• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.155-163
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• 2003

마이크로어레이를 이용한 발현실험이 기하급수적으로 늘어남에 따라 마이크로어레이이미지를 자동으로 처리하는 기술에 대한 요구가 커지고 있고, 이에 대한 연구도 많아지고 있다. 마이크로어레이 이미지를 자동으로 처리하기 위해서는 각 이미지가 가지고 있는 스팟 패턴를 알아보고, 자동화 정도를 측정할 수 있는 품질평가함수가 필요하다. 우리는 본 논문에서 마이크로어레이 이미지 분석의 자동화에 대한 평가를 도와주는 스팟 패턴의 품질평가함수(quality measure)를 정의하고, 각 실험이 얼마나 잘 이루어졌는지를 예측할 수 있는 품질제어평가함수(quality control measure)를 정의한다. 또한 마이크로어레이 실험과 이미지에 대한 품질을 평가하기 위해서 이미지내의 블럭들과 스팟들에 대한 통계량을 이용하고, 스팟들의 발현값에 대한 정확도를 측정하기 위한 품질평가함수들을 정의한다. 이러한 품질평가함수의 측정을 위해서 최대정규정점의 집합(maximal regular point set)과 메타그리드를 이용한다.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.4
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• pp.365-384
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• 2024

The development of scanning technology is accelerating for safer and more efficient automated inspection than human-based inspection. Research on automatically detecting facility damage from images collected using computer vision technology is also increasing. The pixel size, quality, and quantity of an image can affect the performance of deep learning or image processing for automatic damage detection. This study is a basic to acquire high-quality raw image data and camera performance of a mobile tunnel scanning system for automatic detection of damage based on deep learning, and proposes a method to quantitatively evaluate image quality. A test chart was attached to a panel device capable of simulating a moving speed of 40 km/h, and an indoor test was performed using the international standard ISO 12233 method. Existing image quality evaluation methods were applied to evaluate the quality of images obtained in indoor experiments. It was determined that the shutter speed of the camera is closely related to the motion blur that occurs in the image. Modulation transfer function (MTF), one of the image quality evaluation method, can objectively evaluate image quality and was judged to be consistent with visual observation.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10e
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• pp.475-477
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• 2002

이미지 압축을 위한 새로운 기법 중의 하나가 웨이블릿 변환이다. 웨이블릿 변환된 이미지는 이미지 전체의 중요 정보가 한쪽으로 치우치는 경향을 보인다. 그러므로 웨이블 이미지를 순차적으로 네트웍상에 전송한다면 중요 정보가 포함된 패킷에 손실이 발생할 경우 이미지의 품질에 치명적인 영향을 미친다. 본 논문에서는 전송된 웨이블릿 이미지의 품질을 보장하기 위한 새로운 패킷타이징 기법을 제안한다. 즉 주파수 부대역(frequency subband)을 여러 개의 블록으로 나누고, 이 블록들을 서로 다른 패킷에 삽입하여 패킷의 중요도를 분산하는 것이다. 또한 주파수대역이 가장 낮은 부대역 정보를 중복하여 전송함으로써 이미지 전체의 품질을 보장한다. 제안된 기법의 성능을 평가하기 위해 객관적인 성능평가 단위인 PSNR과 주관적인 이미지 분석을 수행하였다. 실험결과 제안된 기법의 성능이 순차적인 블록 패킷 기법에 비하여 PSNR에서 1～4 ㏈ 높았으며, 이미지의 선명도도 높음을 알 수 있었다.

• Journal of KIISE
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• v.42 no.10
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• pp.1294-1302
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• 2015

A lot of image quality assessment metrics that can precisely reflect the human visual system (HVS) have previously been researched. The Structural SIMilarity (SSIM) index is a remarkable HVS-aware metric that utilizes structural information, since the HVS is sensitive to the overall structure of an image. However, SSIM fails to deal with color difference in terms of the HVS. In order to solve this problem, the Structural and Hue SIMilarity (SHSIM) index has been selected with the Hue, Saturation, Intensity (HSI) model as a color space, but it cannot reflect the HVS-aware color difference between two color images. In this paper, we propose a new image quality assessment method for a color image by using a CIE Lab color space. In addition, by using a support vector machine (SVM) classifier, we also propose an optimization system for applying optimal metric according to the types of distortion. To evaluate the proposed index, a LIVE database, which is the most well-known in the area of image quality assessment, is employed and four criteria are used. Experimental results show that the proposed index is more consistent with the other methods.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.837-840
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• 2015

SSIM은 인간의 시각 체계가 이미지의 구조적 정보에 예민하다는 점을 이용하여 여러 가지 구조적 정보들의 유사성을 계산함으로써 이미지를 평가하는 대표적인 이미지 평가 기법이다. 하지만 SSIM은 컬러 이미지들에 대해 색 차이를 고려하지 못하는 문제가 있다. 이러한 문제를 해결하기 위해, HSI 색 공간을 활용한 SHSIM 기법이 제안되었으나 이 기법 또한 두 컬러 이미지 간 인지적인 색 차이를 충분히 반영하지는 못하고 있다. 본 논문에서는 CIE Lab 색 공간을 도입하여 대응 되는 픽셀들의 인지적 색 차이를 계산하여 이미지 평가에 활용하는 방법을 제안한다. 제안하는 기법의 성능을 평가하기 위해, 이미지 평가 분야에서 가장 많이 알려진 네 가지의 데이터베이스와 네 종류의 평가 기준들을 이용하였다. 실험 결과에서는 제안하는 기법이 다른 기법들보다 인간 시각 체계와 더 상관성이 높다는 것을 보여줌으로써 성능을 증명하였다.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.3
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• pp.265-280
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• 2014

In this study, the service image of the public library was investigated to the users of the public library, and basic data to improve the service image of the public library was also analyzed. In order to analyze public library service image, survey was conducted to 143 users of regional central library in Daejeon Metropolitan City. The results are as followed. First, reliability and publicity was the most highly rated and service satisfaction was the least highly rated. Second, when it was expressed with service quality image, there was no large difference. Third, reliability-providing useful information, publicity-fair treatment, and tangibles-convenient facility had positive images. On the other hand, access-good traffic condition, responsiveness-providing prompt new information, and tangibles-comfortable facility had negative images. Fourth, higher age group had lower mean value from teens to sixties.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.161-165
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• 2007

The process of selecting a small number of representative colors from an image of higher color resolution is called color image quantization. In a color quantization process, it is vet important to determine what colors should be preserve and the others not. In our study, by the idea of an image can be divided into interesting area and uninteresting area, we propose a color quantization method that preserves more colors in the interesting area of an image. We evaluated correctness of extracting interesting area and compared the quality of our method with the others.

• Journal of KIISE
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• v.44 no.9
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• pp.992-1004
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• 2017

To assess image quality accurately, an image quality assessment (IQA) metric is required to reflect the human visual system (HVS) properly. In other words, the structure, color, and contrast ratio of the image should be evaluated in consideration of various factors. In addition, as mobile embedded devices such as smartphone become popular, a fast computing speed is important. In this paper, the proposed IQA metric combines color similarity, gradient similarity, and phase similarity synergistically to satisfy the HVS and is designed by using optimized pooling and quantization for fast computation. The proposed IQA metric is compared against existing 13 methods using 4 kinds of evaluation methods. The experimental results show that the proposed IQA metric ranks the first on 3 evaluation methods and the first on the remaining method, next to VSI which is the most remarkable IQA metric. Its computing speed is on average about 20% faster than VSI's. In addition, we find that the proposed IQA metric has a bigger amount of correlation with the HVS than existing IQA metrics.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.567-569
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• 2023

GAN은 이미지 생성모델로서 이미지 공간에서 좋은 결과를 보여왔다. 우리는 이러한 GAN의 능력을 더욱 향상하기 위하여 본 연구에서 주파수 영역에서 이미지를 학습하고 생성하는 새로운 방법을 제안한다. 이를 위하여 먼저 학습데이터를 2D FFT로 주파수 영역으로 변환한 후 변환된 학습데이터를 GAN이 학습하게 한다. 학습 후에 GAN은 새로운 이미지를 생성하며 생성된 이미지를 2D IFFT하여 이미지 공간으로 변환한다. 이렇게 주파수 영역에서 이미지를 생성하는 방법은 이미지 공간에서 생성하는 방법보다 다양한 장점이 있다. 생성된 이미지의 품질을 평가하기 위하여 4개 데이터 셋에 4개의 평가지표를 사용하여 평가한 결과 주파수 영역에서 생성한 이미지가 IS, P&R, D&C 측면에서 더 좋은 것으로 평가되었다.

• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.213-220
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• 2021

With the continuing development of the global economy, the scale of international production and management of companies is expanding rapidly nowadays. As a result, it is increasingly important for multinational companies to establish appropriate marketing strategies for products in order to successfully enter overseas markets. When consumers evaluate the quality of products from various countries, they depend heavily on the image of the product as well as the price of the product. Therefore, this study aim to find out how the price, country image, brand image and country of origin image affect on consumer product evaluation and purchase intention. Based on these concepts, the significance of this study is helping local companies make more appropriate marketing strategies by understanding the importance of price and image of a product to companies and knowing more accurate recognition in Korea and Korean-made products of Chinese consumers. The results of this study which used AMOS model showed that 1) The country image and country of origin image for a product had a positive effects on product quality, 2) The price and country image of a product had a positive effects on service quality, 3) And evaluation of product had a positive effects on purchase intention. Based on these results, we made some proposals and presented the future research directions according to the limitations.