• 한국실내디자인학회논문집
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• 제15권4호
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• pp.123-128
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• 2006

The purpose of the research is to estimate the amount of a color image reaction variation by changing areas in order to design the method to reduce an error about the color sample when it is applied in the real situation. The summary of the results acquired in this research is as followed. (1) With fixed observing distance of 1m, we observed that the value and chroma of each color object became higher as sight angle was increased as $2^{\circ},\;10^{\circ},\;and\;30^{\circ}$, even though the variation ratio was different. (2) With fixed sight angle of 10, we observed that the value and chroma of each color object becane higher as observing distance was changed from 1m to 3.3m, even though the variation ratio was different. (3) With same area, we observed that the values and chromas of each color object in the conditions of $1m-30^{\circ}\;and\;3.3m-10^{\circ}$ were almost same. (4) When the area became larger, the subjects tended to feel that colors were bright and clear with the increase of tone. In all the colors, the variation of a color reaction in chroma is higher than those in value. In future, we can observe the limit in applying to colors in the architecture by identifying the tendency of the color change according to the area change qualitatively.

• 한국포장학회지
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• 제27권3호
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• pp.203-210
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• 2021

With the development of package printing technology, the package has expanded from the basic function of protecting products to the marketing function through package design. Color, the visual element that composes the package design, is delivered to the consumer most quickly and effectively. As color marketing of these package designs expands, accurate color reproduction that the product wants to express is becoming more important. The color of an object is transmitted by absorption and scattering of light. Spectral reflectance refers to the intensity of light reflected by an object at different wavelengths by the spectral effect. As a result, the color of the object is expressed in various colors. Packaged printing inks have their own absorption and scattering coefficients, and the Kubelka-Munk model for color reproduction and prediction defines the relationship between these correlation coefficients through reflectance. In the Kubelka-Munk model for color reproduction and prediction, the relationship between the absorption and scattering coefficients (K/S) of printed material is predicted as the sum of the K/S values according to the mixing ratio of all color ink used. In this study, the reflectance of the measured print is reversely calculated at the mixing ratio of print ink using the Kubelka-Munk model. Through this, the relationship value of the ink-specific absorption/scattering coefficient constituting the final printed material is predicted. Delta E is derived through the predicted reflectance, and the similarity between the measured value and the predicted value is confirmed.

• 한국멀티미디어학회논문지
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• 제5권6호
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• pp.616-624
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• 2002

본 논문에서는 영상에 포함된 중심 객체를 추출하는 방법에 대해 제시한다. 중심 객체는 촬영의 중심이 되어 영상의 중앙 부분에 비교적 큰 면적을 차지하는 객체로 정의하는데 영상 내용에 대한 중요한 정보를 제공한다. 중심 객체 추출을 위해 우선 입력 영상에 대해 해상도를 줄여가며 영상 분할하고 분할된 결과에 대해 계층적 영역 병합을 수행함으로써 객체가 많은 수의 영역으로 세분화되어 영상 분할되는 것을 방지할 수 있도록 하였다. 분할된 각 영역은 영상의 경계와 접하는 경계 영역과 그 외의 비경계 영역으로 분류하였다. 비경계 영역은 중심 객체에 해당될 가능성이 있는 영역으로써, 이들 중에서 영상 중심 부근에서 가장 큰 크기를 차지하는 영역이 핵심객체영역으로 선택된다. 또한 경계 영역 중에서 영상의 네 모서리에 인접하는 영역은 핵심배경영역으로 선택되어 핵심객체영역과 함께 중심 객체 추출에 이용된다. 각 비경계 영역은 핵심 배경영역및 핵심객체영역과 칼라 분포 유사도출 비교하여 배경영역과 전경영역으로 분류된다. 핵심객체영역 및 핵심객체영역과 연결성을 가지는 전경영역이 최종 중심 객체로 선택된다. 본 논문에서 제안된 방법은 비교적 복잡한 배경을 갖는 영상에 대해서도 어느 정도 만족할 만한 결과를 얻을 수 있었다.

• 전기학회논문지
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• 제67권4호
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• pp.586-594
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• 2018

In this paper, we propose a livestock theft detection system through moving object classification and tracking method. To do this, first, we extract moving objects using GMM(Gaussian Mixture Model) and RGB background modeling method. Second, it utilizes a morphology technique to remove shadows and noise, and recognizes moving objects through labeling. Third, the recognized moving objects are classified into human and livestock using skeletal features and color similarity judgment. Fourth, for the classified moving objects, CAM (Continuously Adaptive Meanshift) Shift and Kalman Filter are used to perform tracking and overlapping judgment, and risk is judged to generate a notification. Finally, several experiments demonstrate the feasibility and applicability of the proposed method.

• 대한의용생체공학회:의공학회지
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• 제13권1호
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• pp.39-46
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• 1992

This paper proposes the method that evoked potentials stimulated by object colors are analyzed and examined on the phenomemon of color sensory. The method which is used to estimate the signal is time-varying. filtering (TVF). At the results of experiment which used object colors, it is shown that color sensory times of red are within the range of 0.0~0.25[sec], those of yellow are within the range of 0.25~0.55[sec], and those of blue are within the range of 0.55~0.75[sec]; they are inclined to sequence in accending order as red, yellow, and blue.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2007년도 학술대회 1부
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• pp.298-301
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• 2007

Computational speed plays key role in background subtraction and shadow detection, because those are only preprocessing steps of a moving object segmentation, tracking and activity recognition. A color intensity variation based approach fastly detect a moving object and extract shadow in a image sequences. The moving object is subtracted from background using meanmax, meanmin thresholds and shadow is detected by decrease limit and correspondence thresholds. The proposed approach relies on the ability to represent shadow cast impact by offline experiment dataset on sub grouped RGB color space.

• 한국멀티미디어학회논문지
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• 제19권4호
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• pp.681-688
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• 2016

In the intelligent video surveillance, recognizing the moving objects is important issue. However, the conventional moving object recognition methods have some problems, that is, the influence of light, the distinguishing between similar colors, and so on. The recognition methods for the moving objects using depth information have been also studied, but these methods have limit of accuracy because the depth camera cannot measure the depth value accurately. In this paper, we propose a recognition method for the moving objects by using both the depth and the color information. The depth information is used for extracting areas of moving object and then the color information for correcting the extracted areas. Through tests with typical videos including moving objects, we confirmed that the proposed method could extract areas of moving objects more accurately than a method using only one of two information. The proposed method can be not only used in CCTV field, but also used in other fields of recognizing moving objects.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2007년도 추계종합학술대회
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• pp.277-280
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• 2007

특정컬러정보 검출기반의 이동객체 탐색 알고리듬을 구현한다. 입력 이미지에 대해 조도변화 및 노이즈 제거 등을 위해 전처리 과정을 거치고, 이동객체 탐색은 R,G,B 각 채널의 영상차를 이용하여 객체를 검색한다. 실험 결과 검색 속도는 윤관선 탐색 및 정합법에 비해 15% 향상되었고 안정적이다. 또한 컬러 정보 기반의 객체 탐색이 가능함을 제시하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권2호
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• pp.142-148
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• 2004

In this paper, we propose the color fuzzy decision algorithm to face segmentation in a color image. Our algorithm can segment without the user's interaction by fuzzy decision marking. And it removes small parts such as a noise using wavelet morphology in the image obtained by applying the fuzzy decision algorithm. Also, it merges and chooses the face region in each quantization image through rough sets. This video object division algorithm is shown to be superior to a conventional algorithm.

• 전기학회논문지
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• 제67권2호
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• pp.293-300
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• 2018

We propose a moving object extraction and tracking method for improvement of animal identification and tracking technology. First, we propose a method of merging separated moving objects into a moving object by using FCM (Fuzzy C-Means) clustering algorithm to solve the problem of moving object loss caused by moving object extraction process. In addition, we propose a method of extracting data from a moving object and a method of counting moving objects to determine the number of clusters in order to satisfy the conditions for performing FCM clustering algorithm. Then, we propose a method to continuously track merged moving objects. In the proposed method, color histograms are extracted from feature information of each moving object, and the histograms are continuously accumulated so as not to react sensitively to noise or changes, and the average is obtained and stored. Thereafter, when a plurality of moving objects are overlapped and separated, the stored color histogram is compared with each other to correctly recognize each moving object. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.