• The Research Journal of the Costume Culture
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• v.19 no.6
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• pp.1163-1176
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• 2011

The purposes of this study was to identify characteristics of total coordination in the pursuit fashion sensibility among women their 20's. A self-administered questionnaire was used for data collection from 410 women in their 20's. Data collection was conducted Aug. 5 to Aug. 15, 2009. Most women emphasized on clothing for total coordination and utilized clothing color and style as a selection criteria. They tried to match makeup and clothing, and spent more time considering makeup, hair styles, and fashion accessaries than clothing for their total coordination. Factors of fashion sensibility included luxury and fashion, casualness and ethnicity, modernity, sociality, activity, and sexual attractiveness and women were segmented into fashionably sensible intermediate, low, and high groups according to their fashion sensibility. The fashionably sensible intermediate group predominantly encompassed women who were unmarried or in their late 20's, unemployed, highly educated, or of low economic status, preferred to mixing and matching colors, and who utilized their individuality or makeup color for total coordination. The fashionably sensible low group encompassed homemakers, in their early 20's, high school graduates or university students, who utilized their clothing or hair color within their total coordination criteria. The fashionably sensible high group encompassed unmarried career women in their mid 20's or of high economic status, who spent much money on their clothing, makeup, hair styles, and fashion accessaries, who preferred achromatic, warm or cool colors, and utilized their individuality or fashion color.

• The Korean Fashion and Textile Research Journal
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• v.20 no.3
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• pp.323-330
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• 2018

This study aim is to provide new coloration method by laccase-catalyzation on natural phenolic dyeing process. In this study, silk was dyed with black tea, which is one of polyphenolic dye, extracted in distilled water. The dyed samples were catalyzed by laccase as the eco-friendly mordanting process. To optimize the conditions of laccase-catalyzed coloration, conditions were varied by different mordanting methods (one-bath, two-bath), temperature and treatment time. The dye affinity in terms of the value of K/S, $L^*$, $a^*$, $b^*$, and H, V, C was measured by Computer Color Matching System (CCM, CM-2600d, Spectra Magic NX, Korea). The effect of laccase-catalyzed coloration on washing fastness was evaluated and compared with the synthetic mordant (Al, Cu, and Fe). As the result of color analysis of dyed silk, the optimum conditions of laccase-catalyzed coloration were determined to post-mordanting by one-bath at $50^{\circ}C$ for 3 hours. Under the optimum laccase-catalyzed conditions, the dyed silk was shown the color of yellowish-red. After laccase-catalyzed coloration on the dyed silk, the improvement of washing fastness was obtained compared with mordanted silk by synthetic mordant (Al, Cu, and Fe). Therefore, the present study was demonstrated that the effective enzymatic mordanting method by laccase for phenolic natural dyeing with vivid color and good fastness.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.376-379
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• 2008

This paper presents an image retrieval algorithm based on feature vector using color of histogram refinement for a faster and more efficient search in the process of content based image retrieval. First, we segment each of R, G, and B images from RGB color image and extract their respective histograms. Secondly, these histograms of individual R, G and B are divided into sixteen of bins each. Finally, we extract the maximum pixel values in each bins' histogram, which are calculated, compared and analyzed, Now, we can perform image retrieval technique using these maximum pixel value. Hence, the proposed algorithm of this paper effectively extracts features by comparing input and database images, making features from R, G and B into a feature vector table, and prove a batter searching performance than the current algorithm that uses histogram matching and ranks, only.

• Science of Emotion and Sensibility
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• v.11 no.3
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• pp.427-439
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• 2008

In order to effectively communicate the fragrances of commercial perfumes to consumers, it is important to apply congruent colors to their bottles and packaging. This research investigated the cross-modal associations between colors and fragrances through two experiments. In the first experiment, bottle colors of more than 200 popular perfumes in the market were analyzed. Distinguishable color design patterns of the bottles were revealed in accordance with their fragrance types. The second experiment expanded the use of color-odor matching task to a test population of Korean participants. Participants selected colors evoked by fragrances of three test perfumes in a blind setting. These three perfumes had characteristic hues and their associated hues were similar with the real colors of their bottles. In addition, there were significant variations in color tone across fragrance notes, viz. the top notes, middle notes, and base notes. The results of the two experiments suggest the existence of robust cross-modal associations between particular colors and fragrances in commercial perfumery.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.470-481
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• 2006

In this paper, we propose a real-time face detection, tracking and tilted face image correction system using multi-color model and face feature information. In the proposed system, we detect face candidate using YCbCr and YIQ color model. And also, we detect face using vertical and horizontal projection method and track people's face using Hausdorff matching method. And also, we correct tilted face with the correction of tilted eye features. The experiments have been performed for 110 test images and shows good performance. Experimental results show that the proposed algorithm robust to detection and tracking of face at real-time with the change of exterior condition and recognition of tilted face. Accordingly face detection and tilted face correction rate displayed 92.27% and 92.70% respectively and proposed algorithm shows 90.0% successive recognition rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.123-129
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• 2017

New mobile phones with high tech-camera and a large size memory have been recently launched and people upload pictures of beautiful scenes or unknown flowers in SNS. This paper develops a flower recognition system that can get information on flowers in the place where mobile communication is not even available. It consists of a registration part for reference flowers and a recognition part based on OpenCV for Android platform. A new color classification method using RGB color channel and K-means clustering is proposed to reduce the recognition processing time. And ORB for feature extraction and Brute-Force Hamming algorithm for matching are used. We use 12 kinds of flowers with four color groups, and 60 images are applied for reference DB design and 60 images for test. Simulation results show that the success rate is 83.3% and the average recognition time is 2.58 s on Huawei ALEUL00 and the proposed system is suitable for a mobile phone without a network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.367-370
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• 2015

This paper proposes an improve method of the detection performance of traffic lights for autonomous driving cars. Earlier detection methods used to adopt color thresholding, template matching and based learning maching methods, but its have some problems such as recognition rate decreasing, slow processing time. The proposed method uses both detection mask and morphological preprocessing. Firstly, input color images are converted to YCbCr image in order to strengthen its illumination, and horizontal edge components are extracted in the Y Channel. Secondly, the region of interest is detected according to morphological characteristics of the traffic lights. Finally, the traffic signal is detected based on color distributions. The proposed method showed that the detection rate and processing time improved rather than the conventional algorithm about some surrounding environments.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.401-410
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• 2016

3D registration is a computer vision technique of aligning multi-view range images with respect to a reference coordinate system. Various 3D registration algorithms have been introduced in the past few decades. Iterative Closest Point (ICP) is one of the widely used 3D registration algorithms, where various modifications are available nowadays. In the ICP-based algorithms, the closest points are considered as the corresponding points. However, this assumption fails to find matching points accurately when the initial pose between point clouds is not sufficiently close. In this paper, we propose a new method to solve this problem using the 6D distance (3D color space and 3D Euclidean distances). Moreover, a color segmentation-based adaptive sampling technique is used to reduce the computational time and improve the registration accuracy. Several experiments are performed to evaluate the proposed method. Experimental results show that the proposed method yields better performance compared to the conventional methods.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.117-124
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• 2013

In this paper, we present a new method which efficiently estimates a face direction from a sequences of input video images in real time fashion. For this work, the proposed method performs detecting the facial region and major facial features such as both eyes, nose and mouth by using the Haar-like feature, which is relatively not sensitive against light variation, from the detected facial area. Then, it becomes able to track the feature points from every frame using optical flow in real time fashion, and determine the direction of the face based on the feature points tracked. Further, in order to prevent the erroneously recognizing the false positions of the facial features when if the coordinates of the features are lost during the tracking by using optical flow, the proposed method determines the validity of locations of the facial features using the template matching of detected facial features in real time. Depending on the correlation rate of re-considering the detection of the features by the template matching, the face direction estimation process is divided into detecting the facial features again or tracking features while determining the direction of the face. The template matching initially saves the location information of 4 facial features such as the left and right eye, the end of nose and mouse in facial feature detection phase and reevaluated these information when the similarity measure between the stored information and the traced facial information by optical flow is exceed a certain level of threshold by detecting the new facial features from the input image. The proposed approach automatically combines the phase of detecting facial features and the phase of tracking features reciprocally and enables to estimate face pose stably in a real-time fashion. From the experiment, we can prove that the proposed method efficiently estimates face direction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8C
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• pp.651-660
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• 2010

In this paper, we implement an efficient histogram-based prefiltering to compensate the illumination mismatches in regions between neighboring views. In multi-view video, such illumination disharmony can primarily occur on account of different camera location and orientation and an imperfect camera calibration. This discrepancy can cause the performance decrease of multi-view video coding(MVC) algorithm. A histogram matching algorithm can be exploited to make up for these differences in a prefiltering step. Once all camera frames of a multi-view sequence are adjusted to a predefined reference through the histogram matching, the coding efficiency of MVC is improved. However general frames of multi-view video sequence are composed of several regions with different color composition and their histogram distribution which are mutually independent of each other. In addition, the location and depth of these objects from sequeuces captured from different cameras can be different with different frames. Thus we propose a new algorithm which classify a image into several subpartitions by its depth information first and then histogram matching is performed for each region individually. Experimental results show that the compression ratio for the proposed algorithm is improved comparing with the conventional image-based algorithms.