• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.450-460
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• 2005

Today, multimedia information is used on the internet and various social areas by rapid development of computer and communication technology. Therefor, the usage is growing dramatically. Multimedia information analysis system is basically based on text. So, there are many difficult problems like expressing ambiguity of multimedia information, excessive burden of works in appending notes and a lack of objectivity. In this study, we suggest a method which uses color and shape information of multimedia image partitions efficiently analyze a large amount of multimedia information. Partitions use field growth and union method. To extract color information, we use distinctive information which matches with a representative color from converting process from RGB(Red Green Blue) to HSI(Hue Saturation Intensity). Also, we use IMI(Improved Moment Invariants) which target to only outline pixels of an object and execute computing as shape information.

• Journal of Digital Contents Society
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• v.10 no.3
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• pp.423-431
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• 2009

There are various image retrieval methods using shape, color and texture features. One of the most active area is using shape and color information. A number of shape representations have been suggested to recognize shapes even under affine transformation. There are many kinds of method for shape recognition, the well-known method is Fourier descriptors and moment invariant. The other method is CSS(Curvature Scale Space). The maxima of curvature scale space image have already been used to represent 2-D shapes in different applications. Because preexistence CSS exists several problems, in this paper we use improved CSS method for retrieval image. There are two kinds of method, One is using RGB color information feature and the other is using HSI color information feature. In this paper we used HSI color model to represent color histogram before, then use it as comparison measure. The similarity is measured by using Euclidean distance and for reduce search time and accuracy, We use DTW for measure similarity. Compare with the result of using Euclidean distance, we can find efficiency elevated.

• Journal of the Korea Society of Computer and Information
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• v.7 no.3
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• pp.1-8
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• 2002

Due to the fast development in computer application technologies, a video is now being more widely used than ever in many areas. The current information analyzing systems are basically built to process text-based data. Thus, it has little bits Problems when it needs to correctly represent the ambiguity of a video, when it has to process a large amount of comments. or when it lacks the objectivity that the jobs require. We would like to purpose the method that is capable of analyze a large amount of video efficiently. To extract the color, we translate the color from RGB to HSI and use the information that matches with the representative colors. To extract the shape information, we use improved moment invariants(IMI) so that we can solve many problems of histogram intersection.

• Journal of Korea Multimedia Society
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• v.15 no.11
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• pp.1273-1283
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• 2012

In this paper, vision-based positioning algorithm for melon harvesting robot is presented. RGB value of the input image was converted into HSI value then, melon area was extracted after performing the binarization using HUE value. After morphological filtering was applied to remove noise, outermost boundary points were obtained using border following and convex hull method. Elliptical fitting for melons was perform by the RANSAC algorithm, the center point of ellipse, the length of the short and long axis, and rotation angle were obtained. We verified the effectiveness of the proposed method by various simulation experiments and confirmed actual feasibility of the proposed method by applying to the real melon.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.251-256
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• 2010

This paper aims for developing the intelligent robot emulating human synesthetic skills which associate a color image with sound, so that we are able to build an application system based on the principle of mutual conversion between color image and sound. As the first step, in this study, we have tried to realize a basic system using the color image to sound conversion. This study describes a new conversion method to convert color image into sound, based on the likelihood in the physical frequency information between light and sound. In addition, we present the method of converting color image into sound using color model conversion as well as histograms in the converted color model. In the basis of the method proposed in this study, we built a basic system using Microsoft Visual C++(ver. 6.0). The simulation results revealed that the hue, saturation and intensity elements of a input color image were converted into F0, harmonic and octave elements of a sound, respectively. The converted sound elements were synthesized to generate a sound source with WAV file format using Csound toolkit.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.428-434
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• 2015

A new tongue examination model by using color analysis according to the taste division of tongue. The proposed system consists of a tongue image acquisition in a predefined template, taste region segmentation, color distribution analysis and abnormality decision of tongue by color analysis using Hue-Saturation histograms and the part of a mobile application service. We divided 4 basic taste(bitter, sweet, salty and sour) regions and performed color distribution analysis targeting each region under HSI(Hue Saturation Intensity) color model. To minimize the influence of illumination, the histograms of H and S components only except U are utilized. Using the analyzed results, the abnormality is discriminated by the criteria of the histogram range of normal tongues. Finally, a self tongue diagnosis system which can be used anytime and anywhere on mobile environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2927-2936
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• 2013

In this paper, we propose a noise reduction and hole removal algorithm in order to improve the quality of depth images when they are used for creating 3D contents. In the proposed algorithm, the depth image and the corresponding color image are both used. First, an intensity image is generated by converting the RGB color space into the HSI color space. By estimating the difference of distance and depth between reference and neighbor pixels from the depth image and difference of intensity values from the color image, they are used to remove noise in the proposed algorithm. Then, the proposed hole filling method fills the detected holes with the difference of euclidean distance and intensity values between reference and neighbor pixels from the color image. Finally, we apply a parallel structure of GPGPU to the proposed algorithm to speed-up its processing time for real-time applications. The experimental results show that the proposed algorithm performs better than other conventional algorithms. Especially, the proposed algorithm is more effective in reducing edge blurring effect and removing noise and holes.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.3-10
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• 2014

Digital maps are made by experts who digitize the data from aerial image and field survey. And the digital maps are updated every 2 years in National Geographic Information Institute. Conventional Digitizing methods take a lot of time and cost. And geographic information needs to be modified and updated appropriately as geographical features are changing rapidly. Therefore in this paper, we modify the digital map updates the road information for rapid high-resolution aerial orthophoto taken at different times were performed HSI color conversion. Road area of the cassification was performed the region growing methods. In addition, changes in the target area for analysis by applying the CVA technique to compare the changed road area by analyzing the accuracy of the proposed extraction.

• 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

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.267-274
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• 2004

In this paper, the interesting moving objects tracking algorithm using color information on Multi-Video camera is proposed Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area, after converting RGB color coordination of image which is input from multi-video camera into HSI color coordination. Hue information of the detected moving area are normalized by 24 steps from 0$^{\circ}$ to 360$^{\circ}$ It is used for the feature parameters of the moving objects that three normalization levels with the highest distribution and distance among three normalization levels after obtaining a hue distribution chart of the normalized moving objects. Moving objects identity among four cameras is distinguished with distribution of three normalization levels and distance among three normalization levels, and then the moving objects are tracked and surveilled. To examine propriety of the proposed method, four cameras are set up indoor difference places, humans are targeted for moving objects. As surveillance results of the interesting human, hue distribution chart variation of the detected Interesting human at each camera in under 10%, and it is confirmed that the interesting human is tracked and surveilled by using feature parameters at four cameras, automatically.