• Journal of Digital Contents Society
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• v.2 no.2
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• pp.157-166
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• 2001

In this paper we propose a feature vector extraction technique using regression of shape features for the content-based image retrieval system. The proposed technique can reduce the number of dimensions of a feature vector by converting the extracted high-dimensional feature vector into a specific n-dimensional feature vector. This paper shows how to resolve the 'dimensionality curse' problem by reducing the number of dimensions of a feature vector, and shows that the technique is more efficient than the conventional techniques for the practical image retrievals.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.779-782
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• 2013

오늘날 우리 생활에 영상이나 이미지는 우리 실생활에 아주 밀접하게 연관되어 있다. 카메라, 휴대폰, TV, 영상 및 이미지 관련 기기들이 증가하고 이로 인해 영상이나 이미지 관련 서비스의 기술적인 요소들이 중요시되고 있다. 이러한 영상에서 기본적으로 사용하는 압축방식인 DCT는 직교 변환 방식의 국제 표준으로써, 정지 이미지나 동영상의 압축 파일등에서 사용된다. DCT(Discrete Cosine Transform) 알고리즘은 음성 및 영상 압축 등 많은 디지털 신호처리 분야에서 사용되고 있다. 본 논문에서는 WMV의 $4{\times}4$, $4{\times}8$,$8{\times}4$, $8{\times}8$ 4가지 모드에 대해 DCT를 지원할 수 있도록 C언어를 통해 상위 수준의 검증을 수행하고, 이를 HDL을 사용하여 코딩하고, Modelsim SE6.1을 사용해 회로 검증하였다.

• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.383-384
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• 2014

본 연구는 모바일 환경에서 활용 가능한 해석된 빗속의 사람 결과 이미지를 활용한 스트레스 평가도구 개발을 위해, 결과 이미지를 사용자에게 대비하여 제시하고 사용자의 선택 결과를 분석하여 스트레스 수준을 평가하기 위한 방법론의 타당성을 분석하였다. '빗속의 사람' 검사는 대상자가 직접 그림을 그려야 하나, 모바일 환경에서는 구현과 해석이 어려워 이미 그려진 그림을 선택하도록 설계하였다. 이를 위해 '빗속의 사람' 검사의 결과 이미지가 스트레스 상태를 선별할 때 유용한지를 밝히고자 하였다. 서울 및 경기지역의 20~50대 이하 여성 101명이 본 연구에 참여하였다. 이들을 대상으로 '빗속의 사람' 검사와 스트레스 검사를 동시에 실시하였다. '빗속의 사람' 검사 결과와 스트레스 검사 결과는 검사해석방법에 따라 스트레스를 3단계로 분류하였다. 분류된 3단계의 결과는 서로 유의한 상관관계가 있어 유용하게 활용 가능함을 확인하였다.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.420-438
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• 2004

Artificially or naturally contained texts in the natural images have significant and detailed information about the scenes. If we develop a method that can extract and recognize those texts in real-time, the method can be applied to many important applications. In this paper, we suggest a new method that extracts the text areas in the natural images using the low-level image features of color continuity. gray-level variation and color valiance and that verifies the extracted candidate regions by using the high-level text feature such as stroke. And the two level features are combined hierarchically. The color continuity is used since most of the characters in the same text lesion have the same color, and the gray-level variation is used since the text strokes are distinctive in their gray-values to the background. Also, the color variance is used since the text strokes are distinctive in their gray-values to the background, and this value is more sensitive than the gray-level variations. The text level stroke features are extracted using a multi-resolution wavelet transforms on the local image areas and the feature vectors are input to a SVM(Support Vector Machine) classifier for the verification. We have tested the proposed method using various kinds of the natural images and have confirmed that the extraction rates are very high even in complex background images.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.413-420
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• 2023

For a long time, researchers have presented excellent results in the field of image retrieval due to many studies on CBIR. However, there is still a semantic gap between these search results for images and human perception. It is still a difficult problem to classify images with a level of human perception using a small number of images. Therefore, this paper proposes an image classification model using deep learning-based transfer learning to minimize the semantic gap between images of people and search systems in image retrieval. As a result of the experiment, the loss rate of the learning model was 0.2451% and the accuracy was 0.8922%. The implementation of the proposed image classification method was able to achieve the desired goal. And in deep learning, it was confirmed that the CNN's transfer learning model method was effective in creating an image database by adding new data.

• Journal of the Korea Computer Graphics Society
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• v.20 no.3
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• pp.1-8
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• 2014

We propose a method to compose a foreground object into a background image, where the foreground object is a part (or a region) of an image taken by a front-facing camera and the background image is a whole image taken by a back-facing camera in a smart phone at the same time. Recent high-end cell-phones have two cameras and provide users with preview video before taking photos. We extract the foreground object that is moving along with the front-facing camera using the optical flow during the preview. We compose the extracted foreground object into a background image using a simple image composition technique. For better-looking result in the composed image, we apply a border smoothing technique using a weighted-border mask to blend transparency from background to foreground. Since constructing and grouping pixel-level dense optical flow are quite slow even in high-end cell-phones, we compute a mask to extract the foreground object in low-resolution image, which reduces the computational cost greatly. Experimental result shows the effectiveness of our extraction and composition techniques, with much less computational time in extracting the foreground object and better composition quality compared with Poisson image editing technique which is widely used in image composition. The proposed method can improve limitedly the color bleeding artifacts observed in Poisson image editing using weighted-border blending.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.173-189
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• 2023

Although many researches have been conducted that the contents consumption, called Hallyu, has a positive effect on the national image of Korea, which leads to product purchases, there have been few empirical studies based on the experience economy theory that connects to value relationships with customers. Therefore, based on the experiential economy theory, this research conducted an empirical analysis of the effect on Korean image and cosmetics purchase intention targeting women living in Malaysia and the Philippines who have experienced the Korean Wave(Hallyu). As a result of the research, entertainment experience, educational experience, and escape experience had a significant effect on the image of Korea, but aesthetic experience did not. Entertainment experience, educational experience and escape experience also had significant relationships in the indirect effect of Korean image on cosmetics purchase intention. In the moderating effect analysis comparing the two countries, in Malaysia, escape experience had a significant effect on the image of Korea, but in the Philippines, entertainment experience and educational experience had a significant effect on the image of Korea, so there was a difference between the two countries. The effect of Korean image on cosmetics purchase intention was confirmed significantly in both countries, but it was greater in the Philippines than in Malaysia. This research is meaningful in that it is an empirical study based on the systematic framework of experiential economy theory. In order to maintain the effectiveness of the Korean Wave(Hallyu), various improvements in the contents that make up the Korean Wave are required and policy consideration by the relevant authorities is needed. It is also necessary to consider each country's different acceptance of the Korean Wave(Hallyu).

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.406-408
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• 2003

요즘 값싼 PC를 빠른 네트웍으로 묶어 높은 성능을 얻고자하는 클러스터 컴퓨팅에 대한 연구가 활발히 이루어지고 있다. 이러한 연구 중 클러스터 컴퓨팅 환경을 구성하는 여러 컴퓨터들을 하나의 컴퓨터처럼 보이게 해주는 단일 시스템 이미지 서비스는 사용자에게 쓰기 편리한 환경과 높은 가용성을 제공하여 준다. 단일 시스템 이미지 서비스를 제공하기 위해서는 단일 프로세스 공간, 단일 메모리 공간 및 단일 디스크 입출력을 제공하여 주어야 한다. 단일 디스크 입출력은 여러 컴퓨터에 나누어져 있는 디스크들을 하나의 큰 디스크로 보여주고 여러 디스크들을 효율적으로 사용할 수 있도록 서비스를 제공한다. 이러한 단일 디스크 입출력을 사용자 수준이나 파일 시스템 수준에서 제공하여 주는 것은 성능 측면이나 투명성의 측면에서 커널 모듈로 제공하여 주는 것 보다 좋지 않다. 따라서 본 논문에서는 단일 디스크 입출력을 위하여 커널 모듈 프로토타입을 설계하고 구현한다. 그리고 네트웍 파일 시스템과 단일 디스크를 이용하여 단일 디스크 입출력을 위한 터널 모듈의 성능과 비교, 분석한다.

• Journal of the Korean Society of Radiology
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• v.84 no.1
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• pp.240-252
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• 2023

Purpose To assess the effect of deep learning image reconstruction (DLIR) for head CT in pediatric patients. Materials and Methods We collected 126 pediatric head CT images, which were reconstructed using filtered back projection, iterative reconstruction using adaptive statistical iterative reconstruction (ASiR)-V, and all three levels of DLIR (TrueFidelity; GE Healthcare). Each image set group was divided into four subgroups according to the patients' ages. Clinical and dose-related data were reviewed. Quantitative parameters, including the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), and qualitative parameters, including noise, gray matter-white matter (GM-WM) differentiation, sharpness, artifact, acceptability, and unfamiliar texture change were evaluated and compared. Results The SNR and CNR of each level in each age group increased among strength levels of DLIR. High-level DLIR showed a significantly improved SNR and CNR (p < 0.05). Sequential reduction of noise, improvement of GM-WM differentiation, and improvement of sharpness was noted among strength levels of DLIR. Those of high-level DLIR showed a similar value as that with ASiR-V. Artifact and acceptability did not show a significant difference among the adapted levels of DLIR. Conclusion Adaptation of high-level DLIR for the pediatric head CT can significantly reduce image noise. Modification is needed while processing artifacts.

• Journal of Distribution Science
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• v.10 no.6
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• pp.17-26
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• 2012

Suncheon is a city comprising a rural and urban area, where there are four types of large stores. Studies have shown that there are too many large stores serving the local population of just 300,000. However, geographically, Suncheon is located at a transportation hub that borders the cities of Gwangyang and Yeosu as well as the local counties of Boseong and Gurae. Residents of these areas can reach these shopping stores within an hour's drive. Thus, the managers of these four stores regard residents in these areas as their valued customers and endeavor to create a differentiated image among them. In this study, 13 different images were used to determine the public's opinions and feelings towards these stores and the differences were analyzed. The store images measured overall store impression, diversity of the product, the quality of products displayed at the store, accessibility, the atmosphere, service to the customers, and so on. These images are evaluated subjectively by each customer and are major factors in them deciding to revisit the stores. The 13 images are classified into five main categories and further classified into 13 sub-categories. Three kinds of factor images were extracted from the store images in the five main categories by factor analysis using SPSS Ver. 19. The first factor image was extracted from the images of convenience, atmosphere, and service in the main categories and is called a sub-service factor for the store in this study. Accessibility to the store was classified as a convenience image in the main category and was extracted as a common factor along with diversity and the price of goods. These differences are expected according to the store location, that is, the difference between stores located in a large city and those in a small local city, and depending on the nature of survey respondents. The result shows that there is a significant difference between the stores' images with regard to accessibility, the price of products, brand image, and lighting/sound image. This study has the following limitations. First, the survey sample was restricted to residents of a small local city that includes rural and urban populations. The differences between the store images regarding traffic and accessibility are factored by store location, whether they are located within a large or a small city as well as the economic situation of these cities. Second, only the customers of large-scale stores were included in the survey as respondents. Relatively large traditional markets are held every five days in local cities and there is competition between large-scale stores and traditional markets with regard to diversity and the price of goods. It could be expected that customers in large-scale stores and customers in traditional markets would hold different store images. In future studies, images of stores in large cities should be compared with the images of stores located in small local cities. In addition, customer behavior when buying goods in large-scale stores should be compared with their behavior when buying goods in traditional markets.