• Journal of Information Display
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• v.12 no.4
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• pp.179-190
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• 2011

A complete analysis of the color-viewing-angle properties of different displays is presented herein using color-viewing-angle measurements made with a Fourier-optics system. The color gamut in the CIE u'v' chromatic plane was computed for all the viewing angles. The introduction of the lightness using the $L^*a^*b^*$ color space allowed a more precise analysis of the emissive properties of each display. The displays can be directly compared using a common reference. The viewing-angle dependence can be analyzed in full detail using the on-axis values as reference. The gravity center behavior and area of the color hull were computed for a more precise evaluation and comparison.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.1
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• pp.41.2-41.2
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• 2012

It has been suggested that merging plays an important role in the formation and the evolution of early-type galaxies (ETGs). Optical-NIR color gradients of ETGs in high density environments are found to be less steep than those of ETGs in low density environments, hinting frequent merger activities in ETGs in high density environments. In order to examine if the flat color gradients are the result of dry mergers, we studied the relations between merging features, luminosities, environments and color gradients of 196 low redshift ETGs selected from Sloan Digital Sky Survey (SDSS) Stripe82. Near Infrared (NIR) images are taken from UKIRT Infrared Deep Sky Survey (UKIDSS) Large Area Survey (LAS). Color (r-K) gradients of ETGs with tidal features are a little flatter than relaxed ETGs, but not significant. We found that massive (> 10^11.3 solar masses) ETGs have -40% less scattered color gradients than less massive ETGs. The less scattered color gradients of massive ETGs could be evidence of dry merger processes in the evolution of massive ETGs. We found no relation between color gradients of ETGs and their environments.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.42-42
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• 2017

Prediction of rice yield during a growing season would be very helpful to magnify rice yield as it also allows better farm practices to maximize yield with greater profit and lesser costs. UAV imagery based automatic detection of rice can be a relevant solution for early prediction of yield. So, we propose an image processing technique to predict rice yield using low altitude UAV images. We proposed $L^*a^*b^*$ color space based image segmentation algorithm. All images were captured using UAV mounted RGB camera. The proposed algorithm was developed to find out rice grain area from the image background. We took RGB image and applied filter to remove noise and converted RGB image to $L^*a^*b^*$ color space. All color information contain in both $a^*$ and $b^*$ layers and by using k-mean clustering classification of these colors were executed. Variation between two colors can be measured and labelling of pixels was completed by cluster index. Image was finally segmented using color. The proposed method showed that rice grain could be segmented and we can recognize rice grains from the UAV images. We can analyze grain areas and by estimating area and volume we could predict rice yield.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.1
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• pp.107-112
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• 2016

Fastener is a very important component that is used in various areas in industry. Recently, various color fasteners are introduced. According to this, online inspection is required in this area. In this paper, an algorithm for the automatic extraction of the surface of color fastener using color information and dynamic programming is presented. The outer boundary of fastener is found using the difference of color that enables robust processing. The inner boundary of fastener is found by dynamic programming that uses the difference of brightness value within fixed area after converting image to polar coordinate. Experiments are done using the same parameters.

• Journal of Fashion Business
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• v.11 no.3
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• pp.87-96
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• 2007

The purpose of this study is to analyse the characteristics of style, color and items of street fashion in Harbin. This kind of study will contribute to the understanding the preference of fashion in northeastern area, thereby, affording a fundamental resources for the strategic establishments of design and marketing in Korean brand launching into China. The results of this study are as follows. The preferred fashion style is casual one, rather than formal one. The order of preference in casual wear is character, jean and sports casual. In the view of color, preference in top color is, white, black, brown and pink. In the bottom, it is blue, white, black and brown. In one-piece, it is white, blue and brown. Throughout all items, the most frequently founded color is white, which might be ascribed to the seasonal influence of summer. The Chinese specific preference of color could not be observed. In aspect of items, the one-piece takes the proportions of more than half of the all the items. The typical details of one-piece dress are irregular hemline and asymmetrical line. While knee length takes proportion of 70%, in item of skirt, the full length is 46.8% in frequency for pants. In one-piece, knee length is 80% amounted as first rank, followed by midi and mini.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.160-161
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• 2010

In this paper, trademark image retrieval system is proposed by using color information and shape information. We use the image for a color information by dividing into the area and extracting the area color distribution histogram. We use for the shape information by preprocessing of the boundary extraction, the centroid extraction, angular sampling etc. and calculating of the sum of the distance from the centroid to the boundary, the standard deviation, and the rate of long axis to short axis. In particular, centroid by using the angular sampling can extract feature and reduce the processing time. Users can perform searchs using the color and shape information, and also the two methods by mixing can be used by weighting.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.1-6
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• 2018

In this paper, we propose a method dividing effectively the hand and fingers using general webcam. The method executes 4 times empirically preprocessing one to erase noise. First, it erases the overall noise of the image using Gaussian smoothing. Second, it changes from RGB image to HSV color model and YCbCr color model, executes a global static binarization based on the statistical value for each color model, and erase the noise through bitwise-OR operation. Third, it executes outline approximation and inner region filling algorithm using RDP algorithm and Flood fill algorithm and erase noise. Lastly, it erases noise through morphological operation and determines the threshold propositional to the image size and selects the hand and fingers area. This paper compares to existing one color based hand area division method and focuses the noise deduction and can be used to a gesture recognition application.

• Journal of Broadcast Engineering
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• v.14 no.4
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• pp.397-408
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• 2009

In this paper, we present a non-static color histogram method to retrieve clothing images that are similar to a query clothing. Given clothing area, our method automatically extracts major colors by using the octree-based quantization approach[16]. Then, a color palette that is composed of the major colors is generated. The feature of each clothing, which can be either a query or a database clothing image, is represented as a color histogram based on its color palette. We define the match color bins between two possibly different color palettes, and unify the color palettes by merging or deleting some color bins if necessary. The similarity between two histograms is measured by using the weighted Euclidean distance between the match color bins, where the weight is derived from the frequency of each bin. We compare our method with previous histogram matching methods through experiments. Compared to HSV cumulative histogram-based approach, our method improves the retrieval precision by 13.7 % with less number of color bins.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.9-15
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• 2015

Various studies with regard to increasing the optical efficiency of plasmonic color filters have previously been conducted, such as mixing materials or applying diverse pattern shapes. Fundamentally, it is important to maximize the photonic crystal effect by finding the optimum periods of lattice as well as calculating the most efficient transmission area. In this study, we propose a technical method for optimizing the plasmonic color filters that have a high color gamut and luminance by analyzing the light spectrums based on the 1931 color coordinate system. Moreover, we suggest a calculation method in order to define the individual color purity of red and green and blue filters. Consequently, efficiency values are obtained independently from each color filter by evaluating the color purity and the luminance. The final result obtained from simulation are 27.6% of relative luminance and 25.3% of color gamut. The proposed optimization method is applicable to all plasmonic color filters having photonic crystal arrays.

• Agricultural and Biosystems Engineering
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• v.4 no.1
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• pp.16-21
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• 2003

In the agricultural field, a machine vision system has been widely used to automate most inspection processes especially in quality grading. Though machine vision system was very effective in quantifying geometrical quality factors, it had a deficiency in quantifying color information. This study was conducted to evaluate color of beef using machine vision system. Though measuring color of a beef using machine vision system had an advantage of covering whole lean tissue area at a time compared to a colorimeter, it revealed the problem of sensitivity depending on the system components such as types of camera, lighting conditions, and so on. The effect of color balancing control of a camera was investigated and multi-layer BP neural network based color calibration process was developed. Color calibration network model was trained using reference color patches and showed the high correlation with L*a*b* coordinates of a colorimeter. The proposed calibration process showed the successful adaptability to various measurement environments such as different types of cameras and light sources. Compared results with the proposed calibration process and MLR based calibration were also presented. Color calibration network was also successfully applied to measure the color of the beef. However, it was suggested that reflectance properties of reference materials for calibration and test materials should be considered to achieve more accurate color measurement.