• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.321-324
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• 2002

본 논문에서는 다양한 환경하에서 인간의 식별과 감정을 인식할 수 있는 감정 인식 알고리즘을 제안한다. 제안된 알고리즘을 구현하기 위해, 먼저, CCD 칼라 카메라에 의해 획득한 원 영상으로부터 피부색을 이용해 얼굴영상을 얻는 과정을 거친다. 그 다음, 주요 요소분석을 기본으로 하는 얼굴인식기술인 Eigenface를 사용하여 이미지들을 고차원의 픽셀공간으로부터 저차원공간으로의 변환하는 파정을 거친다. 제안된 개인에 대한 식별과 감성인식은 사용한 특징벡터들의 추출로 인한 Eigenface의 가중치와 상관관계를 통해 이루어진다 즉, 영상의 가중치로부터 개인에 대한 식별과 감성정보를 찾는 방법을 제안한다. 마지막으로, 실험을 통해 제안된 방법의 응용가능성을 보인다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.103-114
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• 2005

This paper presents a content-based image retrieval (CBIR) method using the combination of color and texture features. As a color feature, a color autocorrelogram is chosen which is extracted from the hue and saturation components of a color image. As a texture feature, BDIP(block difference of inverse probabilities) and BVLC(block variation of local correlation coefficients) are chosen which are extracted from the value component. When the features are extracted, the color autocorrelogram and the BVLC are simplified in consideration of their calculation complexity. After the feature extraction, vector components of these features are efficiently quantized in consideration of their storage space. Experiments for Corel and VisTex DBs show that the proposed retrieval method yields 9.5% maximum precision gain over the method using only the color autucorrelogram and 4.0% over the BDIP-BVLC. Also, the proposed method yields 12.6%, 14.6%, and 27.9% maximum precision gains over the methods using wavelet moments, CSD, and color histogram, respectively.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.670-672
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• 2005

본 논문은 비전을 기반으로 한 감정인식 로봇에 관한 논문이다. 피부스킨칼라와 얼굴의 기하학적 정보를 이용한 얼굴검출과 감정인식 알고리즘을 제안하고, 개발한 로봇 시스템을 설명한다. 얼굴 검출은 RGB 칼라 공간을 CIElab칼라 공간으로 변환하여, 피부스킨 후보영역을 추출하고, Face Filter로 얼굴의 기하학적 상관관계를 통하여 얼굴을 검출한다. 기하학적인 특징을 이용하여 눈, 코, 입의 위치를 판별하여 표정 인식의 기본 데이터로 활용한다. 눈썹과 입의 영역에 감정 인식 윈도우를 적용하여, 윈도우 내에서의 픽셀값의 변화와 크기의 변화로 감정인식의 특징 칼을 추출한다. 추출된 값은 실험에 의해서 미리 구해진 샘플과 비교를 통해 강정을 표현하고, 표현된 감정은 Serial Communication을 통하여 로봇에 전달되고, 감정 데이터를 받은 얼굴에 장착되어 있는 모터를 통해 표정을 표현한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.216-221
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• 2003

Emotions recognition is a topic on which little research has been done to date. This paper proposes a new method that can recognize the human s emotion from facial image by using eigenspace. To do so, first, we get the face image by using the skin color from the original color image acquired by CCD color camera. Second, we get the vector image which is projected the obtained face image into eigenspace. And then, we propose the method for finding out each person s identification and emotion from the weight of vector image. Finally, we show the practical application possibility of the proposed method through the experiment.

• 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.

• Journal of Digital Convergence
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• v.14 no.5
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• pp.263-271
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• 2016

Localizing an object in image is a common task in the field of computer vision. As the existing methods provide a detection for the single object in an image, they have an utilization limit for the use of the application, due to similar objects are in the actual picture. This paper proposes an efficient method of object localization for image recognition. The new proposed method uses color correlation back-projection in the YCbCr chromaticity color space to deal with the object localization problem. Using the proposed algorithm enables users to detect and locate primary location of object within the image, as well as candidate regions can be detected accurately without any information about object counts. To evaluate performance of the proposed algorithm, we estimate success rate of locating object with common used image database. Experimental results reveal that improvement of 21% success ratio was observed. This study builds on spatially localized color features and correlation-based localization, and the main contribution of this paper is that a different way of using correlogram is applied in object localization.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.111-120
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• 2004

This paper proposes a vector error diffusion method for smear artifact reduction in the boundary region. This artifact mainly results from a large accumulation of quantization errors. In particular, color bands with a smear artifact, the width of a few pixels appear along the edges. Accordingly, to reduce this artifact, the proposed halftoning process excludes the large accumulated Quantization error by comparing the vector norms and vector angles between the error-corrected vector and eight primary color patches. When the vector norm of the error corrected vector is larger than those of eight primary color patches, the quantization error vector is excluded from the quantization error distribution process. In addition, the quantization error is also excluded when the angle between eight primary color patches and error corrected vector is large. As a result, the proposed method enables a visually pleasing halftone pattern to be generated by all three color separations into account in a device- independent color space and reduces smear artifact in the boundary regions.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.142-154
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• 2010

The purpose of this study is to analyze the effects of various spatial characteristics on the land surface temperature and to grasp the characteristics of thermal environment by types of urban area in Changwon, Gyeongsangnam-do. The spatial data were consisted LST, normalized difference built-up index(NDBI) and normalized difference vegetation index(NDVI) obtained from Landsat 5 TM and land use and land cover map classified from high resolution digital aerial photograph($10cm{\times}10cm$). The unit space for spatial analysis was built by $500m{\times}500m$ Vector GRID. According to the results of estimation of relationship between thermal environment and spatial characteristics, LST had the highest positive correlation with NDBI by 0.929 and had high positive correlation with impervious area ratio by 0.857. In order to analysis of thermal environment on land use, types of urban area were classified by 4 of residential focus area, industrial focus area, green focus area and mixed area. According to the results of analysis, mean LST of industrial focus area was showed the highest by $21.10^{\circ}C$. But mean LST of green focus area was analyzed the lowest by $18.85^{\circ}C$. In conclusion, the results of this study investigated the effects of spatial characteristics on urban thermal environment and can provide methods and basic informations about land use planning and development density restriction for reduction of urban heat.