• 대한전자공학회논문지SP
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• 제45권3호
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• pp.37-45
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• 2008

화질 평가는 원영상과 열화된 영상 간의 차이를 측정함으로써, 열화된 영상의 화질이 좋고 나쁨을 판단하는 것을 목표로 한다. 본 논문에서는 열화된 영상의 화질 평가를 위해, 원영상과 열화된 영상 전체를 비교하는 것 대신, 원영상과 열화된 영상, 각각의 특징으로 에지 투영을 이용하는 방법을 제안하였다. 여기서 에지 투영은 에지 맵에서 수직, 수평 방향으로 투영시킴으로써 얻을 수 있다. 에지 투영 시 수직, 수평 방향에 대한 그래디언트 크기를 고려함으로써, 보다 나은 화질 평가 방법을 제안하였다. 제안한 방법의 탁월함을 기존의 화질 평가 방법인 structural similarity(SSIM), edge peak signal-to-noise ratio(EPSNR), 그리고 edge histogram descriptor(EHD) 방법과 비교 실험을 통해 보였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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• pp.295-299
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• 2002

This paper presents an image contrast enhancement technique for improving low contrast images. We applied fuzzy logic to develop an image contrast enhancement technique in the viewpoint of considering that the low pictorial information of a low contrast image is due to the vaguness or fuzziness of the multivalued levels of brightness rather than randomness. The fuzzy image contrast enhancement technique consists of three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. In the stage of image fuzzification, we need to select a crossover point. To select the crossover point automatically the K-means algorithm is used. The problem of crossover point selection can be considered as the two-category, object and background, classification problem. The proposed method is applied to an experimental image with 256 gray levels and the result of the proposed method is compared with that of the histogram equalization technique. We used the index of fuzziness as a measure of image quality. The result shows that the proposed method is better than the histogram equalization technique.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권3호
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• pp.592-606
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• 2011

Currently, the development of multimedia communication has progressed so rapidly that the video program service has become a requirement for ordinary customers. The quality of experience (QoE) for the visual signal is of the fundamental importance for numerous image and video processing applications, where the goal of video quality assessment (VQA) is to automatically measure the quality of the visual signal in agreement with the human judgment of the video quality. Considering the codec effect to the video quality, in this paper an efficient non-reference (NR) VQA algorithm is proposed which estimates the video quality (VQ) only by utilizing the distorted video signal at the destination. The VQA feature vectors (FVs) which have high relationships with the subjective quality of the distorted video are investigated, and a hybrid NR VQA (HNRVQA) function is established by considering the multiple FVs. The simulation results, testing on the SDTV programming provided by VCEG Phase I, show that the proposed algorithm can represent the VQ accurately, and it can be used to replace the subjective VQA to measure the quality of the video signal automatically at the destinations.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.279-282
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• 2001

This paper presents an image contrast enhancement technique for improving the low contrast images using the improved IAFC(Integrated Adaptive Fuzzy Clustering) Model. The low pictorial information of a low contrast image is due to the vagueness or fuzziness of the multivalued levels of brightness rather than randomness. Fuzzy image processing has three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. Using a new model of automatic crossover point selection, optimal crossover point is selected automatically. The problem of crossover point selection can be considered as the two-category classification problem. The improved MEC can classify the image into two classes with unsupervised teaming rule. The proposed method is applied to some experimental images with 256 gray levels and the results are compared with those of the histogram equalization technique. We utilized the index of fuzziness as a measure of image quality. The results show that the proposed method is better than the histogram equalization technique.

• 한국의류학회지
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• 제16권2호
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• pp.155-168
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• 1992

The purposes of this study were: (1) to identify the image dimensions of apparel stores according to how the consumers rate the importance of store attributes; (2) to classify the apparel stores in Seoul, Korea according to consumers' perception of the image attributes of their preferred store; (3) to develop a positioning map of the apparel stores according to their salient image dimensions; and (4) to classify the female adults in Seoul according to the criteria of their preferred store and to describe the characteristics of target customers according to storetype. 'A questionnaire was developed to measure store patronage, perceived importance of the store image attributes, perception of the store image attributes for the respondent's most frequently patronized store, and demographic information. Data from 520 female adults living in Seoul were analyzed. The results were as follows; 1. The image dimensions of fashion stores were product quality, shopping convenience, location, promotion, atmosphere, product information, design characteristics and price. 2. The apparel stores in Seoul were classified into five groups by the perception of store image, which were labeled as national chain store, designer store, specialty store, wholesale store and independent store, according to their discriminant characteristics. 3. According to the positioning map, product quality and location convenience were identified as the most important apparel store type patronage criteria. 4. The female adult group divided by store preference indicated significant differences in the perceived importance of store attributes. Each group showed multi-store patronage.

• 방송공학회논문지
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• 제1권1호
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• pp.22-28
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• 1996

팔레트 (palette)를 사용하는 컬러 색인 영상 (indexed color image)에서 손상된 팔레트의 색인값을 수신단에서 복원 영상의 심각한 화질 저하를 초래한다. 본 논문에서는 컬러에 대한 인간의 감지 특성을 이용해 화질 저하 및 복원 오차를 최소화하는 컬러 영상 팔레트를 제안하였다. 팔레트 구성 알고리듬의 성능을 비교하기 위해 새로운 평가함수를 정의하였으며, 컴퓨터 모의 실험을 통해 비트 오류 상황하에서 제안한 방법의 효율성을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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• pp.2938-2956
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• 2020

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.

• Asia pacific journal of information systems
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• 제18권1호
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• pp.1-23
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• 2008

As managing customer relationship gets more important, companies are strengthening information service using multi-channels to their customers as a part of their customer relationship management (CRM) initiatives. It means companies are now accepting such information services not as simple information -delivering tools, but as strategic initiatives for acquiring and maintaining customer loyalty. In this paper, we attempt to validate whether or not such various information services would impact on organizational performance in terms of CRM strategy. More specifically, our research objective is to answer the next three questions: first, how to construct the instruments to measure not information quality but information service quality?; second, which attributes of information service quality can influence corporate image and customer loyalty?; finally, does each information service type have unique characteristics compared with others in terms of influencing corporate image and customer loyalty? With respect to providing answers to those questions, the previous studies had been limited in that those studies failed to consider the variety of types of information service or restricted the quality of information service to information quality. An appropriate research model answering the above questions should consider the fact that most companies are utilizing multi channels for their information services, and include the recent strategic information service such as customer online community. Moreover, since corporate information service could be regarded as a type of products or services delivered to customer, it is necessary to adopt the criteria for assessing customer's perceived value when to measure the quality of information service. Therefore, considering both multi-channels and multi-traits may enable us to tell the detailed causal routes showing which quality attributes of which information service would affect corporate image and customer loyalty. As information service channels, we include not only homepage and DM (direct mail), which are the most frequently applied information service channels, but also online community, which is getting more strategic importance in recent years. With respect to information service quality, we abstract information quality, convenience of information service, and timeliness of information service through a wide range of relevant literature reviews. As our dependant variables, we consider corporate image and customer loyalty that both of them are the critical determinants of organizational performance, and also attempt to grasp the relationship between the two constructs. We conducted a huge online survey at the homepage of one of representative dairy companies in Korea, and gathered 367 valid samples from 407 customers. The reliability and validity of our measurements were tested by using Cronbach's alpha coefficient and principal factor analysis respectively, and seven hypotheses were tested through performing correlation test and multiple regression analysis. The results from data analysis demonstrated that timeliness and convenience of homepage have positive effects on both corporate image and customer loyalty. In terms of DM, its' information quality was represented to influence both corporate image and customer loyalty, but we found its' convenience have a positive effect only on corporate image. With respect to online community, we found its timeliness contribute significantly both to corporate image and customer loyalty. Finally, as we expected, corporate image was revealed to provide a great influence to customer loyalty. This paper provides several academic and practical implications. Firstly, we think our research reinforces CRM literatures by developing the instruments for measuring information service quality. The previous relevant studies have mainly depended on the measurements of information quality or service quality which were developed independently. Secondly, the fact that we conducted our research in a real situation may enable academics and practitioners to understand the effects of information services more clearly. Finally, since our study involved three different types of information service which are most frequently applied in recent years, the results from our study might provide operational guidelines to the companies that are delivering their customers information by multi-channel. In other words, since we found that, in terms of customer loyalty, the key areas would be different from each other according to the types of information services, our analysis would help to make decisions such as selecting strengthening points or allocating resources by information service channels.

• 성인간호학회지
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• 제24권1호
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• pp.52-63
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• 2012

Purpose: The purpose of this study was to measure the quality of life (QOL) and to identify the factors influencing QOL in gynecological cancer patients. Methods: The subjects of this study were 242 people who were receiving medical therapy or follow-up after surgery from one general hospital in Daegu. Data were collected from August 1, 2010 to January 31, 2011. A questionnaire including questions on QOL, distress score, distress problem, depression, anxiety, insomnia, perceived health status and body image were completed by the subjects. Results: The mean score of QOL was $70.68{\pm}13.40$. Religion, job, presence of spouse, level of education, household income, financial compensation, disease stage and recurrence were the significant factors related to QOL. Distress score, distress problem, depression, anxiety, insomnia, perceived health status and body image were also significant factors influencing QOL. Sixty eight percent of the variance in subjective overall QOL can be explained by body image, distress problem, distress score, anxiety, level of education and perceived health status (Cum $R^2$=0.689, F=76.316, $p$ <.001). Body image was the most important factor related to QOL. Conclusion: An integrative care program which includes general, disease-related and psychosocial characteristics of patients is essential to improve QOL in gynecological cancer patients.

• 한국지리정보학회지
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• 제22권3호
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• pp.82-98
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• 2019

정보화 사회로 진입하면서 공간정보의 중요성은 급격하게 부각되고 있다. 특히 스마트시티, 디지털트윈과 같은 Real World Object의 3차원 공간정보 구축 및 모델링은 중요한 핵심기술로 자리매김하고 있다. 구축된 3차원 공간정보는 국토관리, 경관분석, 환경 및 복지 서비스 등 다양한 분야에서 활용된다. 영상기반의 3차원 모델링은 객체 벽면에 대한 텍스처링을 생성하여 객체의 가시성과 현실성을 높이고 있다. 하지만 이러한 텍스처링은 영상 취득 당시의 가로수, 인접 객체, 차량, 현수막 등의 물리적 적치물에 의해 필연적으로 폐색영역이 발생한다. 이러한 폐색영역은 구축된 3차원 모델링의 현실성과 정확성 저하의 주요원인이다. 폐색영역 해결을 위한 다양한 연구가 수행되고 있으며, 딥러닝을 이용한 폐색영역 검출 및 해결방안에 대한 연구가 수행되고 있다. 딥러닝 알고리즘 적용한 폐색영역 검출 및 해결을 위해서는 충분한 학습 데이터가 필요하며, 수집된 학습 데이터 품질은 딥러닝의 성능 및 결과에 직접적인 영향을 미친다. 따라서 본 연구에서는 이러한 학습 데이터의 품질에 따라 딥러닝의 성능 및 결과를 확인하기 위하여 다양한 영상품질을 이용하여 영상의 폐색영역 검출 능력을 분석하였다. 폐색을 유발하는 객체가 포함된 영상을 인위적이고 정량화된 영상품질별로 생성하여 구현된 딥러닝 알고리즘에 적용하였다. 연구결과, 밝기값 조절 영상품질은 밝은 영상일수록 0.56 검출비율로 낮게 나타났고 픽셀크기와 인위적 노이즈 조절 영상품질은 원본영상에서 중간단계의 비율로 조절된 영상부터 결과 검출비율이 급격히 낮아지는 것을 확인할 수 있었다. F-measure 성능평가 방법에서 노이즈 조절한 영상품질 변화가 0.53으로 가장 높게 나타났다. 연구결과로 획득된 영상품질별에 따른 폐색영역 검출 능력은 향후 딥러닝을 실제 적용을 위한 귀중한 기준으로 활용될 것이다. 영상 취득 단계에서 일정 수준의 영상 취득과 노이즈, 밝기값, 픽셀크기 등에 대한 기준을 마련함으로써 딥러닝을 실질적인 적용에 많은 기여가 예상된다.