• Journal of Broadcast Engineering
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• v.23 no.5
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• pp.714-717
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• 2018

This paper presents a method of HDR imaging with adaptive saturation compensation for brightness change. The saturation of HDR images were lighten on dark region because conventional HDR methods have focused on brightness change. Therefore, the proposed HDR method compensates saturation adaptively according to brightness change. For experiments of several images, the proposed algorithm is superior to conventional HDR methods qualitatively and quantitatively in terms of color saturation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.553-555
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• 2015

In this paper, we proposed the blue-green algae monitoring system using the HSV(Hue Saturation Value) color model. The proposed system is to extract the image data from the camera of raspberry pie server by an wireless network, and it is analyzed through the HSV color model. We implemented a web server to provide the information of the XML data which was analyzed from the raspberry pie server. Also, the mobile app was developed to view the XML data on smart devices.

• Korean Institute of Interior Design Journal
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• v.21 no.1
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• pp.40-50
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• 2012

This study aims at suggesting the applicability of color combination based upon the characteristics of environmental color perception and the nuance concept of Natural Color System(NCS). The results are summarized below: First, NCS is a scientific coloring system in consideration of the relevance between people, light and environment, to be based on a phenomenological point of view. NCS can be called a psychometric model reflecting our natural color sense. Second, the color triangle established by NCS is one of the methods of expression based on the human visual mechanism, which is classified by two attributes of hue and nuance, not by the three color attributes of hue, lightness and saturation. The nuance concept of NCS implies the impression, atmosphere and tone that are perceived in colors, which are related to lightness and saturation. Accordingly, this paper suggests that the coloring arrangement emphasizing nuance and tone is more useful than hue in color planning. Third, aesthetic impression in environmental color perception is inclusive of instantly perceptive nuance, which is connected with affordance. The affordance is revealed by the different relation of similarity. In this regard, a strong relationship is noticed between color combination and the sense of pleasantness. The hypothesis regarding the complementation and similarity of contrasting nature is judged to provide observers with aesthetic order. Finally, this paper also suggests four harmonizing methods in the NCS color triangle based upon equal blackness, equal whiteness, equal chromaticness and same nuance. At the same time, opposition and a different concept of hue, lightness and lightness are combined complementarily with the nuance value to suggest patterns of color combination.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.4
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• pp.232-237
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• 2013

This paper presents image database retrieval based on maximum color occurrenceusing Hue, Saturation and Value (HSV) color space. Our system is based on color segmentation. We dividedthe image into n number of areas based on different selected ranges of hue and value, then each area is partitioned into m number of segments based on the number of pixels it contains, after this we calculated the maximumcolor occurrence in each segment and used its HSV value. This is used as a feature vector.

• The Journal of the Korea Contents Association
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• v.10 no.7
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• pp.107-114
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• 2010

Color is a sense signal for human to perceive being through light, and the color is divided into chromatic color and achromatic color. Chromatic color has hue, intensity, and saturation, but achromatic color has only intensity among the properties of chromatic color and doesn't have hue and saturation. Therefore it is important to split colors of image into area for human to perceive colors and not to perceive ones based on vision of human being. In this paper, we find a function to split colors of image into chromatic region of chromatic color region and achromatic region of achromatic color region. First, the input image of RGB color space is converted into the image of HSI color space in consideration of human vision and get a binary image from the converted image. After then, a function to split colors into ROC(ROC: Region of chromatic.) and ROA(ROA:Region of achromatic) is yield. It is difficult to split color of a general image into ROC and ROA. Therefore, to get the chromatic area and achromatic area, we make gradient images to have all range of intensity and range of saturation and to have a little range of hue and yield the function. The evaluation is tested using subjective-quality by 50 non-experts for result images of test images and general images. The results of the proposed method get better 27.5~32.96% than these of the conventional method

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1729-1740
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• 2017

This paper describes a vision-based method that effectively recognize a traffic light. The method consists of two steps of traffic light detection and discrimination. Many related studies have used color information to detect traffic light, but color information is not robust to the varying illumination environment. This paper proposes a new method of traffic light detection based on intensity and saturation. When a traffic light is turned on, the light region usually shows values with high saturation and high intensity. However, when the light region is oversaturated, the region shows values of low saturation and high intensity. So this study proposes a method to be able to detect a traffic light under these conditions. After detecting a traffic light, it estimates the size of the body region including the traffic light and extracts the body region. The body region is compared with five models which represent specific traffic signals, then the region is discriminated as one of the five models or rejected as none of them. Experimental results show the performance of traffic light detection reporting the precision of 97.2%, the recall of 95.8%, and correct recognition rate of 94.3%. These results shows that the proposed method is effective.

• Journal of the Korean Institute of Navigation
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• v.21 no.1
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• pp.119-128
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• 1997

Nowadays, many satellites regularly produce digital multispectral images of the earth's surface. Multispectral images may be displayed as color pictures by selecting three components for assignment to the primary colors. It is desired to enhance these images to generate a display picture that are representativde of their features. in this paper, a false color image processing algorithm is proposed for the purpose of enchancement of the multispectral images based on the human perception. The mean of each primary component is transformed to equalo. Intensity and saturation are enhanced by modified piecewise linear contrast strectching and saturation enhancement method. The proposed method has been successfully applied the LANDSAT TM image and shows good enhancement.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.215-218
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• 2013

In this paper, we proposed a method for enhancement of color images with sky regions. The input image is converted into HSV space and then sky and non-sky regions are separated. For sky region, saturation enhancement is performed for each pixel based on the enhancement factor calculated from the average saturation of its local neighborhood. On the other hand, for the non-sky region, the enhancement is applied only on the luminance value (V) component of the HSV color image, which is performed in two steps. The luminance enhancement, which is also called as dynamic range compression, is carried out using nonlinear transfer function. Again, each pixel is further enhanced for the adjustment of the image contrast depending upon the center pixel and its neighborhood pixel values. At last, the original H and V component image and enhanced S component image for the sky region, and original H and S component image and enhanced V component image for the non-sky region are converted back to RGB image.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.350-356
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• 2017

With increasing attention to real-time body detection, active research is being conducted on human body detection based on skin color. Despite this, most existing skin detection methods utilize static skin color models and have detection rates in images, in which colors are distorted. This study proposed a method of detecting the skin region using a fuzzy classification of the gradient map, saturation, and Cb and Cr in the YCbCr space. The proposed method, first, creates a gradient map, followed by a saturation map, CbCR map, fuzzy classification, and skin region binarization in that order. The focus of this method is to rigorously detect human skin regardless of the lighting, race, age, and individual differences, using features other than color. On the other hand,the borders between these features and non-skin regions are unclear. To solve this problem, the membership functions were defined by analyzing the relationship between the gradient, saturation, and color features and generate 108 fuzzy rules. The detection accuracy of the proposed method was 86.35%, which is 2~5% better than the conventional method.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.579-582
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• 1999

In this paper, we propose a human face detection algorithm using adaptive skin color model and neural networks. To attain robustness in the changes of illumination and variability of human skin color, we perform a color segmentation of input image by thresholding adaptively in modified hue-saturation color space (TSV). In order to distinguish faces from other segmented objects, we calculate invariant moments for each face candidate and use the multilayer perceptron neural network of backpropagation algorithm. The simulation results show superior performance for a variety of poses and relatively complex backgrounds, when compared to other existing algorithm.