• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.495-506
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• 2017

This study was carried out to effectively perform relative color correction for high-resolution aerial ortho image. For this study, relative geometrical error between adjacent images was analyzed. The block sum method is proposed to reduce the relative geometrical error. We used the regression coefficients determined based on the block sum size to perform the color correction. As a result, it was confirmed that the relative color correction was visually performed well. Quantitative analysis was performed through histogram similarity analysis. It is proved that block sum method is useful for relative color correction. Particularly, the block sum size was very important to correct color based on the amount of relative geometrical error.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.105-113
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• 2007

In this paper, an image segmentation method which is based on edge salience map and region merging is presented. The edge salience map is calculated by combining a texture edge map with a color edge map. The texture edge map is computed over multiple spatial orientations and frequencies by using Gabor filter. A color edge is computed over the H component of the HSI color model. Then the Watershed transformation technique is applied to the edge salience map to and homogeneous regions where the dissimilarity of color and texture distribution is relatively low. The Watershed transformation tends to over-segment images. To merge the over-segmented regions, first of all, morphological operation is applied to the edge salience map to enhance a contrast of it and also to find mark regions. Then the region characteristics, a Gabor texture vector and a mean color, in the segmented regions is defined and regions that have the similar characteristics, are merged. Experimental results have demonstrated the superiority in segmentation results for various images.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.29-36
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• 2012

In this paper, we suggest a new method of detecting human skin-color regions from three-dimensional static or dynamic stereoscopic images by effectively integrating depth and color features. The suggested method first extracts depth information that represents the distance between a camera and an object from input left and right stereoscopic images through a stereo matching technique. It then performs labeling for pixels with similar depth features and determines the labeled regions having human skin color as actual skin color regions. Our experimental results show that the suggested skin region extraction method outperforms existing skin detection methods in terms of skin-color region extraction accuracy.

• Journal of Korea Multimedia Society
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• v.7 no.5
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• pp.648-657
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• 2004

A method of extracting central objects in color images without any prior-knowledge is proposed in this paper, which uses basically information of significant color distribution. A central object in an image is defined as a set of regions that lie around center of the image and have significant color distribution against the other surround (or background) regions. Significant colors in an image are first defined as the colors that are distributed more densely around center of the image than near borders. Then core object regions (CORs) are selected as the regions a lot of pixels of which have the significant colors. Finally, the adjacent regions to the CORs are iteratively merged if they are similar to the CORs but not to the background regions in color distribution. The merging result is accepted as the central object that may include differently color-characterized regions and/or two or more objects of interest. Usefulness of the significant colors in extracting the central object was verified through experiments on several kinds of test images. We expect that central objects shall be used usefully in image retrieval applications.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.91-97
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• 2009

This paper proposes novel FE-CBIRS that finds best position of a cut to be retrieved based on color feature distribution in digital contents of IPTV. Conventional CBIRS have used a method that utilizes both color and shape information together to classify images, as well as a method that utilizes both feature information of the entire region and feature information of a partial region that is extracted by segmentation for searching. Also, in the algorithm, average, standard deviation and skewness values are used in case of color features for each hue, saturation and intensity values respectively. Furthermore, in case of using partial regions, only a few major colors are used and in case of shape features, the invariant moment is mainly used on the extracted partial regions. Due to these reasons, some problems have been issued in CBIRS in processing time and accuracy so far. Therefore, in order to tackle these problems, this paper proposes the FE-CBIRS that makes searching speed faster by classifying and indexing the extracted color information by each class and by using several cuts that are restricted in range as comparative images.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.135-143
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• 2009

Recently, in the mobile device, the increase of the need for encoding and decoding of high-resolution images requires an efficient implementation of the image codec. This paper proposes a time-optimized color conversion method for the JPEG decoder, which reduces the number of calculations in the color conversion by the rearrangement of arithmetic operations being possible due to the linearity of the IDCT and the color conversion matrices and brings down the time complexity of the color conversion itself by the integer mapping replacing floating-point operations to the optimal fixed-point shift and addition operations, eventually reducing the time complexity of the JPEG decoder. And the proposed method compensates a decline of image quality incurred by the quantification error of the operation arrangement and the integer mapping by using the multi-mode chrominance reconstruction. The performance evaluation performed on the development platform of embedded systems showed that, compared to previous color conversion methods, the proposed method greatly reduces the image decoding time, minimizing the distortion of decoded images.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.83-92
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• 2009

In this paper, an extended snake algorithm using color variance energy is proposed for segmenting an interest object in color image. General snake algorithm makes use of energy in image to segment images into a interesting area and background. There are many kinds of energy that can be used by the snake algorithm. The efficiency of the snake algorithm is depend on what kind of energy is used. A general snake algorithm based on active contour model uses the intensity value as an image energy that can be implemented and analyzed easily. But it is sensitive to noises because the image gradient uses a differential operator to get its image energy. And it is difficult for the general snake algorithm to be applied on the complex image background. Therefore, the proposed snake algorithm efficiently segment an interest object on the color image by adding a color variance of the segmented area to the image energy. This paper executed various experiments to segment an interest object on color images with simple or complex background for verifying the performance of the proposed extended snake algorithm. It shows improved accuracy performance about 12.42 %.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.12
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• pp.81-89
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• 1997

In this paper, we propose a new image retrieval algorithm using the block classification. More specifically, we classify nonoverlappint small image blocks into texture, monotone, and various edges. Using these classification results and the RGB color histogram, we propose a new similarity measure which considers both local and global fretures. According to our experimental results using 232 color images, the retrieval efficiencies of the proposed and the previous methods were 0.610 and 0.522, respectively, which implies that the proposed algorithm yields better performance.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.207-210
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• 2002

In this paper, content-based retrieval for region of interest(ROI) has been described, using maximum bin color. From a given query image, the object of interest is selected by a user. Using maximum bin color of the selected object, candidate regions are extracted from database images. The final regions of interest are determined by comparing the normalized histograms of the selected object and each candidate region.

• 한국정보디스플레이학회:학술대회논문집
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• 2002.08a
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• pp.743-745
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• 2002

We reported the possibility of color filtering of white method for achieving full-color displays using OELDs. Here, we fabricated white organic electroluminescent devices (OELDs) and drove moving images with a 384${/times}$160 pixel.