• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.93-103
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• 2023

The problem of reconstructing three-dimensional models of people and objects from color and depth images captured by low-cost RGB-D cameras has long been an active research area in computer graphics. Color and depth images captured by low-cost RGB-D cameras are represented as point clouds in three-dimensional space, which correspond to discrete values in a continuous three-dimensional space and require additional surface reconstruction compared to rendering using polygonal models. In this paper, we propose an effective ray-tracing based technique for visualizing point clouds rather than polygonal models. In particular, our method shows the possibility of an effective rendering method even in mobile environment which has limited performance due to processor heat and lack of battery.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.217-224
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• 2024

With the rapid growth of K-POP, the dance content industry is spreading. With the recent increase in the spread of SNS, they also shoot and share their dance videos. However, it is not easy for dance beginners who are new to dancing to learn dance moves because it is difficult to receive objective feedback when dancing alone while watching videos. This paper describes a system that uses MediaPipe to compare choreography videos and dance videos of users and detect whether they are following the movement correctly. This study proposes a method of giving feedback based on Color Map to users by calculating the similarity of dance movements between user images taken with webcam or camera and choreography images using cosine similarity and COCO OKS. Through this system, objective feedback on users' dance movements can be visually received, and beginners are expected to be able to learn accurate dance movements.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.47-55
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• 2024

We spend a lot of time in indoor space, and the space has a huge impact on our lives. Interior design plays a significant role to make an indoor space attractive and functional. However, it should consider a lot of complex elements such as color, pattern, and material etc. With the increasing demand for interior design, there is a growing need for technologies that analyze these design elements accurately and efficiently. To address this need, this study suggests a deep learning-based design analysis system. The proposed system consists of a semantic segmentation model that classifies spatial components and an image classification model that classifies attributes such as color, pattern, and material from the segmented components. Semantic segmentation model was trained using a dataset of 30000 personal indoor interior images collected for research, and during inference, the model separate the input image pixel into 34 categories. And experiments were conducted with various backbones in order to obtain the optimal performance of the deep learning model for the collected interior dataset. Finally, the model achieved good performance of 89.05% and 0.5768 in terms of accuracy and mean intersection over union (mIoU). In classification part convolutional neural network (CNN) model which has recorded high performance in other image recognition tasks was used. To improve the performance of the classification model we suggests an approach that how to handle data that has data imbalance and vulnerable to light intensity. Using our methods, we achieve satisfactory results in classifying interior design component attributes. In this paper, we propose indoor space design analysis system that automatically analyzes and classifies the attributes of indoor images using a deep learning-based model. This analysis system, used as a core module in the A.I interior recommendation service, can help users pursuing self-interior design to complete their designs more easily and efficiently.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2776-2785
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• 1998

An image retrieval system based on image content is a key issue for building and managing large multimedia database, such as art galleries and museums, trademarks and copyrights, and picture archiving and communication system. Therefore, the interest on the subject of content-based image retrieval has been greatly increased for the last few years. This paper proposes a feature-based image retrieval technique which uses a compound feature vector representing both of color and shape of an image. Color information for the feature vector is obtained using the algebraic moment of each pixel of an image based on the property of regional color distribution. Shape information for the feature vector is obtained using the Improved Moment Invariant(IMI) which reduces the quantity of computation and increases retrieval efficiency. In the preprocessing phase for extracting shape feature, we transform a color image into a gray image. Since we make use of the modified DCT algorithm, it is implemented easily and can extract contour in real time. As an experiment, we have compared our method with previous methods using a database consisting of 150 automobile images, and the results of the experiment have shown that our method has the better performance on retrieval effectiveness.

• Journal of the Korea Fashion and Costume Design Association
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• v.17 no.1
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• pp.141-154
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• 2015

The purpose of this study is to look for a development plan for strategic brand logo by a means of scrutinizing general characteristics and trend in the visual properties of outdoor logo brands. In this study, data research and analysis were conducted over the 68 outdoor brands in circulation in the domestic market based on the information on the website of each brand in order to examine the visual characteristics of an outdoor brand logo. For this, it was performed to examine the desired brand concept of each brand and to analyze the visual characteristics of typeface, color, and type of logo. The results of this research are the followings: First, it was found that the most popular typeface in outdoor brand logos is a capitalized Gothic type. It seems that the logo type is designed to symbolize power, toughness, and masculinity and to express the concept of sportswear brand. Second, when it comes to color, black color tone appeared most frequently, and also reddish colors among chromatic colors were prevailing over others like green, blue, or yellow. It is believed that reddish colors were used to express passion, power, youthfulness, and energy; black color tone for tough, masculine power. Third, the logo symbol of outdoor brands mostly contains mountain, the heads of powerful animals, spherical shape/abstract image that embodies outdoor sports activities. It was analyzed that these resulting symbols were chosen to convey the images of nature, conquest, challenge, future, and passion that are the brand concept of most outdoor brands. Today, in our country, the logo of an outdoor brand is the important factor that symbolizes the brand concept, function, or characteristics. Therefore, the necessity of constant follow-up researches is required to devise the way of designing the brand logo that can build brand power and enhance brand image.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.41.1-41.1
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• 2013

To test whether the close relationships between host and satellite galaxies in isolated groups are also found in the harsh environment of a galaxy cluster, we carry out a case study of WHL 085910.0+294957, a galaxy cluster at z=0.30, using deep images obtained with the 2.1-m Otto Struve telescope and CQUEAN CCD camera. When environmental parameters are controlled, the local weighted mean color of faint galaxies shows a measurable correlation with the color of their bright ($M_i$ < -18) neighbor. The most striking result is that the red (r - i > 0.2) and bright galaxies within 200 kpc distance from the center of the cluster are correlated in color with very faint ($M_i$ > -14) galaxies around them by $(r-i)_{satellites}=(7.276{\pm}1.402){\times}(r-i)_{host}-2.434$ (correlation coefficient = 0.665). We suggest three scenarios to interpret the results: vestiges of infallen groups, dwarf capturing, and tidal tearing of bright galaxies.

• Journal of the Korean Society of Clothing and Textiles
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• v.36 no.8
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• pp.875-884
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• 2012

Many Koreans have recently bleached their black hair to blond or a light color due to the influence of their favorite Korean idols. Bleaching effects were studied under various bleaching conditions, such as the concentration of oxidants, the ratio between bleach accelerant and oxidant, and treatment temperature and time. The degree of damage of bleached hair with the same color difference (${\Delta}E$) intervals was observed in SEM images, the retention of breaking load and the change of color after dyeing. The ratio between bleach accelerant and oxidant of 1:2.5 was an effective condition. $L^*$ values of the bleached hair treated with 9% oxidant increased to 90 min. At a treatment temperature of $30^{\circ}C$, $a^*$ values were maximum at 30 min and then decreased as time further increased; however, $b^*$ values of the bleached hair increased as the treatment time increased. At $45^{\circ}C$, both of $a^*$ and $b^*$ values showed a maximum at a specific time. Bleaching efficiency was influenced most by temperature, followed in order by time, and oxidant concentration. As the treatment time increased, $L^*$ values greatly increased with twice treatment; however, $a^*$ and $b^*$ values decreased. Bleached hair, which had a color difference of higher than 30, showed the scales were completely removed and the retention of the breaking load greatly decreased. Highly bleached hair showed a great decrease in $L^*$ values by dyeing; however, dyeing with bright colors was more indicative to the effect of bleaching.

• The Journal of Internal Korean Medicine
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• v.39 no.4
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• pp.637-644
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• 2018

Objectives: In this study, the tongue features of patients with functional dyspepsia (FD) were compared with those of healthy controls. Methods: This prospective, case-control study was conducted on patients with FD and controls recruited at a single center. After screening, the subjects were allocated to the patient or control groups (patients=42, controls=40). Tongue images were acquired using a computerized tongue image acquisition system (CTIS). An independent t-test was conducted to compare the measurements from patients and controls. Binary logistic regression was performed to determine significant differences between the two groups after adjusting for age and sex. Results: The CIE $a^*$ color value in the tongue coating area was significantly lower in the patients with FD than in the controls (p=0.001). The tongue coating ratios were also significantly higher in the FD group than in the control group (p=0.003). We found that the CIE $a^*$ color value in the tongue coating area and the tongue coating ratios were significant predictive factors in both groups, based on binary regression analysis (p=0.016, 0.044, respectively). Conclusions: This study found that FD was significantly associated with CIE $a^*$ color value in the tongue coating area and tongue coating ratios. We suggest that these factors could be used as objective indicators of FD.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.961-973
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• 2005

In this paper, we proposed an adaptive steganography of color image using bit-planes and multichannel characteristics. Applying fixing threshold, if we insert information into all bit-planes of RGB channel, each channels showed different image quality. Therefore, we first defined the channel weight and the bit-plane weight to solve the fixing threshold problem of BPCS (bit-plane complexity steganography) method. We then proposed a new adaptive threshold method using the bit-plane weight of channels and the bit-plane complexity of cover image to increase insertion capacity adaptively In the experiment, we inserted information into the color images with the same image quality and same insertion capacity, and we analyzed the Insertion capacity and image quality. As a result, the proposed method increased the insertion capacity and improved the image quality than BPCS method.

• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.733-744
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• 1996

Content-based image retrieval(CBIR) is an image data retrieval methodology using characteristic values of image data those are generated by system automatically without any caption or text information. In this paper, we propose a content-based image data retrieval method using shape and color features of image data as characteristic values. For this, we present some image processing techniques used for feature extraction and indexing techniques based on trie and R tree for fast image data retrieval. In our approach, image query result is more reliable because both shape and color features are considered. Also, we how an image database which implemented according to our approaches and sample retrieval results which are selected by our system from 200 sample images, and an analysis about the result by considering the effect of characteristic values of shape and color.