• Journal of the Korea Society of Computer and Information
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• v.15 no.3
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• pp.27-35
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• 2010

Accurately extracting skin color regions is very important in various areas such as face recognition and tracking, facial expression recognition, adult image identification, health-care, and so forth. In this paper, we evaluate the performances of several skin color detection algorithms in indoor environments by changing the distance between the camera and the object as well as the background colors of the object. The distance is from 60cm to 120cm and the background colors are white, black, orange, pink, and yellow, respectively. The algorithms that we use for the performance evaluation are Peer algorithm, NNYUV, NNHSV, LutYUV, and Kimset algorithm. The experimental results show that NNHSV, NNYUV and LutYUV algorithm are stable, but the other algorithms are somewhat sensitive to the changes of backgrounds. As a result, we expect that the comparative experimental results of this paper will be used very effectively when developing a new skin color extraction algorithm which are very robust to dynamic real environments.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.69-76
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• 2010

The segmentation of moving object in video sequence is a core technique of intelligent image processing system such as video surveillance, traffic monitoring and human tracking. A typical method to segment a moving region from the background is the background subtraction. The steps of background subtraction involve calculating a reference image, subtracting new frame from reference image and then thresholding the subtracted result. One of famous background modeling is Gaussian mixture model (GMM). Even though the method is known efficient and exact, GMM suffers from a problem that includes false pixels in ROI (region of interest), specifically shadow pixels. These false pixels cause fail of the post-processing tasks such as tracking and object recognition. This paper presents a method for removing false pixels included in ROT. First, we subdivide a ROI by using shape characteristics of detected objects. Then, a method is proposed to classify pixels from using histogram characteristic and comparing difference of energy that converts the color value of pixel into grayscale value, in order to estimate whether the pixels belong to moving object area or shadow area. The method is applied to real video sequence and the performance is verified.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.889-898
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• 1997

Most general content-based image retrieval techniques use color and texture as retrieval indices. Spatial information is not used to color histogram and color pair based on color retrieval techniques. This paper proposes the selection of a set of representative in the duplicated color histogram, the analysis of spatial information of the selected colors and the image retrieval process based on the duplicated color histogram and spatial information. Two color historgrams for background and object are used in order to decide on color selection in the duplicated color histogram. Spatial information is obtained using a maximum entropy discretization. A retrieval process applies to duplicated color histogram and spatial to retrieve input images and relevant images. As the result of experiment of the image retrieval, improved color his togram and spatial information method hs increased the retrieval effectiveness more the color histogram method and color pair method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.2
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• pp.81-87
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• 2013

Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter (AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.1
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• pp.61-67
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• 2014

Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter(AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

• Journal of the Semiconductor & Display Technology
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• v.18 no.2
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• pp.67-72
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• 2019

This paper proposes a new method for the recognition of resistor color band using a color segmentation in a HSI color model. The proposed method firstly segments a resistor in a chromatic color as a ROI from a background. Secondly, the color bands of the resistor are segmented by vertical projection profile using both the intensity and the saturation differentiation and finally, it recognizes the colors of the segmented color bands using hue, saturation and intensity values. The final results are the value of the resistor and the names of the recognized color. The proposed method is implemented using C language in Raspberry Pi system with a camera module for a real-time image processing. Experiments were conducted by using various resistor images. The results show that the proposed method is successful for the recognition of resistor color band.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1132-1137
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• 2011

In this paper, we propose Modified Multi CAMShift Algorithm(Modified Multi Continuously Adaptive Mean Shift Algorithm) that extracts skin color area and tracks several human body parts for real-time human tracking system. Skin color area is extracted by filtering input image in predefined RGB value range. These areas are initial search windows of hands and face for tracking. Gaussian background model prevents search window expending because it restricts skin color area. Also when occluding between these areas, we give more weights in occlusion area and move mass center of target area in color probability distribution image. As result, the proposed algorithm performs better than the original CAMShift approach in multiple object tracking and even when occluding of objects with similar colors.

• Journal of Korea Game Society
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• v.18 no.6
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• pp.49-58
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• 2018

This study analyzes semiotic aspects of game concept art which is developed considering individual 's color experience. The six stages of Frank H. Mahnke's color pyramid are roughly classified into three categories, and how the game concept art meets each stage. Using the Roland Barthes's mythological-symbolic model of meaning, The meaning of righteousness and the characteristics of newly derived symbols. The results showed that colors could make the background stage more recognizable or intended to have a particular impression. In this way, game concept art, in which what is intended to be implemented in game development, can identify various functions and possibilities of game concept art, such as presenting game convenience as well as impression through a combination of various colors.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.2
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• pp.1-8
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• 2003

This paper proposes an object-based image retrieval technique based on the dominant color pair information. Most of existing methods for content based retrieval extract the features from an image as a whole, instead of an object of interest. As a result, the retrieval performance tends to degrade due to the background colors. This paper proposes an object based retrieval scheme, in which an object of interest is used as a query and the similarity is measured on candidate regions of DB images where the object may exist. From the segmented image, the dominant color pair information between adjacent regions is used for selecting candidate regions. The similarity between the query image and DB image is measured by using the color correlogram technique. The dominant color pair information is robust against translation, rotation, and scaling. Experimental results show that the performance of the proposed method has been improved by reducing the errors caused by background colors.

• Fashion & Textile Research Journal
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• v.10 no.6
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• pp.1014-1022
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• 2008

This study focuses on practical appliance of color therapy to skin care. After visiting the notion of color therapy and skin care, this study considers the ideas and background theories for diagnosis of constitution and skin. Cosmic duals force five element theory developed in China was the first introduction; Ayurvedic medicine and seven chakra notion are examined. Cosmic duals force five element theory, an idea describing the composition and movement rule of the cosmic components, adopted five colors(white, yellow, red, blue, and black) for cure purposes. In future, mental effect of the color is examined in the latter part of this study. The practice of the color therapy assigns solarized cream treatment and photo therapy, simultaneously proposes the use of color therapy to the skin care. For the diagnosis of the constitution, cosmic duals force five element theory and ayurvedic medicine are followed in a sequence. Cosmic duals force five element theory introduces five colors. Constitution medicine considers four types, ayurvedic medicine adopts three types, and seven colors are mentioned as chakra colors. Such a variations lead to possible disagreement on constitution analysis and driven colors. This study adopts the above methodologies for selecting potential color therapy for skin care. Adopt of selected cases are purely a part of the proposal. Initially, examined theories serve as a pilot for selecting a representative hypothesis. Followed selection of constitution and matched color for the use of the skin care are the scope of this study. In summary, background methodologies are implemented for the calculation of color therapy.