• 전자공학회논문지 IE
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• v.48 no.1
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• pp.51-56
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• 2011

In this paper, a variety of digital image processing technique was applied to improve the quality of medical images which is a chest CR image. And the image quality was performed. On the other hand, the high-frequency emphasis filtering and the histogram equalization were realized by MATLAB programs to better the contrast of the chest CR image. As a result of simulation, the sharpness of the original image was elevated by the high-frequency emphasis filtering and the histogram equalization. To evaluate the degree which is improved the image quality by the digital image processing, the subjective evaluation is used by the observation of the image. The sensitivity which is the probability to find a signal or a lesion is calculated. The sensitivity of the image performed the high-frequency emphasis filtering and the histogram equalization became more improved than that of the original and the digital image processing performed in the medical image improved the quality of the image.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.12
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• pp.1039-1047
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• 2015

Contact type sensors (e.g., displacement sensor and strain gauge) were typically used to evaluate the safety and mechanical properties in machines and construction. However, those contact type sensors have been constrained because of measurement problems such as surface roughness, temperature, humidity, and shape. The Digital Image Correlation (DIC) measurement system is a vision measurement system. This measurement system uses the taken image using a CCD camera and calculates the image correlation between the reference image and the deformed image under external force to measure the displacement and strain rates. In this paper, we discuss methods to improve the measurement precision of the digital image correlation measurement system. A tensile test was conducted to compare the precision improvement effects, by using the universal test machine and the DIC measurement system, with the use of subpixel algorithms, i.e., the Coarse Fine Search (CFS) algorithm and the Peak Finding (PF) algorithm.

• Journal of Korean society of Dental Hygiene
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• v.9 no.1
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• pp.113-123
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• 2009

This study was undertaken evaluate the general image for dental hygienist. A questionnaire was given to each Dentist, the staff of dental. 65 Dentist, 145 the staff of dental were included in the subjects between Jul. 1 and Oct. 30, 2008. The collected data was analysed by the SPSS Win 12.0/PC using frequency, percentage, mean, standard deviation, chi-square, t-test, ANOVA. The image for the dental hygienist was analyzed by 28 items. As a result of analysis on image of dental hygienist, The Dentist's group and staff's group, both appreciated positive image that explain process of treatment to patient very well, having professional knowledge and experienced skill, carries on an effective and valuable work. give a confidenced to patient. These group also gave negative image in the aspect that the dental hygienist is stressful job, handmaid of Dentist, participate of decided something for dental clinic, having association activities. It is necessary for dental hygienist by oneself development ability through science congress variety major and acquirement new technology, exchange information, interchange activities, and association of dental hygienist should efforts for growing up image through mass media.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.5
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• pp.476-486
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• 2022

Synthetic dynamic infrared image generation from the given virtual environment is being the primary goal to simulate the output of the infra-red(IR) camera installed on a vehicle to evaluate the control algorithm for various search & reconnaissance missions. Due to the difficulty to obtain actual IR data in complex environments, Artificial intelligence(AI) has been used recently in the field of image data generation. In this paper, CycleGAN technique is applied to obtain a more realistic synthetic IR image. We added the Structural Similarity Index Measure(SSIM) loss function to the L1 loss function to generate a more realistic synthetic IR image when the CycleGAN image is generated. From the simulation, it is applicable to the guided-missile flight simulation tests by using the synthetic infrared image generated by the proposed technique.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.147-154
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• 2020

In this study, four types of composite added filtration (aluminum, nickel, copper, and zinc) were combined for each thickness to evaluate dose reduction and optimal images due to X-ray attenuation. To evaluate dose and image quality. X-ray generators, Dose Area Product(DAP) and ICY programs with RQR9 standard quality were used. In the image quality evaluation element (PSNR, RMSE, SSIM), only images with PSNR value of 30 dB or more were analyzed. As a result, the best combination in dose evaluation was 3 mmAl + 0.6 mmNi (0.16µGy㎡), and the best filter in image quality evaluation was 0.9 mmAl (PSNR 34.24dB, RMSE 79.52, SSIM 0.24). In this study, the dose aspect and the image quality aspect are mentioned, So it is considered that further studies on patient's exposure dose and optimal image will be needed in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.1
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• pp.1-12
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• 2012

Even though the semi-actuated signal control system based on image detectors has been spreading in Korea, any appropriate methods to evaluate the effectiveness and performance has not been established yet. Therefore, this research effort is aiming at developing a systematic method for evaluating the effectiveness and performance of the semi-actuated signal control system based on image detectors. To this end, this research firstly established measures of effectiveness(MOEs) and associated information to be surveyed from fields. Secondly, this research provided a procedure and methodology to evaluate any improvements due to the introduction of a semi-actuated signal control system based on image detectors. The developed methodology was examined at a case study site located in the city of Paju. As a result of the evaluation, the MOEs including traffic throughput, travel speeds, split usage rate, progression rate, etc. showed positive improvements though individual signalized intersections as well as coordinated corridors.

• Smart Media Journal
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• v.12 no.9
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• pp.45-59
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• 2023

Weakly supervised object localization (WSOL) is a task of localizing an object in an image using only image-level labels. Previous studies have followed the conventional class activation mapping (CAM) pipeline. However, we reveal the current CAM approach suffers from problems which cause original CAM could not capture the complete defects features. This work utilizes a convolutional neural network (CNN) pretrained on image-level labels to generate class activation maps in a multi-scale manner to highlight discriminative regions. Additionally, a vision transformer (ViT) pretrained was treated to produce multi-head attention maps as an auxiliary detector. By integrating the CNN-based CAMs and attention maps, our approach localizes defective regions without requiring bounding box or pixel-level supervision during training. We evaluate our approach on a dataset of apple images with only image-level labels of defect categories. Experiments demonstrate our proposed method aligns with several Object Detection models performance, hold a promise for improving localization.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.719-722
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• 2019

Gamma-ray images generally suffer from a lot of noise because of low photon detection in the gamma camera system. The purpose of this study is to improve the image quality in gamma-ray images using a gamma camera system with a fast nonlocal means (FNLM) noise reduction algorithm with an acceleration function. The designed FNLM algorithm is based on local region considerations, including the Euclidean distance in the gamma-ray image and use of the encoded information. To evaluate the noise characteristics, the normalized noise power spectrum (NNPS), contrast-to-noise ratio (CNR), and coefficient of variation (COV) were used. According to the NNPS result, the lowest values can be obtained using the FNLM noise reduction algorithm. In addition, when the conventional methods and the FNLM noise reduction algorithm were compared, the average CNR and COV using the proposed algorithm were approximately 2.23 and 7.95 times better than those of the noisy image, respectively. In particular, the image-processing time of the FNLM noise reduction algorithm can achieve the fastest time compared with conventional noise reduction methods. The results of the image qualities related to noise characteristics demonstrated the superiority of the proposed FNLM noise reduction algorithm in a gamma camera system.

• Annual Conference of KIPS
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• 2010.11a
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• pp.625-628
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• 2010

This paper proposes a novel feature extraction method for unsupervised multispectral image segmentation based in one dimensional combined neighborhood differences (1D CND). In contrast with the original CND, which is applied with traditional image, 1D CND is computed on a single pixel with various bands. The proposed algorithm utilizes the sign of differences between bands of the pixel. The difference values are thresholded to form a binary codeword. A binomial factor is assigned to these codeword to form another unique value. These values are then grouped to construct the 1D CND feature image where is used in the unsupervised image segmentation. Various experiments using two LANDSAT multispectral images have been performed to evaluate the segmentation and classification accuracy of the proposed method. The result shows that 1D CND feature outperforms the spectral feature, with average classification accuracy of 87.55% whereas that of spectral feature is 55.81%.

• English Language & Literature Teaching
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• v.18 no.2
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• pp.1-20
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• 2012

This study aims to propose using English reading strategies to enhance Intercultural Communicative Competence (ICC) for EFL learners. The study recruited college-level participants who were enrolled in a general English reading course (N=30) and administrated the surveys with a Repeated Measures Design (RMD). In the survey, an intercultural sensitivity scale and metacognitive reading strategies inventory were conducted for comparison. During the instruction, participants were asked to use the R.I.D.E.R. (i.e. Read, Image, Describe, Evaluate, and Repeat) strategy for visualization of text, which is aimed at facilitating the use of metacognitive reading strategies. In the results, participants showed a statistically significant increase both in the intercultural sensitivity level and the use of metacognitive reading strategies after the practice of R.I.D.E.R for one semester. Further analysis was appended to the results by the correlation and regression analysis, and proposed that participants benefit their development of intercultural sensitivity from the use of metacognitive reading strategies. Therefore, the study suggests that implementing metacognitive reading strategies facilitates college EFL readers to increase their cultural sensitivity, which empowers ICC through English reading (176words).