• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.99-107
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• 2019

Retinex-based image enhancement is a technique that utilizes the property that the human visual characteristics are sensitive to the difference from the surrounding pixel value rather than the pixel value itself. These Retinex-based algorithms show different characteristics of the improved image depending on the applied color space or gamma correction. In this paper, we set eight different experimental conditions according to the application of color space and gamma correction, and analyze the objective and subjective performance of each Retinex based image enhancement algorithm and apply it to the implementation of Retinex based algorithm. In the case of gamma correction, quantitative low entropy images and low contrast images are obtained. The application of Retinex technique in HSI color space rather than RGB color space is found to be high in overall subjective image quality as well as maintaining color.

• Proceedings of the Korean Printing Society Conference
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• 2000.12a
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• pp.0.2-0
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• 2000

Most important step for the color matching in scanner is the color coordinate transformation from the scanner RGB space to device independent uniform color space. A variety of color calibration technologies have been developed for input device. Linear or nonlinear matrices have been conveniently applied to correct the color filter\`s mismatch with color matching function in scanners. The color matching accuracy is expected to be further improved when the nonlinear matrices are optimized into subdivided smaller color spaces than in single matrix of the entire color space. This article proposed the scanner calibration method using subspace division regression analysis and it were compared with conventional method.

• Journal of the Korean Graphic Arts Communication Society
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• v.19 no.1
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• pp.4-16
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• 2001

Most important step for the color matching in scanner is the color coordinate transformation from the scanner RGB space to device independent uniform color space. A variety of color calibration technologies have been developed for input device. Linear or nonlinear matrices have been conveniently applied to correct the color filter's mismatch with color matching function in scanners. The color matching accuracy is expected to be further improved when the nonlinear matrices are optimized into subdivided smaller color spaces than in single matrix of the entire color space. This article proposed the scanner calibration method using subspace division regression analysis and it were compared with conventional method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.181-185
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• 1996

Color image is largely corrupted by various ambient illumination. However, human perceives always white color as white under any illumination because of a characteristic of human vision, called color constancy. In the conventional algorithm which applied the constancy effect, after the RGB color space is transformed to the IHS(Intensity, Hue, and Saturation) color space, then the hue is preserved and the intensity or the saturation is properly enhanced. Then the enhanced IHS color is reversely transformed to the RGB color space. In this process, the color distortion is included due to the color gamut error. But in the proposed algorithm, there is not transformation. In that, the RGB color is considered as 3 dimensional color vector and we assume that white color is the natural daylight. As the color vector of the illumination can be calculated as the average vector of R, G, and B image, we can achieve the constancy effect by simply rotating the illumination vector to the white color vector. The simulation results show the efficiency of the vector rotating process for color image enhancement.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.1
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• pp.39-45
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• 2019

We propose an active color model based method for tracking motions of multiple human using a networked multiple-camera system in IoT space as a human-robot coexistent system. An IoT space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of IoT space as well. One of the main goals of IoT space is to assist humans and to do different services for them. In order to be capable of doing that, IoT space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and IoT space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in IoT space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.153-156
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• 2005

Skin region detection in images is an important process in many computer vision applications targeting humans such as hand gesture recognition and face identification. It usually starts at a pixel-level, and involves a pre-process of color spae transformation followed by a classification process. A color space transformation is assumed to increase separability between skin classes and other classes, to increase similarity among different skin tones, and to bring a robust performance under varying imaging conditions, without any complicated analysis. In this paper, we examine if the color space transformation actually brings those benefits to the problem of skin region detection on a set of human hand images with different postures, backgrounds, people, and illuminations. Our experimental results indicate that color space transfomation affects the skin detection performance. Although the performance depends on camera and surround conditions, normalized [R, G, B] color space may be a good choice in general.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.385-388
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• 2003

In this paper, we propose a new saturation enhancement algorithm which is processed on the new color space, called Normalized YCbCr(NYCbCr). The algorithm consists of two processing unit. One is color space conversion from YCbCr to NYCbCr, and the other is using adaptive saturation mapping function(ASMF). NYCbCr color space is designed to prevent shortcomings such as luminance and hue shift of YCbCr color space and by saturation enhancement. ASMF is effective to enhance saturation properly for each image and to protect low saturation regions of color images from over-saturation. we verified our method using several color images. Experimental results show that the proposed method enhance the saturation with minimizing Luminance and Hue shift.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.64-65
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• 2020

With the modernization fund of the government, construction of new passenger ships make the level of interior design is improved, but the space where the crew is working is still inadequate. This study is to investigate the color environment of the Bridge Deck and Engine Room among working spaces of passenger ships. It aims to improve the mental health of crews and set up a safe working environment by presenting color design, and suggest the specificity of ship's working space and color value with matching the color environment.

• Journal of the Korean Graphic Arts Communication Society
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• v.22 no.2
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• pp.163-178
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• 2004

In this study, the CIE RGB color space which was one of the most popular device-dependent application program in digital image processing was adopted to make the profile with the device information. The profile was applied to the digital image of a JPEG file format. The result was compared with the color reproduction of another digital image of a JPEG file format, which was made in the e-sRGB color space that had the color spaces allocated to each reproduced color of an image and device-independent colors. In this way it was investigated which color space was more appropriate for digital image processing for web printing and if the e-sRGB color space was good as a color management tool that didn't depend on a device in processing a digital image for web printing.

• Journal of Sensor Science and Technology
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• v.21 no.1
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• pp.28-33
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• 2012

The visual sensing of human hands plays an important part in many man-machine interaction/interface systems. Most existing visionbased hand detection techniques depend on the color cues of human skin. The RGB color image from a vision sensor is often transformed to another color space as a preprocessing of hand detection because the color space transformation is assumed to increase the detection accuracy. However, the actual effect of color space transformation has not been well investigated in literature. This paper discusses a comparative evaluation of the pixel classification performance of hand skin detection in four widely used color spaces; RGB, YIQ, HSV, and normalized rgb. The experimental results indicate that using the normalized red-green color values is the most reliable under different backgrounds, lighting conditions, individuals, and hand postures. The nonlinear classification of pixel colors by the use of a multilayer neural network is also proposed to improve the detection accuracy.