• Title/Summary/Keyword: 색특징

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Content-Based Image Retrieval using 3rd Order Color Object Relation (3차 칼라 오브젝트 관계에 의한 내용 기반 영상 검색)

  • 최재우;권희용;황희융
    • Proceedings of the KAIS Fall Conference
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    • 2000.10a
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    • pp.208-213
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    • 2000
  • 본 논문은 정지 화상에 대한 CBIR(Content-Based Image Retrieval)방법 중 칼라 특성을 이용해서 영상 내 공간 정보를 충분하게 표현할 수 있는 알고리즘을 제안한다. 일반적으로 칼라 특성을 이용한 CBIR은 영상 내 공간정보를 충분하게 표현하지 못하는 단점을 지니고 있다. 이에 기존 논문에서는 인위적으로 영상을 여러 개로 분할하는 방법 등으로 공간정보를 표현하고자 하였지만 특징벡터의 수가 급격히 늘어남에 따라 검색효율이 저하된다는 단점을 가지고있다. 본 논문에서는 기존의 방법을 칼라 오브젝트의 추출 방법에 따라 1차와 2차 관계에 의한 방법으로 분류하고, 이동, 회전 특히 크기 변화(축소, 확대)에 탁월한 성능을 보이는 칼라 오브젝트의 3차 관계를 이용한 방법을 소개한다. 주어진 영상으로부터 양자화된 24개의 버킷을 생성해서 각 버킷 내의 칼라에 대한 색의 표준 편차로 색의 분산 정도틀 나타내고, 히스토그램의 빈도수가 높은 세 개 버킷의 평균 칼라 위치를 계산해서 그들의 상호 각도를 추출하여 영상의 특징 벡터로 사용한을 제안하였다. 실험결과 기존 방법보다 특히 영상의 크기 변화에 대해 좋은 결과를 얻을 수 있었으며, 계산량도 적어 효율적임을 보여 주었다.

Efficient Index Structure and Search Mehtod for Shape Image (모양 영상 검색을 위한 효율적인 색인구조와 검색방법)

  • 장용석;김성재;최병걸;안철웅;김승호
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10b
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    • pp.347-349
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    • 1999
  • 본 논문에서는 대규모 영상 데이터베이스로부터 모양 영상에 대한 검색을 빠르고 효율적으로 수행하기 위해 해싱기법을 변형한 색인구조와 검색방법을 제안한다. 제안된 색인 구조는 이진 모양 영상(binary shape image)의 불변 모멘트 집합(invariant moments set)을 특징 벡터로 사용하여 다차원으로 구성된다. 이 색인 구조를 기반으로 제안된 해싱을 변형한 검색방법은 기존의 방법들에 비해 검색공간을 줄임으로써 검색속도를 높인다. 본 논문에서 제안한 색인구조와 검색방법을 1000개의 이진 모양 영상들에 적용해 본 결과 검색공간이 전체 공간의 10% 미만으로 줄어드는 효과가 있었다.

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A Color Feature for Retrieving Design Images with limited Colors (제한된 색을 갖는 디자인 영상 검색을 위한 색 특징)

  • 권태완;박섭형
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.541-544
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    • 2003
  • This paper proposes a new color feature and a corresponding distance measure for content-based retrieval of design images such as trade marks, pattens, logos, textile images, and icons. Simulation results with textile images show that the proposed method outperforms the traditional color-based retrieval methods which was originally proposed fer content-based retrieval of natural images.

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Content based Image retrieval using Object Shape Token Clustering (객체 외형의 토큰 군집화를 통한 내용 기반 영상 검색)

  • Jeong Seok-hyun;KIM Gae-Young
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.07b
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    • pp.880-882
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    • 2005
  • 내용기반 영상 검색 시스템은 데이터베이스에 저장된 정지영상의 색이나, 질감, 형태 등의 특징을 이용한다. 본 연구는 실험 영상 집합에서 주요 객체를 추출하여, 객체들의 외형으로부터 분리된 토큰들을 군집화 한 후, 그 군집단위를 색인어로 사용하여 검색하는 방법이다. 기존의 내용기반 영상 검색 시스템에서 모양 정보는 그 표현과 색인 정합 등의 문제로 처리 방법이 명확하지 않았고, 회전, 크기 변화, 폐색 등에 민감했다. 따라서 기존 방법의 문제점을 해결하기 위해서 토큰을 이용한 색인을 이용하여 지역 정보와, 이들 지역 정보들의 관계에 의한 전역 정보를 복합적으로 이용한 방법을 제안한다.

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ORT(Ornithobacterium rhinotracheale) 감염증의 원인과 예방대책

  • 권용국
    • KOREAN POULTRY JOURNAL
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    • v.34 no.1 s.387
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    • pp.118-121
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    • 2002
  • ORT(Ornithobacterium rhinotracheale) 감염증이란 닭과 칠면조에서 급성 호흡기 증상과 함께 복기낭에 노란색 삼출물 저류가 특징적인 세균성 전염병이다. ORT감염증은 1991년 남아프리카에서 성장지체와 호흡기증상을 보이는 28일령의 육계에서 최초로 분리된 이후 네덜란드, 독일, 폴란드 등 여러 나라에서 발생 보고되었다.

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Content Based Classification of Audio Signal using Discriminant Function (식별함수를 이용한 오디오신호의 내용기반 분류)

  • Kim, Young-Sub;Lee, Kwang-Seok;Koh, Si-Young;Hur, Kang-In
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.06a
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    • pp.201-204
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    • 2007
  • In this paper, we research the content-based analysis and classification according to the composition of the feature parameters pool for the auditory signals to implement the auditory indexing and searching system. Auditory data is classified to the primitive various auditory types. we described the analysis and feature extraction method for the feature parameters available to the auditory data classification. And we compose the feature parameters pool in the indexing group unit, then compare and analysis the auditory data centering around the including level and indexing criterion into the audio categories. Based on this result, we composit feature vectors of audio data according to the classification categories, then experiment the classification using discrimination function.

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A Study on the Perception of Pit and Fissure Sealant using Unstructured Big Data (비정형 빅데이터를 이용한 치면열구전색(치아홈메우기)에 대한 인식분석)

  • Han-A Cho
    • Journal of Korean Dental Hygiene Science
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    • v.6 no.2
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    • pp.101-114
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    • 2023
  • Background: This study aimed to explore the overall perception of pit and fissure sealants and suggest methods to revitalize their current stagnation. Methods: To determine the social perception of the change in coverage policy for pit and fissure sealants, we categorized them into five time periods. The first period (December 1, 2009 to November 30, 2010), the second period (December 1, 2010 to September 30, 2012), the third period (October 1, 2012 to May 5, 2013), the fourth period (May 6, 2013 to September 30, 2017), and the fifth period (October 1, 2017 to December 31, 2022). We utilized text mining, an unstructured big data analysis method. Keywords were collected and analyzed using Textom, and the frequency analysis of the top 30 keywords, structural features of the semantic network, centrality analysis, QAP correlation analysis, and co-occurrence analysis were conducted. Results: The frequency analysis showed that the top keywords for each time period were 'Cavities', 'Treatment', and 'Children'. In the structural features of the semantic network of pit and fissure sealants by time period, the density index was found to be around 1.00 for all time periods. The QAP correlation analysis showed the highest correlation between the first and second periods and the fourth and fifth periods with a correlation coefficient of 0.834. The co-occurrence analysis showed that 'cavities' and 'prevention were the top two words across all time periods. Conclusion: This study showed that pit and fissure sealants are well accepted by the society as a preventive treatment for caries. However, the awareness of health education related to these sealants was found to be low. Efforts to revitalize stagnant pit and fissure sealants need to be strengthened with effective education.

The effect of color on apparent warmth and judgment distortion (색의 속성에 따른 지각된 온도감과 판단 왜곡)

  • Kim, Moon-Ju;Han, Kwang-Hee;Lee, Ju-Hwan
    • Science of Emotion and Sensibility
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    • v.9 no.4
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    • pp.341-351
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    • 2006
  • The effect of color evokes a certain feeling and affects behavior. Especially, an understanding and applying color are critical because well-designed color substantially contributes to quality and usability. In this study, the effects of three color components(hue, value, and chroma) on apparent warmth were investigated separately and relatively, and then feasibility of applying to the information display was examined. The result showed that the apparent warmth of 10 Hues was a U-shaped function declining from Red to Purple-Blue and increasing from Purple-Blue to Red-Purple with following order of color-circle. Chroma made the character of hues remarkably clear, so warm color becomes warmer and cool color becomes cooler if chroma gets higher. But value has no effect on warmth. These results propose that we can change the apparent warmth by varying chroma in the limitation of color use. And there was a sharp distinction between warm and cool color, Meanwhile, in the reading task of the graphical information, the subjects' judgment distortion overestimating or underestimating the actual degrees was ascertained. This result should be applied to control operator's sensitivity in accordance with the purpose of task and display.

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Design of RBFNNs Pattern Classifier Realized with the Aid of Face Features Detection (얼굴 특징 검출에 의한 RBFNNs 패턴분류기의 설계)

  • Park, Chan-Jun;Kim, Sun-Hwan;Oh, Sung-Kwun;Kim, Jin-Yul
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.2
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    • pp.120-126
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    • 2016
  • In this study, we propose a method for effectively detecting and recognizing the face in image using RBFNNs pattern classifier and HCbCr-based skin color feature. Skin color detection is computationally rapid and is robust to pattern variation for face detection, however, the objects with similar colors can be mistakenly detected as face. Thus, in order to enhance the accuracy of the skin detection, we take into consideration the combination of the H and CbCr components jointly obtained from both HSI and YCbCr color space. Then, the exact location of the face is found from the candidate region of skin color by detecting the eyes through the Haar-like feature. Finally, the face recognition is performed by using the proposed FCM-based RBFNNs pattern classifier. We show the results as well as computer simulation experiments carried out by using the image database of Cambridge ICPR.

Vehicle Color Recognition Using Neural-Network (신경회로망을 이용한 차량의 색상 인식)

  • Kim, Tae-hyung;Lee, Jung-hwa;Cha, Eui-young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.731-734
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    • 2009
  • In this paper, we propose the method the vehicle color recognizing in the image including a vehicle. In an image, the color feature vector of a vehicle is extracted and by using the backpropagation learning algorithm, that is the multi-layer perceptron, the recognized vehicle color. By using the RGB and HSI color model the feature vector used as the input of the backpropagation learning algorithm is the feature of the color used as the input of the neural network. The color of a vehicle recognizes as the white, the silver color, the black, the red, the yellow, the blue, and the green among the color of the vehicle most very much found out as 7 colors. By using the image including a vehicle for the performance evaluation of the method proposing, the color recognition performance was experimented.

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