• Title/Summary/Keyword: Color Similarity

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Women's Wear Brand Positioning According to Brand Loyalty (상표충성도에 따른 여성복 브랜드 포지셔닝)

  • 권현주;구양숙
    • Journal of the Korean Home Economics Association
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    • v.38 no.10
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    • pp.85-95
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    • 2000
  • The purpose of this study was to identify brand loyally of women's wear and construct brand positioning maps by using multidimensional scaling(MDS). There were significant differences between brand loyal and indifferent group in ages, income, occupation status and level of education. Significant differences were found between groups in the degree of importance of attributes (design/color, fashion, quality, store image, salesperson's attitude and brand reputation) when evaluating brands. The positioning maps upon the similarity and preference of brand image were composed by use of MDS.

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People Counting based on Color Histogram (컬러 매칭을 이용한 사람 계수 측정)

  • Yeon, Je-Weon;Kim, Manbae
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2016.11a
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    • pp.140-141
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    • 2016
  • 기존의 사람 계수 측정 시스템은 적외선 빔이나 열 감지 영상 장치를 통해 측정하였다. 하지만 이와 같은 방법으로 측정하면 객체가 들어가거나 나가는 정보는 제공하지 않는다. 이에 본 논문은 고정된 카메라를 이용하여 각 사람의 피부색과 옷차림 등의 RGB 정보를 이용한 사람 계수 측정 기법을 제안한다. RGB카메라 영상을 통하여 객체의 RGB 히스토그램을 얻은 후 각 객체에 대해 Bhattacharyya metric을 통한 histogram similarity을 계산하여 객체 추적 및 분류를 통해 사람 계수 측정을 한다. 제안된 시스템은 C/C++을 기반으로 구현하여, 사람 계수 측정 성능을 평가하였다.

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A Design and Implementation of a Content_Based Image Retrieval System using Color Space and Keywords (칼라공간과 키워드를 이용한 내용기반 화상검색 시스템 설계 및 구현)

  • Kim, Cheol-Ueon;Choi, Ki-Ho
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.6
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    • pp.1418-1432
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    • 1997
  • Most general content_based image retrieval techniques use color and texture as retrieval indices. In color techniques, color histogram and color pair based color retrieval techniques suffer from a lack of spatial information and text. And This paper describes the design and implementation of content_based image retrieval system using color space and keywords. The preprocessor for image retrieval has used the coordinate system of the existing HSI(Hue, Saturation, Intensity) and preformed to split One image into chromatic region and achromatic region respectively, It is necessary to normalize the size of image for 200*N or N*200 and to convert true colors into 256 color. Two color histograms for background and object are used in order to decide on color selection in the color space. Spatial information is obtained using a maximum entropy discretization. It is possible to choose the class, color, shape, location and size of image by using keyword. An input color is limited by 15 kinds keyword of chromatic and achromatic colors of the Korea Industrial Standards. Image retrieval method is used as the key of retrieval properties in the similarity. The weight values of color space ${\alpha}(%)and\;keyword\;{\beta}(%)$ can be chosen by the user in inputting the query words, controlling the values according to the properties of image_contents. The result of retrieval in the test using extracted feature such as color space and keyword to the query image are lower that those of weight value. In the case of weight value, the average of te measuring parameters shows approximate Precision(0.858), Recall(0.936), RT(1), MT(0). The above results have proved higher retrieval effects than the content_based image retrieval by using color space of keywords.

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Moving Object Tracking using Cumulative Similarity Transform (누적 유사도 변환을 이용한 물체 추적)

  • Choo, Moon-Won
    • The Journal of the Korea Contents Association
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    • v.3 no.1
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    • pp.58-63
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    • 2003
  • In this paper, an object tracking system in a known environment is proposed. It extracts moving area shaped on objects in video sequences and decides tracks of moving objects. Color invarianoe features are exploited to extract the plausible object blocks and the degree of radial homogeneity, which is utilized as local block feature to find out the block correspondences. The experimental results are given.

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A Study on the Architectural Characteristics of De Stijl Style (데 스틸(De Stijl) 사조의 건축특성에 관한 연구)

  • Kim Heung-Seob
    • Korean Institute of Interior Design Journal
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    • v.14 no.6 s.53
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    • pp.29-36
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    • 2005
  • The original members of the De Stijl group, formed in neutral Holland during the First World War, included the painters Piet Mondrian, Bart van Leck and Theo van Doesburg, and the architects J.J.P. Oud and Jan Wils. The aim of the group was to create a language of form and color applicable to every sphere of modern life. The means of expression selected by the De Stijl artists was rigorously restricted, using only vertical and horizontal lines with the right-angle created where they cross, and for color, black, white and the primaries- red, yellow and blue. Of these simple elements consisted the compositions painted by Mondrian and van Doesburg during the years around the end of the First World War, and the famous red-blue chair made by Gerrit Rietvelt in 1917. They did share a common influence, Cubism, and they both emphasized contemporaneity. Otherwise they were quite different movements, both in theory and practice, except lot one further point of similarity.

Similarity between Color Distributions based on Different Color Sets (상이한 칼라집합 기반의 칼라분포간 유사도)

  • 김동균;김성영;김민환
    • Proceedings of the Korea Multimedia Society Conference
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    • 2002.11b
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    • pp.141-144
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    • 2002
  • 영상에서의 칼라분포 정보는 영상간의 유사성을 표현하는데 매우 유용하여 내용기반 영상검색분야에서 기본적으로 사용하고 있다. 이때, 영상 데이터베이스에서의 각 영상에 대하여 동일한 방식으로 (비)균일하게 양자화하여 표현한 칼라 히스토그램이 주로 사용되고 있다. 그러나, 전체영상에 대하여 동일한 개수의 고정된 양자화를 통해 칼라분포 정보를 표현하는데, 여러 가지 문제점과 성능 차이가 있어 다양한 해결 방안이 연구되고 있다. 본 논문에서는, 적응적 양자화 방법으로 각 영상의 칼라분포 정보를 표현하되, 상이한 양자화 칼라간의 유사도를 정의하여 칼라히스토그램 인터섹션 방법과 유사하게 영상간의 칼라분포 유사도를 계산하는 방법을 제안한다. 양자화 칼라간의 유사도는 거리에 반비례하면서 두 양자화 칼라의 작은 빈도값에 비례하도록 정의하였다. 영상간의 칼라분포 유사도는 칼라 히스토그램 인터섹션 방법을 생산자-소비자 모델로 해석하여 구하는 방법을 제안한다. 제안한 방법에 의해 기존의 칼라 히스토그램 인터섹션 방법보다 향상된 결과를 얻을 수 있음을 실험을 통해 확인하였다.

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A Robust Multi-part Tracking of Humans in the Video Sequence (비디오 영상내의 사람 추적을 위한 강인한 멀티-파트 추적 방법)

  • 김태현;김진율
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2088-2091
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    • 2003
  • We presents a new algorithm for tracking person in video sequence that integrates the meanshift iteration procedure into the particle filtering. Utilizing the nice property of convergence to the modes in the meanshift iteration we show that only a few sample points are sufficient, while in general the particle filtering requires a large number of sample points. Multi-parts of a person is tracked independently of each other based on the color Then, the similarity against the reference model color and the geometric constraints between multi-parts are reflected as the sample weights. Also presented is the computer simulation results, which show successful tracking even for complex background clutter.

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Text Extraction Algorithm in Complex Images using Adaptive Edge detection (복잡한 영상에서 적응적 에지검출을 이용한 텍스트 추출 알고리즘 연구)

  • Shin, Seong;Kim, Sung-Dong;Baek, Young-Hyun;Moon, Sung-Ryong
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.251-252
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    • 2007
  • The thesis proposed the Text Extraction Algorithm which is a text extraction algorithm which uses the Coiflet Wavelet, YCbCr Color model and the close curve edge feature of adaptive LoG Operator in order to complement the demerit of the existing research which is weak in complexity of background, variety of light and disordered line and similarity of text and background color. This thesis is simulated with natural images which include naturally text area regardless of size, resolution and slant and so on of image. And the proposed algorithm is confirmed to an excellent by compared with an existing extraction algorithm in same image.

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Normal map generation based on Pix2Pix for rendering fabric image (옷감 이미지 렌더링을 위한 Pix2Pix 기반의 Normal map 생성)

  • Nam, Hyeongil;Park, Jong-Il
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2020.07a
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    • pp.257-260
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    • 2020
  • 본 논문은 단일의 옷감 이미지로 가상의 그래픽 렌더링을 위해 Pix2Pix 방법을 이용하여 Normal map 을 생성하는 방법을 제시한다. 구체적으로 단일의 이미지를 이용해서 Normal map 를 생성하기 위해, Color image 와 Normal map 쌍의 training dataset 을 Pix2Pix 방법을 이용해서 학습시킨다 또한, test dataset 의 Color image 를 입력으로 넣어 생성된 Normal map 결과를 확인한다. 그리고 선행연구에서 사용되어오던 U-Net 방식의 방법과 본 논문에서 사용한 Pix2Pix 를 이용한 Normal map 생성 결과를 SSIM(Structural Similarity Index)으로 비교 평가한다. 또한, 생성된 Normal map 을 렌더링하고자 하는 가상 객체의 사이즈에 맞게 사이즈를 조정하여 OpenGL 로 렌더링한 결과를 확인한다. 본 논문을 통해서 단일의 패턴 이미지를 Pix2Pix 로 생성한 Normal map 으로 옷감의 디테일을 사실감 있게 표현할 수 있음을 확인할 수 있었다.

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Implementation on the Filters Using Color and Intensity for the Content based Image Retrieval (내용기반 영상검색을 위한 색상과 휘도 정보를 이용한 필터 구현)

  • Noh, Jin-Soo;Baek, Chang-Hui;Rhee, Kang-Hyeon
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.44 no.1
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    • pp.122-129
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    • 2007
  • As the availability of an image information has been significantly increasing, necessity of system that can manage an image information is increasing. Accordingly, we proposed the content-based image retrieval(CBIR) method based on an efficient combination of a color feature and an image's shape and position information. As a color feature, a HSI color histogram is chosen which is known to measure spatial of colors well. Shape and position information are obtained using Hu invariant moments in the luminance of HSI model. For efficient similarity computation, the extracted features(Color histogram, Hu invariant moments) are combined and then measured precision. As a experiment result using DB that was supported by http://www.freefoto.com, the proposed image search engine has 93% precision and can apply successfully image retrieval applications.