• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.67-72
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• 2005

Most of image binarization algorithms analyzes the intensity distribution using the histogram for the determination of threshold value. When the intensity difference between the foreground object and the background is great, the histogram shows the tendency to be bimodal and the selection of the histogram valley as the threshold value shows the good result. On the other side. when the intensity difference is not great and the histogram doesn't show the bimodal property, the histogram analysis doesn't support the selection of the proper threshold value. This Paper Proposed the novel binarization method that applies the fuzzy membership function to each color value on the RGB color model and, by using the operation results, separates the features having the great readability from the background. The proposed method prevents the loss of information incurred by the gray scale conversion by using the RGB color model and extracts effectively the readable features by using the fuzzy inference Compared with the traditional binarization methods, the proposed method is able to remove the majority of noise areas and show the improved results on the image of transport containers , etc.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.63-71
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• 2003

This paper describes a color image segmentation algorithm based on region merging using hue difference as a restrictive condition. The proposed algorithm using mathematical morphology and a modified watershed algorithm does over-segmentation in the RGB space to preserve contour information of regions. Then, the segmentation result of color image is acquired by repeated region merging using hue differences as a restrictive condition. This stems from human visual system based on hue, saturation, and intensity. Hue difference between two regions is used as a restrictive condition for region merging because it becomes more important factor than color difference if intensity is not low. Simulation results show that the proposed color image segmentation algorithm provides efficient segmentation results with the predefined number of regions for various color images.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.401-404
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• 2006

Mean shift procedure is applied for the data points in the joint spatial-range domain and achieves a high quality. However, a color image is segmented differently according to the inputted spatial parameter or range parameter and the demerit is that the image is broken into many small regions in case of the small parameter. In this paper, to improve this demerit, we propose the method that groups similar regions using region merging method for over-segmented images. The proposed method converts a over-segmented image in RGB color space into in HSI color space and merges similar regions by hue information. Here, to preserve edge information, the proposed method use by merging constraints to decide whether regions is merged or not. After then, we merge the regions in RGB color space for non-processed regions in HSI color space. Experimental results show the superiority in region's segmentation results.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.1
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• pp.36-46
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• 2013

The Geostationary Ocean Color Imager (GOCI), the first geostationary ocean color observation instrument launched in 2010 on board the Communication, Ocean, and Meteorological Satellite (COMS), has been generating the operational level 1 data. This study describes a methodology for creating the GOCI true color image and data processing software, namely the GOCI RGB maker. The algorithm uses a generic atmospheric correction and reprojection technique to produce the color composite image. Especially, the program is designed for educational purpose in a way that the region of interest and image size can be determined by the user. By distributing software to public, it would maximize the understanding and utilizing the GOCI data. Moreover, images produced from the geostationary observations are expected to be an excellent tool for monitoring environmental changes.

• The Journal of the Korea Contents Association
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• v.6 no.9
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• pp.19-27
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• 2006

Mean shift procedure is applied for the data points in the joint spatial-range domain and achieves a high quality. However, a color image is segmented differently according to the inputted spatial parameter or range parameter and the demerit is that the image is broken into many small regions in case of the small parameter. In this paper, to improve this demerit, we propose the method that groups similar regions using region merging method for over-segmented images. The proposed method converts a over-segmented image in RGB color space into in HSI color space and merges similar regions by hue information. Here, to preserve edge information, the region merge constraints are used to decide whether regions are merged or not. After then, we merge the regions in RGB color space for non-processed regions in HSI color space. Experimental results show the superiority in region's segmentation results.

• Journal of Korea Multimedia Society
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• v.2 no.3
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• pp.289-296
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• 1999

In this paper, an improved fractal color image decoding method using the data dependence parts and the vector distortion measure is proposed. The vector distortion measure exploits the correlation between different color components. The pixel in RGB color space can be considered as a 30dimensional vector with elements of RGB components. The root mean square error(rms) in RGB color for similarity measure of two blocks R and R' was used. We assume that various parameter necessary in image decoding are stored in the transform table. If the parameter is referenced in decoding image, then decoding is performed by the recursive decoding method. If the parameter is not referenced in decoding image, then the parameters recognize as the data dependence parts and store its in the memory. Non-referenced parts can be decoded only one time, because its domain informations exist in the decoded parts by the recursive decoding method. Non-referenced parts are defined the data dependence parts. Image decoding method using data dependence classifies referenced parts and non-referenced parts using information of transform table. And the proposed method can be decoded only one time for R region decoding speed than Zhang & Po's method, since it is decreased the computational numbers by execution iterated contractive transformations for the referenced range only.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.1946-1953
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• 2006

Because the embedded watermark of luminance component guarantees the extraction of ownership information when the color image is converted to gray scale image, the information of ownership right as to the luminance component is embedded in the luminance-chrominance color space such as YCbCr. Therefore, this paper proposes watermark embedding, extraction and authentication algorithm of color image. which considers the device and performance of multimedia contents service by focusing on the robustness and invisibility of watermark. The color image is converted from RGB color space to YCbCr color space, and then the properties of each component of Y(Luminance), Cb(Color Differences) and Cr(Color Differences) are considered in order to embed, extract and certify multi-level watermark in the frequency domain based on the wavelet. As a result, it can guaranteed the robustness for the JPEG compression and invisibility of watermark for multi-level.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.325-332
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• 2003

This study was to develop a system for grading apples by their color using statistical image processing. T-test was used to detect edges in apple images and the chain code method was used for contour coding. The histogram and mean gray level of each RGB channel in a ring-shaped region was used to compare apple colors to reference apple color.

• Journal of Korea Multimedia Society
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• v.15 no.4
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• pp.501-507
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• 2012

Human body motion is a non-verbal part for interaction or movement that can be used to involves real world and virtual world. In this paper, we explain a study on natural user interface (NUI) in human hand motion recognition using RGB color information and depth information by Kinect camera from Microsoft Corporation. To achieve the goal, hand tracking and gesture recognition have no major dependencies of the work environment, lighting or users' skin color, libraries of particular use for natural interaction and Kinect device, which serves to provide RGB images of the environment and the depth map of the scene were used. An improved Camshift tracking algorithm is used to tracking hand motion, the experimental results show out it has better performance than Camshift algorithm, and it has higher stability and accuracy as well.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.273-274
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• 2006

칼라기반 영상 검색에서 칼라의 색상 정보를 이용하는 기법에 많은 연구가 진행되고 있다. 본 논문에서는 칼라의 색상 정보와 명암 정보인 Gray-level의 특징자를 이용해서 영상을 검색하는 시스템을 제안한다. 칼라영상의 RGB 각각의 픽셀 값들을 R값, G값, B값의 크기순으로 배열하고 칼라 그레이-레벨을 구한 뒤 양자화 한다. 이러한 칼라의 특징 정보를 사용함으로써 이미지의 확대, 축소, 회전에도 강인한 검색을 할 수 있음을 실험을 통하여 성능의 우수함을 보였다.