• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1127-1129
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• 2017

상품의 매출은 진열 환경에 크게 영향을 받기 때문에 백화점을 비롯한 각급 매장에서는 다양한 연구를 진행하고 있다. 특히 조명에 따라 의류나 가구는 물론이고 과일을 비롯한 식료품의 매출액도 많은 영향을 받는 것으로 알려져 있다. 이에 따라 어떤 색상의 배경이나 조명이 소비자의 주목을 끌고 호감을 줄 수 있는지에 대한 연구들이 디자인 학자들을 중심으로 이루어지고 있으나, 실제 매장에서는 상품 색상에 맞춰 배경이나 조명을 변경하는 것이 거의 불가능한 실정이다. 따라서 본 연구에서는 상품 색상별로 소비자의 주목을 끌고 호감을 이끌어내서 상품 구매로 이어질 수 있는 IoT 기반의 스마트 LED 조명 시스템을 아두이노 보드를 이용하여 구현하고자 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.481-483
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• 2001

본 논문에서는 동영상으로부터 색상, 서체, 크기와 같은 사전 지식 없이도 글자/자막을 효율적으로 추출하는 방법을 제안한다. 해상도가 낮고 복잡한 배경을 포함할 수 있는 비디오에서 글자 인식률 향상을 위해 먼저 동일한 텍스트 영역의 존재하는 프레임들을 자동적으로 추출한 후 이들의 시간적 평균영상을 만들어 향상된 영상을 얻는다. 평균영상의 외각선 영상의 투영 값을 통해 문자영역을 찾고 각 텍스트 영역에 대해 1차 배경제거 과정인 region filling을 적용하여 글자의 배경들을 제거 함으로써 글자를 추출한다. 1차 배경제거의 결과를 검증하고 추가적으로 k-means를 이용한 color clustering을 적용하여 남아있는 배경들을 효율적으로 제거 함으로써 최종 글자영상을 추출한다.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.377-380
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• 2001

본 논문에서는 실내에서 액티브 카메라를 사용하여 다중 인물의 얼굴의 위치를 검출하고. 추적할 수 있으며 조명과 배경 등의 영향에 강인한 추적 알고리즘을 제시하고자 한다. 알고리즘은 얼굴영역 검출, 추적의 2단계로 구성되며, 빠르고 효율적인 얼굴영역 검출은 추적 알고리즘의 성능향상으로 이어지므로, 이를 위해 독특한 색상영역 분포를 갖는 피부 색상 특징을 이용하였다. 표본영상에서 추출된 피부색상 픽셀들을 바탕으로 YCbCr 색상계를 사용하여 얼굴 색상모델을 구축한 후, Gaussian 함수를 사용하여 입력 영상의 픽셀과 얼굴색상모델과의 유사도를 결정하였다. 최종 얼굴 영역은 추출된 영역에 대한 얼굴의 타원특징, 해부학적 특징을 이용하여 결정된다. 추적은 추출된 얼굴영역과 temporal Gaussian 필터를 적용한 움직임 추정을 통한 움직임 검출의 조합으로 이루어진다. 또한, 예측버퍼의 사용으로 탐색영역의 축소로 인한 계산량 감소와 처리 속도의 증가시켰으며, pan/tilt가 가능한 카메라를 사용하여 상호 피드백이 가능하도록 하였다. 제시된 알고리즘은 PC 상에서 시뮬레이션되었으며, 좋은 결과를 얻을 수 있었다.

• Korean Journal of Cognitive Science
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• v.17 no.4
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• pp.337-356
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• 2006

This research was conducted to see the impact of brightness, polarity, and hue diference on legibility and emotional effcts of the word. In the experiment 1, stimuli with three levels of brightness difference and two-typed polarity were used. The results showed that legibility, aesthetics, and preference increased with increasing brightness difference. In the experiment 2, the same stimuli if experiment 1 included four hues: red, green, blue, yellow. As a result, the effects of brightness and polarity and the interaction effect of brightness and polarity on legibility were significant. Also, the effects of brightness, polarity, and hue and the interaction effect of brightness and hue on aesthetics and preference were significant. These results showed that legibility, aesthetics, and preference increased with increasing brightness difference of word and background and positive polarity was better than negative. Aesthetics and preference rating increased according to the following order: red, blue, green, yellow. In addition, the interaction effect of brightness and polarity on legibility was because reaction time of negative polarity was longer than positive at the small brightness difference condition. The interaction effect of brightness and hue on aesthetics and preference ws because the aesthetics rating of hue at the large brightness difference condition had significant difference compared with small brightness difference. In the experiment 3, participants rated text designs and simple color stimuli with 18 emotional adjectives to see the similarity of their emotion. The conclusion was that to reflect the subjective feelings of a rotor on the text design, it would be appropriate to use the rotor on background of the text design.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.343-348
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• 2024

Today, AI image creation programs are optimized for various and specialized purposes such as fashion product advertising, customized fashion style suggestions, and design development, and are actively utilized in the fashion industry. Meanwhile, color is a powerful formative element and plays an important role in expressing images for suggesting products or fashion styles. This study seeks to expand understanding of the use of Midjourney by identifying the characteristics of color combinations that appear in clothing images created using Midjourney among AI image creation tools. The results of this study are as follows. First, the initial image created in Midjourney reflects the existing image color used to create the image more than the color specified in the command. Second, the color combinations that appear in the clothes of the images created in Midjourney are divided into separate and mixed colors. The ratio of colors expressed in a separate color scheme is affected by the color order specified in the command. The number of colors combined in a mixed color scheme appears as a combination of fewer colors than the total number of colors of clothing in the existing image used to create the image in Midjourney and the number of colors specified in the command. Third, caution is needed because changes in background color can affect the user's color perception of the clothes in the image and the formation of the costume image. It is hoped that the results of this study will be helpful in fashion design education and practice.

• The Optical Journal
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• s.130
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• pp.68-71
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• 2010

눈에 띄는 인상적인 사진을 만들기 위해서는 명도와 색상 대비를 통해 주제를 강조하는 방법, 타이밍, 보조피사체 등을 이용한 다양한 방법들이 있다. 그 중 색상 대비란 조합된 색에 의해 주제가 시각적으로 두드러지게 나타나는 것을 말하면 명도 대비는 주변의 발기와 주제의 밝기가 대비를 이뤄 주제가 배경으로부터 돋보이도록 만드는 기법을 말한다. 특히 하나의 움직임 속에서 서로가 균형을 이루고 있는 단 하나의 순간을 찾아내는 타이밍 또한 인상적인 사진을 만드는 요건이다.

• Journal of the Korean Institute of Landscape Architecture
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• v.14 no.2
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• pp.69-80
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• 1986

In order to analyse the color preference quantitatively, specially with reference to the subjects in the age of twenties, 100 subjects(M=50, F=50) that unconsidered other factors were adopted and responded to 4 items of the questionaire. The item no. 1 was to investigate the most prefered color on the white background, no. 2 was to most preferred stimulation -level of lightness in the same hues, no. 3 was to most prefered color on 5 different backgrounds -grey, blue, pink, yellow, and yellow green-, and no. 4 was same as no. 3 but with different color-arrangement Materials for item 1 and 3 were made with transparent acryl-boards(30cm$\times$30cm), on which 16 color chips arranged on circle, for item 4 on lattice, and for item 2 with 16 white boards(8cm$\times$21cm), on which 7 color chips of different lightness-level arranged. Reflectance(Y) and color coordinate(x, y) of all color chips measured with color difference meter were transfered into wavelength(nm), exitation purity(%), and Munsell's value. The results may be summarized as follows: 1) Most prefered color was bluish green with wave1ength about 500nm. As increasing of exitation purity of color, more prefered. 2) When there were 7 different levels of lightness in the same hues, the relationship between the number of preference and the stimulation was inverted U-shaped. 3) With changing the background -color, the prefered colors were contrasting when backgrounds were low or high intensity-stimulation and familiar colors when backgrounds were medium intensity.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.6
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• pp.692-704
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• 2002

In this paper, we present am image retrieval method based on color-spatial features using quadtree and texture information extracted from object MBRs in an image. Tile proposed method consists of creating a DC image from an original image, changing a color coordinate system, and decomposing regions using quadtree. As such, conditions are present to decompose the DC image, then the system extracts representative colors from each region. And, image segmentation is used to search for object MBRs, including object themselves, object included in the background, or certain background region, then the wavelet coefficients are calculated to provide texture information. Experiments were conducted using the proposed similarity method based on color-spatial and texture features. Our method was able to refute the amount of feature vector storage by about 53%, but was similar to the original image as regards precision and recall. Furthermore, to make up for the deficiency in using only color-spatial features, texture information was added and the results showed images that included objects from the query images.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.06a
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• pp.142-145
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• 2001

본 논문에서는 얼굴추출을 하는데 있어서 빠른 속도로 얼굴의 구성요소들을 분할하고 추출한다. 효율적인 분할과 추출물 위해서 3가지의 정보를 사용한다. 첫 번째는 얼굴의 색상정보로써 배경 속의 얼굴을 찾는데 이용한다. 두 번째는 얼굴의 윤곽선 정보로 얼굴의 구성요소를 추출해 내는데 사용한다. 세 번째는 얼굴의 구조적인 정보를 이용하여 색상 및 윤곽선 정보를 이용하여 추출된 요소에 대해 얼굴의 다른 구성요소를 추출하는데 이용한다.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.228-237
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• 2013

In this paper, we propose a normalized cross correlation(NCC)-based multiview background subtraction method which is robust when an object and background have similar color. When the background of the capturing environment is not artificially composed, the regions in the background images which would be occluded by an object tends to have difference colors. The colors of those regions, however, becomes similar when an object enters the capturing environment. Based on this assumption, this paper proposes a concept of GoNCC(Graph of Normalized Cross Correlation). GoNCC is the distribution of NCC between a pixel in an image and pixels related by epipolar constraints with the pixel. The proposed multiview background subtraction method is performed by comparing GoNCC of the current images with the background images. To reduce computational complexity, we perform multiview background subtraction only to the pixels undetermined by single view background subtraction. Experimental results show that the proposed method is more robust to color similarity between an object and background than a single-view background subtraction method and a previous multiview background subtraction method.