• Proceedings of the Korea Contents Association Conference
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• 2015.05a
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• pp.303-304
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• 2015

최근 차량을 이용한 범죄가 점점 증가하고 있고, 그로인해 범죄 차량의 식별 또한 많은 사람들의 관심을 받고 있다. 본 논문에서는 차량 식별을 위해 방범용 CCTV 영상을 이용한다. 차량 방범을 위한 CCTV 이미지 속에서 얻을 수 있는 차량 내 정보는 크게 번호판, 모델, 크기, 색상 등 여러 가지가 있는데, 본 논문에서는 그중 하나인 색상을 인식하는 방법에 대하여 제안한다. 기존에는 여러 가지 색상공간을 이용하여 추출하는 방법을 많이 사용했는데, 단순히 색상공간만으로는 무채색의 차량 추출이 어렵다. 이를 보완하기 위해 HSI 색상공간과 히스토그램의 분산을 분석하는 방법을 제안한다. 이를 이용하여 차량을 보다 정확한 색상별로 검색하는 것이 가능하며, 또한 차량 외의 다른 물체들의 색상 인식에도 응용 가능하다.

• Annual Conference of KIPS
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• 2005.11a
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• pp.1385-1388
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• 2005

최근 3 차원 스캐닝(Scanning) 기술의 발달로 형상 및 색상 정보 데이터를 동시에 획득할 수 있게 되었다. 특히 한번의 측정으로 다량의 데이터를 확보할 수 있기 때문에 3 차원 데이터의 정합(Registration) 및 병합(Merging) 과정에서 계산량이 증가하게 된다. 또한 정합과 병합 후의 대용량 데이터 자체로는 3 차원 모델의 저장, 전송, 처리 및 렌더링(Rendering) 등의 과정에서 어려움이 있다. 따라서 모델의 기하 정보와 색상, 질감, 곡률 등의 속성 정보를 유지하면서 데이터의 양을 감소시키는 메쉬 간략화 기술이 필요하다. 현재 널리 쓰이는 이차 오차 척도(Quadric Error Metric) 방법으로 메쉬를 극심하게 감소하게 되면 오차가 누적되어 기하 정보 및 속성 정보가 소실된다. 본 연구에서는 이를 방지하기 위해 이차 오차 척도 감소화 과정에서 곡률과 색상 기반의 정점 재조정 방법을 제안한다.

• Proceedings of the Costume Culture Conference
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• 2003.04a
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• pp.72-73
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• 2003

본 연구는 간호사복의 색상 및 문양에 따른 이미지를 분석하고, 색상과 문양이 조합을 이루었을 때 어떤 이미지로 통합되는지를 규명하고, 피험자에 따라 이미지지각의 차이를 알아보는데 목적이 있었다. 연구방법으로는 준실험 연구방법으로 피험자간 설계를 하였으며, 피험자는 대전, 충남지역의 대학생을 대상으로 시행하여 통계에 적합한 739부를 사용하였다. 연구에 사용된 자극물은 간호사복 catalog에서 선택한 모델에게, 색상(흰색, 분홍색, 하늘색, 녹색, 베이지색)과 문양(무지, 줄, 꽃)을 조합한 총 13개의 자극물을CAD simulation으로 제작했다. (중략)

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.356-357
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• 2018

상온에서의 식자재의 시간에 따른 색상 변화 정도를 통해 식자재의 신선도를 파악한다. 식자재 데이터는 임의의 식자재를 선택하여 온도, 습도 등의 외부환경이 동일한 실험환경을 조성한 후 일정 시간 간격으로 식자재 영상을 획득하여 얻는다. 영상 속 식자재의 색상은 기본이 되는 RGB 색상 모델에서 빛에 대하여 강건한 HSV 색상으로 변환 산출하여 변색 정보를 파악한다. 식자재의 기존 색상과 변색 정도를 일련의 관계식으로 산출하며, 산출된 수식을 통하여 영상 속 식자재의 신선도를 산출 추정이 가능하다. 본 논문에서 제안된 기술은 요식업계에서 식자재를 관리할 때 적용하여 식자재를 관리할 수 있다.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.563-572
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• 2006

Advantage that light transmission treatment way of most suitable through skin can investigate light directly in part ar there is difference in ability photoelectricity month by diverse complexion of horn character department which is branch or head of a family outside part of skin and treatment according to various patient can be inappropriate. By result that this research uses color information after search each color ingredient that ingredient of HIS and YIQ that use method, color information to use skin impedance way and color information through skin area ion and difference video to do fixed measuring by light investigation way by skin impedance corresponds to skin color in an experiment though is most universal result according to patient's skin model area detection each single person's skin model through videotex automatically create and because measuring, investigate skin color, energy, wave length, approximately, transmission time, model of most suitable that draw pulse delay and so on and want and special quality, and saved standard of disease treatment pulse modeling by skin impedance, and design and manufacture light investigation pulse modeling system of most suitable by skin subordinate, and constructed suitable treatment pulse database by skin color.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.11
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• pp.521-528
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• 2015

Road-view object classification methods are mostly influenced by weather and illumination conditions, thus the most of the research activities are based on dataset in clean weathers. In this paper, we present a road-view object classification method based on color segmentation that works for all kinds of weathers. The proposed method first classifies the weather and illumination conditions and then applies the weather-specified color models to find the road traffic signs. Using 5 different features of the road-view images, we classify the weather and light conditions as sunny, cloudy, rainy, night, and backlight. Based on the classified weather and illuminations, our model selects the weather-specific color ranges to generate Gaussian Mixture Model for each colors, Green, Yellow, and Blue. The proposed method successfully detects the traffic signs regardless of the weather and illumination conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5A
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• pp.375-387
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• 2012

This paper proposes a new real-time object tracking algorithm using particle filters with color and texture features in moving CCD camera images. If the user selects an initial object, this region is declared as a target particle and an initial state is modeled. Then, N particles are generated based on random distribution and CS-LBP (Centre Symmetric Local Binary Patterns) for texture model and weighted color distribution is modeled from each particle. For observation likelihoods estimation, Bhattacharyya distance between particles and their feature models are calculated and this observation likelihoods are used for weights of individual particles. After weights estimation, a new particle which has the maximum weight is selected and new particles are re-sampled using the maximum particle. For performance comparison, we tested a few combinations of features and particle filters. The proposed algorithm showed best object tracking performance when we used color and texture model simultaneously for likelihood estimation.

• Journal of the Korea Computer Graphics Society
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• v.27 no.2
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• pp.1-11
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• 2021

In a virtual environment, a 3D workspace and 3D interaction are possible, but most virtual reality applications use a 2D color picker. This paper implements a 3D color picker based on 3D color space in a virtual environment, and compares color selection performance with the existing 2D color picker. The 3D color picker is intuitive by using the 3D color space as it is, and it can position the 3D pointer at a specific point in the color space using a controller, which is a virtual reality device, so a user can select a color in one step. On the other hand, the 2D color picker has the advantage of being familiar with existing users who work with colors in a computer environment, but has a disadvantage that requires several steps of user interaction since it has to set color properties through 2D interfaces. Based on user experiments, we confirmed the usefulness of a 3D color picker in addition to a 2D color picker in a virtual environment, and it was possible to perform natural 3D work in a virtual environment using the 3D color picker.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.183-189
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• 2015

In this paper, we propose an object tracking method using the color information of the image in surveillance network. This method perform a object detection using of adaptive color model. Object contour detection plays an important role in application such as object recognition. Experimental results demonstrate successful object detection over a wide range of object's variation in color and scale. In applications to detect an object in real time, when transmitting a large amount of image data it is possible to find the mode of a color distribution. The specific color of an object is modified at dynamically changing color in image. So, this algorithm detects the tracking area information of object within relevant tracking area and only tracking the movement of that object.Through experiments, we show that proposed method is more robust than other methods under certain ideal situations.

• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.25-36
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• 2008

In this paper, we present a robust hand recognition approach to sudden illumination changes. The proposed approach constructs a background model with respect to hue and hue gradient in HSI color space and extracts a foreground hand region from an input image using the background subtraction method. Eighteen features are defined for a hand pose and multi-class SVM(Support Vector Machine) approach is applied to learn and classify hand poses based on eighteen features. The proposed approach robustly extracts the contour of a hand with variations in illumination by applying the hue gradient into the background subtraction. A hand pose is defined by two Eigen values which are normalized by the size of OBB(Object-Oriented Bounding Box), and sixteen feature values which represent the number of hand contour points included in each subrange of OBB. We compared the RGB-based background subtraction, hue-based background subtraction and the proposed approach with sudden illumination changes and proved the robustness of the proposed approach. In the experiment, we built a hand pose training model from 2,700 sample hand images of six subjects which represent nine numerical numbers from one to nine. Our implementation result shows 92.6% of successful recognition rate for 1,620 hand images with various lighting condition using the training model.