• 한국실내디자인학회논문집
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• 제38호
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• pp.217-224
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• 2003

The purpose of this study is to analyze the recent trend color of bathroom based on analysis result of digital color image processing, to analyze the emotional color of that, and to suggest the harmony color combination for the bathroom. It leads to the two final results. That is, the main color of bathroom image is recognized as three color classifications such as YR-Y, Y-GY, PB-P, 2) from the point of emotional aspect, the trend color of the bathroom can be classified into four image categories: 'modern', 'mild', 'elegant', 'natural'. Finally, under these categories, this paper propose 12 color harmony schema which can be applied to color in, especially bathroom Interior design.

• 한국컴퓨터정보학회논문지
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• 제20권12호
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• pp.9-14
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• 2015

In this paper, we present an color quantization method by complementing the disadvantage of K-means color quantization that is one of the well-known color quantization. We named the proposed method "octree-means" color quantization. K-means color quantization does not use all of the clusters because it initializes the centroid of clusters with random value. The proposed method complements this disadvantage by using the octree color quantization which is fast and uses the distribution of colors in image. We compare the proposed method to six well-known color quantization methods on ten test images to evaluate the performance. The experimental results show 68.29 percent of mean square error(MSE) and processing time increased by 14.34 percent compared with K-means color quantization. Therefore, the proposed method improved the K-means color quantization and perform an effective color quantization.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2000년도 추계종합학술대회논문집
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• pp.153-156
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• 2000

Recently, there has been studied on feature extraction method for efficient content-based image retrieval. Especially, Many researchers have been studying on extracting feature from color Information, because of its advantages. This paper proposes a feature and its extraction method based on color correlogram that is extracted from color information in an image. the proposed method is computed from the image segmented into two parts; the complex part and the plain part. Our experiments show that the performance of the proposed method is better as compared with that of the original color correlogram method.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2016년도 추계학술발표대회
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• pp.510-513
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• 2016

Detecting of the object in image processing is substantial but it depends on the object itself and the environment. An object can be detected either by its shape or color. Color is an essential for pattern recognition and computer vision. It is an attractive feature because of its simplicity and its robustness to scale changes and to detect the positions of the object. Generally, color of an object depends on its characteristics of the perceiving eye and brain. Physically, objects can be said to have color because of the light leaving their surfaces. Here, we conducted experiment in the aquarium fish tank. Different color of fish robots are mimic the natural swim of fish. Unfortunately, in the underwater medium, the colors are modified by attenuation and difficult to identify the color for moving objects. We consider the fish motion as a moving object and coordinates are found at every instinct of the aquarium to detect the position of the fish robot using OpenCV color detection. In this paper, we proposed to identify the position of the fish robot by their color and use the position data to control the fish robot gathering in one point in the fish tank through serial communication using RF module. It was verified by the performance test of detecting the position of the fish robot.

• 보존과학회지
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• 제38권1호
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• pp.14-32
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• 2022

Underwater photographing and image recording are essential for pre-excavation survey and during excavation in underwater archaeology. Unlike photographing on land, all underwater images suffer various quality degradations such as shape distortions, color shift, blur, low contrast, high noise levels and so on. Outcome is very often heavily photographing equipment and photographer dependent. Excavation schedule, weather conditions, and water conditions can put burdens on divers. Usable images are very limited compared to the efforts. In underwater archaeological study in very turbid water such as in the Yellow Sea (between mainland China and the Korean peninsula), underwater photographing is very challenging. In this study, off-site image distortion and color compensation techniques using an image processing/analysis software is investigated as an alternative image quality enhancement method. As sample images, photographs taken during the excavation of 800-year-old Taean Mado Shipwrecks in the Yellow Sea in 2008-2010 were mainly used. Significant enhancement in distortion and color compensation of archived images were obtained by simple post image processing using image processing/analysis software (PicMan) customized for given view ports, lenses and cameras with and without optical axis offsets. Post image processing is found to be very effective in distortion and color compensation of both recent and archived images from various photographing equipment models and configurations. Merits and demerit of in-situ, distortion and color compensated photographing with sophisticated equipment and conventional photographing equipment, which requires post image processing, are compared.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제23권1호
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• pp.74-79
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• 2017

세계 최초의 정지궤도 해양관측위성 센서인 천리안해양관측위성(Geostationary Ocean Color Imager; GOCI)은 적조, 녹조, 모자반, 냉수대, 태풍 등의 해양재해를 실시간으로 모니터링하여 피해를 최소화하는데 활용될 수 있다. 이와 같은 활용성을 극대화하기 위해, 이 논문에서는 천리안해양관측위성의 자료처리 방법 및 절차에 관하여 기술하고 있다. 천리안해양관측위성의 자료처리는 크게 수신, 처리, 저장, 배포로 구분되며, 자료의 종류는 Raw, Level 1, Level 2 등으로 나눠진다. Raw 자료는 위성으로부터 수신한 직후의 자료로 구조화되기 이전의 자료를 의미하고, Level 1 자료는 방사보정 및 기하보정을 통하여 2차원으로 구조화한 반사도 자료를 의미하며, Level 2 자료는 Level 1 반사도 자료에 다양한 해색 알고리즘을 적용하여 엽록소농도, 부유물질농도 등을 추출한 해색자료를 의미한다.

• 한국가구학회지
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• 제22권3호
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• pp.239-243
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• 2011

In this study, the coating properties and surface performance of exotic cherry wood (Prunus serotina) were estimated, reviewing color difference, hardness and abrasion resistibility in order to evaluate probability as construction interior members such as wall and floor. The reduction effect of color difference was represented in the order of water soluble color stain, water soluble transparent stain, and non-coated lumber. However, the tendency of distinct difference according to wood grain pattern was not found. The wavy grain lumber showed better properties in hardness and resistance to abrasion than quarter grain. In conclusion, it was supposed that the application of wavy grain lumber in wall and floor as interior materials would be acceptable in practicality.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.1150-1155
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• 2009

정보화 사회에서 정보의 양은 기술의 발달로 급격하게 증가하고 있다. 그로 인해 정보의 다양화와 복잡성 또한 증가하여 빠른 정보처리에 어려움을 주고 있다. 정보의 복잡성 속에 정보의 구조화, 범주화는 사용자가 쉽게 정보에 접근할 수 있게 만들며 처리 속도도 빠르게 해 준다. 본 연구는 정보의 범주화에서 색을 통한 범주화가 정보처리 속도 향상에 어떠한 영향을 주는지를 실험적으로 확인해 보려 한다. 실험 1은 복잡한 정보를 가진 노선도에서 역을 찾는 과제를 시행 하였을 때, target 역 이름의 색과 노선의 색이 동일 할 때 그렇지 않는 경우 보다 탐색시간을 빠름을 보여주고자 한다. 그리고 실험2는 단어 분류 과제에서 색의 범주화가 단어의미 범주화 보다 빨리 처리되며, 색의 대비가 클 때 더 효과적임을 보여 주고자 한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2017년도 추계학술발표대회
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• pp.944-945
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• 2017

Color image edge detection is an important operation in many image processing areas. This paper presents a new method for edge detection based on the Bhattacharyya distance that can handle arbitrary boundaries by exploring several edge patterns. Experiments show promising results compared to some existing methods.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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• pp.222-224
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• 2009

This paper presents an algorithm that extracts road lane's specific information by using HSI color information and performance enhancement of lane detection base on vision processing of drive assist. As a preprocessing for high speed lane detection, the optimal extraction of region of interest for lane boundary(ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled and it also increases reliabilities by deleting edges those are misrecognized. Road lane is extracted with simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since noise can be removed by using saturation and brightness of HSI color model. Also it searches for the road lane's color information and extracts characteristics. The real road experimental results are presented to evaluate the effectiveness of the proposed method.