• Title/Summary/Keyword: 이미지 체계

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An Object-Oriented Retrieval Mechanism for Unstructed Image Repositories (비구조화된 이미지 저장소를 위한 객체지향 검색체계)

  • Cha, Gwang-Ho;Jeong, Jin-Wan
    • Journal of KIISE:Computing Practices and Letters
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    • v.5 no.2
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    • pp.263-272
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    • 1999
  • 본 논문은 비구조화된 이미지 저장소로부터 효과적인 이미지검색을 위한 객체 지향 검색 체계를 제시한다. 본 검색 체계에서는 이미지의 내용을 정량적 특성을 갖는 시각 정보, 비정량적 특성을 나타내는 의미 정보, 그리고 가장 추상적인 정보를 포함하는 키워드의 세 종류로 규정한다. 시각 정보와 키워드는 특별한 구조없이 집합의 형태로 저장하고, 의미 정보는 상속과 군집 관계를 갖는 계층구조로 저장하는 것이 자연스럽다. 본 논문에서는 객체지향 모델을 사용하여 비구조화된 이미지 저장소를 위한 통일된 검색 체게를 제시한다. 제안된 검색 체계의 효과를 검증하기 위해 많은 이미지 집합에 대한 실험을 수행하였다.

Development of compound eye image quality improvement based on ESRGAN (ESRGAN 기반의 복안영상 품질 향상 알고리즘 개발)

  • Taeyoon Lim;Yongjin Jo;Seokhaeng Heo;Jaekwan Ryu
    • Journal of the Korea Computer Graphics Society
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    • v.30 no.2
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    • pp.11-19
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    • 2024
  • Demand for small biomimetic robots that can carry out reconnaissance missions without being exposed to the enemy in underground spaces and narrow passages is increasing in order to increase the fighting power and survivability of soldiers in wartime situations. A small compound eye image sensor for environmental recognition has advantages such as small size, low aberration, wide angle of view, depth estimation, and HDR that can be used in various ways in the field of vision. However, due to the small lens size, the resolution is low, and the problem of resolution in the fused image obtained from the actual compound eye image occurs. This paper proposes a compound eye image quality enhancement algorithm based on Image Enhancement and ESRGAN to overcome the problem of low resolution. If the proposed algorithm is applied to compound eye image fusion images, image resolution and image quality can be improved, so it is expected that performance improvement results can be obtained in various studies using compound eye cameras.

Perceptual Color Difference based Image Quality Assessment Method and Evaluation System according to the Types of Distortion (인지적 색 차이 기반의 이미지 품질 평가 기법 및 왜곡 종류에 따른 평가 시스템 제안)

  • Lee, Jee-Yong;Kim, Young-Jin
    • 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.

Image Quality Assessment Using Perceptual Color Difference (인지적 색 차이를 사용한 이미지 품질 평가)

  • Lee, Jee-Yong;Kim, Young-Jin
    • 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.

A Study on the Development of a Selection System for Preservation Formats of Image-Type Electronic Records (이미지 유형 전자기록물의 보존포맷 선정체계 구축방안 연구)

  • Song, ChaeEun;Yang, Dongmin
    • The Korean Journal of Archival Studies
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    • no.79
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    • pp.343-387
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    • 2024
  • Electronic records, characterized by their inherent volatility and instability, necessitate sustainable preservation measures to ensure their long-term accessibility. The National Archives of Korea has instituted a selection system for preservation formats tailored predominantly for document-type electronic records. However, this system falls short in accommodating other record types such as audiovisual records. This study endeavors to broaden the applicability of the existing system, with a concentrated focus on image-type electronic records, and to formulate foundational guidelines for their long-term preservation. In South Korea, image-type electronic records rank as the second most prevalent category following document-type. The image-type electronic records are the most basic form of audio-visual records, and research on this lays the foundation for future discussions on other audio-visual records. Consequently, this research has led to the development of a selection system for preservation formats specifically for image-type electronic records. This system is designed to facilitate the prompt and efficient evaluation of preservation format suitability, even in the context of emerging image formats. The efficacy of this system was validated through its application to extant image formats, resulting in the selection of TIFF, JFIF, and PNG as the optimal preservation formats. The outcomes of this study offer valuable insights and practical reference points for future preservation format evaluations within the field of electronic record management.

Design and Implementation of Hierarchical Image Classification System for Efficient Image Classification of Objects (효율적인 사물 이미지 분류를 위한 계층적 이미지 분류 체계의 설계 및 구현)

  • You, Taewoo;Kim, Yunuk;Jeong, Hamin;Yoo, Hyunsoo;Ahn, Yonghak
    • Convergence Security Journal
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    • v.18 no.3
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    • pp.53-59
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    • 2018
  • In this paper, we propose a hierarchical image classification scheme for efficient object image classification. In the non-hierarchical image classification, which classifies the existing whole images at one time, it showed that objects with relatively similar shapes are not recognized efficiently. Therefore, in this paper, we introduce the image classification method in the hierarchical structure which attempts to classify object images hierarchically. Also, we introduce to the efficient class structure and algorithms considering the scalability that can occur when a deep learning image classification is applied to an actual system. Such a scheme makes it possible to classify images with a higher degree of confidence in object images having relatively similar shapes.

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A Systematic Review on Concept-based Image Retrieval Research (체계적 분석 기법을 이용한 의미기반 이미지검색 분야 고찰에 관한 연구)

  • Chung, EunKyung
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.25 no.4
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    • pp.313-332
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    • 2014
  • With the increased creation, distribution, and use of image in context of the development of digital technologies and internet, research endeavors have accumulated drastically. As two dominant aspects of image retrieval have been considered content-based and concept-based image retrieval, concept-based image retrieval has been focused in the field of Library and Information Science. This study aims to systematically review the accumulated research of image retrieval from the perspective of LIS field. In order to achieve the purpose of this study, two data sets were prepared: a total of 282 image retrieval research papers from Web of Science, and a total of 35 image retrieval research from DBpia in Kore for comparison. For data analysis, systematic review methodology was utilized with bibliographic analysis of individual research papers in the data sets. The findings of this study demonstrated that two sub-areas, image indexing and description and image needs and image behavior, were dominant. Among these sub-areas, the results indicated that there were emerging areas such as collective indexing, image retrieval in terms of multi-language and multi-culture environments, and affective indexing and use. For the user-centered image retrieval research, college and graduate students were found prominent user groups for research while specific user groups such as medical/health related users, artists, and museum users were found considerably. With the comparison with the distribution of sub-areas of image retrieval research in Korea, considerable similarities were found. The findings of this study expect to guide research directions and agenda for future.

A Dual Graph Data Model for the Representation of Image Information (이미지 정보를 표현하기 위한 이중 그래프 데이터 모델)

  • 박미화;엄기현
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10b
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    • pp.262-264
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    • 1998
  • 이미지 데이터베이스를 구성하여 사용자가 원하는 정보를 추출하는 의미 기반 검색을 지원하기 위해서는 이미지 내용에 관한 의미 정보들이 데이터 모델로 구조화되어야 한다. 본 논문에서는 다양한 정적 이미지 내용 정보들을 분류하고 그를 체계적으로 표현하기 위한 이미지 데이터 모델을 소개한다. 특히 본 이미지 데이터 모델은 그래프 이론을 이용하여 이미지내에 포함된 시각 객체들의 내용 정보를 표현하고 객체들간의 의미 관계를 정의한다. 이는 이미지 내용에 대한 정확한 정보 표현과 질의에 대한 이미지 검색 효율을 향상시킬 수 있으며 객체들간의 의미 관계를 이용한 질의와 검색을 가능하게 한다.

Product Image Concentration System as a Design Strategy to Build Corporate Brand Image (기업 브랜드 이미지 구축을 위한 디자인 전략으로서의 제품 이미지 집중 체계)

  • Kim, Hyun
    • Archives of design research
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    • v.16 no.2
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    • pp.375-384
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    • 2003
  • This study is on the strategy for establishing successful corporate brand image, by understanding the need for increasing brand value based on the level of brand recognition. In order to carry this out, the PICS (Product Image Concentration System) is suggested, which includes Brand Image Analysis on a high-level, Product Image Programming based on the result of the image analysis, and Product Image Coherency Assessment and Management, resulting in setting up a guideline for gaining competitive advantage and brand management. Brand Image Analysis is a method that utilizes image association to understand brand disposition by analyzing the association pattern among available visual materials to measure the corporate and brand image inclinations. As the next step, Product Image Programming establishes design philosophy and principles based on the analysis of brand image, and the Visual Programming is a process for visualizing the intended product image direction. Lastly, Product Image Coherency Assessment examines whether to incorporate design philosophy and principles or not to arrive at an agreed evaluation criteria for developing designs coherent with the brand image. The PICS (Product Image Concentration System) is a practical method for increasing a company' competitive advantage and managing brand. The expectation on this system is to provide a guideline for applying brand image in design process more objectively. For further study, diversification of image spectrum based on expressive keywords and comparative analysis on images as well as a product image interpretation program to understand the order of visual materials will be necessary.

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입체시를 활용한 변화지역 자동 추적 알고리즘 개발

  • Kim, Kam-Lae;Kim, Hoon-Jung;Kim, Byeong-Bae;Cho, Won-Woo
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2007.04a
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    • pp.431-434
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    • 2007
  • 빗물 및 폐수가 흘러가는 하수관은 자연 유하식으로 하수가 흘러갈 수 있도록 설계되어있는 관의 특성상 침전물이 많이 발생하며, 집중호우로 발생하는 다량의 빗물이 빠른 유속으로 관을 흐르기 때문에 관내부를 손상시키는 요인으로 작용하고 있다. 이에 본 연구에서는 관 내부를 촬영할 수 있는 궤도차량을 통해 동영상 자료를 획득하고 영상의 이미지 보정 단계를 거쳐 그래픽 파일로 변환한후 관련 정보를 입력, 저장하는 시스템 개발을 본 연구의 주요 범위로 한다. 이미지보정은 동영상을 거리의 함수를 가지는 이미지 파일로 변환하고 각각의 획득된 이미지를 영상정합기법을 사용하여 하나의 연속된 이미지 형태로 저장하여 영상 해석을 통해 균열, 침전등의 사항을 도출하여 도출된 사항은 지리정보 체계와 연동할 수 있는 파일 체계를 갖추도록 개발하였다.

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