• Proceedings of the Korean Institute of Interior Design Conference
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• 2005.05a
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• pp.243-246
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• 2005

As seen in constant reference to our modern are as the 'Information Age', our daily lives are flooded with a variety of information. Under such circumstance, efficient management and distribution of information are increasingly needed. When it comes to office environment, the role of furniture is very important because furniture must be placed in the office and it also serves as an essential component to improve work efficiency. As the importance of furniture increases, office furniture reflects diverse needs. That is to say, office furniture is used to partition space while reflecting mental and emotional state of workers in the office. At this backdrop, it can be perceived that office goes beyond a place where work is done. In order to contemplate how office and office furniture enhance work efficiency and create pleasant, delightful office environment, the study in this paper identified and examined overall color images of office, and color use and color preference in office furniture. The purposes of this study were: 1) to identify the use of and preference for color images of office 2) to analyze the color images of office furniture and understand its color use and color preference; 3) to understand the color use and color preference in office storage furniture.

• Journal of Surface Science and Engineering
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• v.35 no.5
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• pp.325-329
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• 2002

We investigated the oxide thickness and color evolution with the oxidation temperatures between $370^{\circ}C$ and $950^{\circ}C$ for 30 minutes in an electric furnace. Oxide thickness and color index were determined by cross sectional field emission scanning electron microscopy (FESEM) images and digital camera images, respectively. We confirmed that thermal oxidation was suitable for the mass production of color-titanium products, while coloring process window was narrow compared with anodizing oxidation process.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.940-942
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• 2003

In an attempt to enhance the visual effect of SPOT image, this study develops a neural network algorithm to transform SPOT false color into simulated true color. The method has been tested using Landsat TM and SPOT images. The qualitative and quantitative comparisons indicate that the striking similarity can be found between the true and simulated true images in terms of the visual looks and the statistical analysis.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.196-199
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• 2002

We presented the automatic extraction technique of a biological internal organization from full-color continuous images. It was implemented using the localized homogeneousness of color intensity, and also using the continuity between neighboring images. Moreover, we set the "four-level status value" of area condition as a value showing "area possibility. This played important role of preventing a miss-judgement of area definition. These our approach had a beneficial effect on tracking color and shape change of the interest area in continuous extraction. As a resell we succeeded in extraction of mouse's stomach from continuous 50 images.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.535-546
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• 2010

Digital images have undesired color casts due to various illumination conditions and intrinsic characteristics of cameras. Since the color casts in the images deteriorate performance of color representations, color correction is required for further analysis of images. In this paper, an algorithm for detection and removal of color casts is presented. The proposed algorithm consists of four steps: retrieving similar image using color by correlation, extraction of near neutral color regions, kernel density estimation, and removal of color casts. Ambiguities in near neutral color regions are excluded based on kernel density estimation by the color by correlation algorithm. The method determines whether there are color casts by chromaticity distributions in near neutral color regions, and removes color casts for color constancy. Experimental results suggest that the proposed method outperforms the gray world algorithm and the color by correlation algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.2 s.308
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• pp.63-71
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• 2006

Denoising and reconstruction of color images are extensively studied in the field of computer vision and image processing. Especially, denoising and reconstruction of color face images are more difficult than those of natural images because of the structural characteristics of human faces as well as the subtleties of color interactions. In this paper, we propose a denoising method based on PCA reconstruction for removing complex color noise on human faces, which is not easy to remove by using vectorial color filters. The proposed method is composed of the following five steps: training of canonical eigenface space using PCA, automatic extraction of facial features using active appearance model, relishing of reconstructed color image using bilateral filter, extraction of noise regions using the variance of training data, and reconstruction using partial information of input images (except the noise regions) and blending of the reconstructed image with the original image. Experimental results show that the proposed denoising method maintains the structural characteristics of input faces, while efficiently removing complex color noise.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1641-1648
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• 2017

The main purpose of this paper is to compare the performances of various filters with color images to remove the noise. Furthermore, we suggest a modified de-noising process by the transformation of color model from RGB to another color models, such as HSV and $YC_BC_R$, to improve the quality of de-noising methods encompassing Median, Wiener, and Mean filters. Neither the performance comparison of the de-noising filters with color images nor the converting the color model for better de-noise on the degraded images haven't been performed before. Inspired to make improvements, we conduct experiments with new de-noising process on color images. The result of the experiments is shown that it could assist on certain filters being more reliable techniques.

• Archives of design research
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• v.15 no.4
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• pp.327-336
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• 2002

This paper is intended to help cool-skin-colored people to choose suitable clothing colors confidently and look well-dressed and to make positive self-images. A pseudo-experimental method has made it possible to analyze the visual evaluations of clothing color images for cool-skin-colored people and obtain the following results. 1. Reddish colors of vivid tone for doffing give positive images and those of dull and dark tone, negative ones. 2. Yellowish colors of vivid and bright tone for doffing show positive images and those of dull and dark tone, negative ones. Cool yellow of light tone proves to contribute to a well-looking image. 3. Warm green of vivid and deep tone, and cool green of vivid tone for clothing present positive images. 4. Warm blue of vivid and deep tone, and cool blue of vivid and bright lone make positive images. Either blue with dull tone gives a negative image. 5. Purple colors whose tone is vivid, deep and light contribute to positive images, and those of dull tone, negative ones.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.464-475
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• 2017

In this paper, we present a new texture image retrieval method which combines color and texture features extracted from images by a set of multi-resolution multi-direction (MRMD) filters. The MRMD filter set chosen is simple and can be separable to low and high frequency information, and provides efficient multi-resolution and multi-direction analysis. The color space used is HSV color space separable to hue, saturation, and value components, which are easily analyzed as showing characteristics similar to the human visual system. This experiment is conducted by comparing precision vs. recall of retrieval and feature vector dimensions. Images for experiments include Corel DB and VisTex DB; Corel_MR DB and VisTex_MR DB, which are transformed from the aforementioned two DBs to have multi-resolution images; and Corel_MD DB and VisTex_MD DB, transformed from the two DBs to have multi-direction images. According to the experimental results, the proposed method improves upon the existing methods in aspects of precision and recall of retrieval, and also reduces feature vector dimensions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5058-5072
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• 2015

Quaternions have been commonly employed in color image processing, but when the existing pure quaternion representation for color images is used in perceptual hashing, it would degrade the robustness performance since it is sensitive to image manipulations. To improve the robustness in color image perceptual hashing, in this paper a full quaternion representation for color images is proposed by introducing the local image luminance variances. Based on this new representation, a novel Full Quaternion Discrete Cosine Transform (FQDCT)-based hashing is proposed, in which the Quaternion Discrete Cosine Transform (QDCT) is applied to the pseudo-randomly selected regions of the novel full quaternion image to construct two feature matrices. A new hash value in binary is generated from these two matrices. Our experimental results have validated the robustness improvement brought by the proposed full quaternion representation and demonstrated that better performance can be achieved in the proposed FQDCT-based hashing than that in other notable quaternion-based hashing schemes in terms of robustness and discriminability.