• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.126-131
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• 2001

현재 널리 사용되는 hand-held형 단말기들은 영상을 표현할 때 제한된 수의 칼라만으로 표현할 수 있다. 따라서 자연색 칼라 팔레트를 이용하여 단말기에 나타낼 때 최적의 칼라 팔레트를 구현하는 것과 원영상의 각각의 칼라로부터 팔레트 칼라로 최적으로 정합 시키는 것이 요구된다. 본 논문에서는 효율적으로 칼라 팔레트를 설계하는 히스토그램 기반 영상 의존적 스칼라 양자화 알고리즘을 제안한다. 제안 알고리즘은 칼라 우선순위 결정 부분과 양자화 부분으로 구성되며 양자화 후 ANC(Adaptive Neighborhood-Clustering) 알고리즘을 적용하여 성능을 개선한다. 이 방법은 자연색 칼라 영상을 적은 비트로 표현했음에도 출력 영상이 인간의 눈에 적합하다.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.559-562
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• 2020

본 논문에서는 한국어 입력 텍스트의 의미를 반영하는 색상 팔레트를 생성하는 방법을 제안한다. 기존 영문 모델에서 한국어의 특수성을 고려하여 입력 방법과 형태소 분석, 임베딩 등 여러 조건을 달리한 접근을 시도하고 최종적으로 두개의 모델을 선정하여 평가를 진행한다. 정량적 평가인 단일 팔레트 다양성 평가와 정성적 평가인 사용자 평가를 진행하였으며 결과 기존 영문 버전보다 다양성이 높았고 사용자가 실제 팔레트 보다 생성된 팔레트를 선호하는 비율도 향상되었다. 이번 연구로 한국어 임베딩을 활용하여 팔레트를 생성하였을 때 보다 다양한 색상과 의미적으로도 적합한 색상을 선정함을 확인할 수 있었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.587-591
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the color product.(bad pallets) An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE color pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labelling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets. The labelling algorithm permits to separate all of the connected components appearing on the pallets. Labelling the connected regions of a image is a fundamental computation in image analysis and machine vision, with a large number of application. Also, we suggested vision processing program in window environment. Simulations and experimental results demonstrate the performance of the proposal algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.6
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• pp.1157-1162
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the color product.(bad pallets) An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE color pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labelling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets. The labelling algorithm permits to separate all of the connected components appearing on the pallets. Labelling the connected regions of a image is a fundamental computation in image analysis and machine vision, with a large number of application. Also, we suggested vision processing program in window environment. Simulations and experimental results demonstrate the performance of the proposal algorithm.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1994.06a
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• pp.334-338
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• 1994

• Proceedings of the Korea Society of Design Studies Conference
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• 2005.05a
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• pp.158-159
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• 2005

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1624-1635
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• 1996

Palletized color images are the dominant type of the image used on Internet and World-Wide Web. In spite of this, most image compression and progressive transmission algorithm have been designed for continuous-tone images. Pallettize images. Palletized images differ from continuous-tone images in such a aspect that values are lookup table indices a new pyramid structure for compression and progressive transmission of a palletized image. In the proposed pyramid structure, the color of a node at higher level is the one that occupies the most part in 4 sons and each node is represented by a type code and several color codes. Since the proposed method do not exploit spatial correlation in an image, it is ideally applied to lossless compression and progressive transmission of palletized images. We have confirmed this through the experimental results.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.535-542
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• 2003

This study is concerned with an assistive technology which reduces color blinds´s confusion when they access electronic documents including color objects in their computers. In this study, 1 restrict the assistive technology would apply to windows operating system, 256 color mode and implement to minimize color distortion which occurs in multi window environments because of color approximation process. As a basic palette, I use a 216 colors web safe palette which the Christine proposed as a standard for color blind, expand it to 256 colors to apply all computer displays using Microsoft Windows as its operating system and implement it as windows application. To test its effectiveness, I use a simulator for dichromats, as results of the test, the developed color vision deficiency correction S/W is effective to reduce the confusion. It is more effective to use the implemented S/W in both of design and client process for electronic documents.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.21-26
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• 2004

Color image quantization is a process of selecting a set of colors to display an image with some representative colors without noticeable perceived difference. It is very important in many applications to display a true color image in a low cost color monitor or printer. The basic problem is how to display 256 colors or less colors, called color palette, In this paper, we propose improved binary tree vector quantization based on spatial sensitivity which is one of the human visual properties. We combine the weights based on the responsibility of human visual system according to changes of three Primary colors in blocks of images with the process of splitting nodes using eigenvector in binary tree vector quantization. The test results show that the proposed method generates the quantized images with fine color and performs better than the conventional method in terms of clustering the similar regions. Also the proposed method can get the better result in subjective quality test and WSNR.

• Science of Emotion and Sensibility
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• v.2 no.2
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• pp.67-74
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• 1999

본 연구는 실제 현장에서 적용할 수 있는 보다 구체적인 감성 데이터를 제공하기 위한 시도로서, 메이크업의 주요한 색채특성을 평가변인으로 하여 칼라 시뮬레이션 실험 및 분석을 실시하여, 최종적으로 색채감성 분석기법에 의한 이미지 유형별 예측모델을 작성하였다. 그 결과, $\ulcorner$품위있는.귀족적인$\lrcorner$, $\ulcorner$깔끔한.여성스러운$\lrcorner$, $\ulcorner$강렬한.도발적인$\lrcorner$, $\ulcorner$캐주얼한.경쾌한$\lrcorner$, $\ulcorner$수수한.부드러운$\lrcorner$의 5가지 이미지유형이 추출되었고, 이미지유형별로 이미지와 색채특성간의 정량적 예측모델을 작성한 후, 그 결과를 토대로 이미지유형별 색채팔레트를 제시하였다.