eye region. In performance evaluation, the proposed algorithm achieved 94.04% accuracy in average for open/closed eye detection in terms of test video sequences of gray scale with 30FPS/$320{\times}180$ resolution.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.545-559
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• 2020

In this paper, we propose a content creation framework that enables users without programming experience to easily create interactive media content that responds to user gestures. In the proposed framework, users define the gestures they use and the media effects that respond to them by numbers, and link them in a text-based configuration file. In the proposed framework, the interactive media content that responds to the user's gesture is linked with the dynamic projection mapping module to track the user's location and project the media effects onto the user. To reduce the processing speed and memory burden of the gesture recognition, the user's movement is expressed as a gray scale motion history image. We designed a convolutional neural network model for gesture recognition using motion history images as input data. The number of network layers and hyperparameters of the convolutional neural network model were determined through experiments that recognize five gestures, and applied to the proposed framework. In the gesture recognition experiment, we obtained a recognition accuracy of 97.96% and a processing speed of 12.04 FPS. In the experiment connected with the three media effects, we confirmed that the intended media effect was appropriately displayed in real-time according to the user's gesture.

• Journal of Broadcast Engineering
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• v.15 no.4
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• pp.474-486
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• 2010

In this paper, we propose a new method for detection moving object contour using spatial and temporal edge. In general, contour pixels of the moving object are likely present around pixels with high gradient value along the time axis and the spatial axis. Therefore, we can detect the contour of the moving objects by finding pixels which have high gradient value in the time axis and spatial axis. In this paper, we introduce a new computation method, termed as temporal edge, to compute an gradient value along the time axis for any pixel on an image. The temporal edge can be computed using two input gray images at time t and t-2 using the Sobel operator. Temporal edge is utilized to detect a candidate region of the moving object contour and then the detected candidate region is used to extract spatial edge information. The final contour of the moving object is detected using the combination of these two edge information, which are temporal edge and spatial edge, and then the post processing such as a morphological operation and a background edge removing procedure are applied to remove noise regions. The complexity of the proposed method is very low because it dose not use any background scene and high complex operation, therefore it can be applied to real-time applications. Experimental results show that the proposed method outperforms the conventional contour extraction methods in term of processing effort and a ghost effect which is occurred in the case of entropy method.

• Journal of Platform Technology
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• v.8 no.3
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• pp.10-21
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• 2020

Partial discharge occurs a lot in high-voltage power equipment such as switchgear, transformers, and switch gears. Partial discharge shortens the life of the insulator and causes insulation breakdown, resulting in large-scale damage such as a power outage. There are several types of partial discharge that occur inside the product and the surface. In this paper, we design a predictive model that can predict the pattern and probability of occurrence of partial discharge. In order to analyze the designed model, learning data for each type of partial discharge was collected through the UHF sensor by using a simulator that generates partial discharge. The predictive model designed in this paper was designed based on CNN during deep learning, and the model was verified through learning. To learn about the designed model, 5000 training data were created, and the form of training data was used as input data for the model by pre-processing the 3D raw data input from the UHF sensor as 2D data. As a result of the experiment, it was found that the accuracy of the model designed through learning has an accuracy of 0.9972. It was found that the accuracy of the proposed model was higher in the case of learning by making the data into a two-dimensional image and learning it in the form of a grayscale image.

• Sim-seong Yeon-gu
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• v.28 no.2
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• pp.139-153
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• 2013

Psychological typology in analytic psychology is used not only for ascertaining the attitude or function of the conscious ego, but also as one blueprint for the individuation process. We all know the need to emphasize an awareness of the deployment and development of the superior function, the secondary function, the third function and the inferior function for the individuation process. This study has the goal of refining our awareness of this deployment and development of typological functions. The questionnaires of the Myers-Briggs Type Inventory and the Gray Wheelwrights Jungian Type Survey use the method of a forced-choice questionnaire, on the assumption of a bi-polarity hypothesis. But the questionnaire of the Singer-Loomis Type Deployment Inventory uses the Likert scale. It is able to show the deployment of the superior function, the secondary function, the third function and the inferior function visibly. It allows us to test the subject at stated periods for his/her development or change of psychological typology. The Singer-Loomis Type Deployment Inventory is a statistically superior method for showing Jung's psychological typology relative to both the Myers-Briggs Type Inventory and the Gray Wheelwrights Jungian Type Survey. I have studied how the original authors of The Singer-Loomis Type Deployment Inventory understood Jung's psychological typology. I produced the reliability and the item-discrimination power of the Korean Version of the Singer-Loomis Type Deployment Inventory. On the basis of this study, I produced the revised Korean version 1 of Singer-Loomis Type Deployment Inventory.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.385-392
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• 2023

Caroli's disease is a fibrocystic liver disease. Autosomal recessive disorder is characterized by congenital multiple dilatation of the bile duct. Computerized tomography, magnetic resonance imaging, cholangiography and ultrasound are among the methods for diagnosing caroli disease. Computerized tomography is essential for detecting and distinguishing fibroplastic liver disease and is useful for determining intrahepatic bile duct dilatation. However, awareness of the possible side effects of using contrast mediums is necessary. A typical method of magnetic resonance cholangiography is used for magnetic resonance imaging. A non-invasive examination can reduce the pain of the patient, and the anatomical structure of the bile pancreatic duct and the presence or absence of lesions can be easily and quickly observed. Biliary contrast is an effective diagnostic method that can directly visualize various cystic dilatations throughout the enlarged bile duct. However, since this procedure is also an invasive procedure, it is recommended not for diagnosis but for treatment purposes. Ultrasonography can confirm similar findings to computerized tomography. The hepatic artery root is difficult to prove with conventional grayscale ultrasound. However, it is of clinical value in that it can not only describe dilated bile ducts with vascular roots in the tube but also easily identify color Doppler signals in the tube. With the development of video diagnostics, early diagnosis has become possible through computerized tomography, magnetic resonance imaging, cholangiography, and ultrasound. In order to further contribute to the development of video diagnostics so that long-term prognosis can be improved after treatment through early diagnosis, we examined what aspects of each test's caroli disease appear.