• Journal of Sensor Science and Technology
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• v.27 no.6
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• pp.392-396
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• 2018

Structural color has many advantages over pigment based color. In recent years, researches are being conducted to apply these advantages to applications such as wearable devices. In this study, strain sensor, a kind of wearable device, was developed using structural color. The use of structural color has the advantage of not using energy and complex measuring equipment to measure strain rate. Wrinkle structure was fabricated on the surface of Poly-dimethylsiloxane (PDMS) and used it as a sensor which color changes according to the applied strain. In addition, a transmittance-changing sensor was developed and fabricated by synthesizing additional glass nanoparticles. Furthermore, a strain sensor was developed that is largely transparent at the target strain and opaque otherwise.

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.616-622
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• 2014

Specular structural colors generated by two-dimensional periodic binary gratings are investigated theoretically. An approximate mathematical model of the grating specular structural colors is described, based on scalar nonparaxial diffraction theory, and the functional relationships of specular structural color and structural parameters of gratings are analyzed. Through this, the optimal condition for maximizing the color-representation range in the standard CIE 1931 chromaticity diagram is derived.

• Journal of Industrial Technology
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• v.39 no.1
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• pp.33-39
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• 2019

This paper addresses effects of nanoscale structures on structural colors of micropatterned transparent substrate by light diffraction. Structural colors is widely investigated because they present colors without any chemical pigments. Typically structural colors is presented by diffraction of light on a micropatterned surface or by multiple interference of light on a surface containing a periodic or quasi-periodic nano-structures. In this paper, each structural colors induced by quasi-periodic nano-structures, periodic micro-structures, and nano/micro dual structures is measured in order to investigate effects of nanoscale and microscale structures on structural colors in the transparent substrate. Using pre-fabricated pattern mold and hot-embossing process, nanoscale and microscale structures are replicated on the transparent PMMA(Poly methyl methacrylate) substrate. Nanoscale and microscale pattern molds are prepared by anodic oxidation process of aluminum sheet and by reactive ion etching process of silicon wafer, respectively. Structural colors are captured by digital camera, and their optical transmittance spectrum are measured by UV/visible spectrometer. From experimental results, we found that nano-structures provide monotonic colors by multiple interference, and micro-structures induce iridescent colors by diffraction of light. Structural colors is permanent and unchangeable, thus it can be used in various application field such as security, color filter and so on.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.10-16
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• 2007

In this paper, we propose a technique for retrieving images using spatial color correlation and texture characteristics based on local fourier transform. In order to retrieve images, two new descriptors are proposed. One is a color descriptor which represents spatial color correlation. The other is a descriptor combining the proposed color descriptor with texture descriptor. Since most of existing color descriptors including color correlogram which represent spatial color correlation considered just color distribution between neighborhood pixels, the structural information of neighborhood pixels is not considered. Therefore, a novel color descriptor which simultaneously represents spatial color distribution and structural information is proposed. The proposed color descriptor represents color distribution of Min-Max color pairs calculating color distance between center pixel and neighborhood pixels in a block with 3x3 size. Also, the structural information which indicates directional difference between minimum color and maximum color is simultaneously considered. Then new color descriptor(min-max color correlation descriptor, MMCCD) containing mean and variance values of each directional difference is generated. While the proposed color descriptor includes by far smaller feature vector over color correlogram, the proposed color descriptor improves 2.5 % ${\sim}$ 13.21% precision rate, compared with color correlogram. In addition, we propose a another descriptor which combines the proposed color descriptor and texture characteristics based on local fourier transform. The combined method reduces size of feature vector as well as shows improved results over existing methods.

• Journal of KIISE
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• v.42 no.10
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• pp.1294-1302
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• 2015

A lot of image quality assessment metrics that can precisely reflect the human visual system (HVS) have previously been researched. The Structural SIMilarity (SSIM) index is a remarkable HVS-aware metric that utilizes structural information, since the HVS is sensitive to the overall structure of an image. However, SSIM fails to deal with color difference in terms of the HVS. In order to solve this problem, the Structural and Hue SIMilarity (SHSIM) index has been selected with the Hue, Saturation, Intensity (HSI) model as a color space, but it cannot reflect the HVS-aware color difference between two color images. In this paper, we propose a new image quality assessment method for a color image by using a CIE Lab color space. In addition, by using a support vector machine (SVM) classifier, we also propose an optimization system for applying optimal metric according to the types of distortion. To evaluate the proposed index, a LIVE database, which is the most well-known in the area of image quality assessment, is employed and four criteria are used. Experimental results show that the proposed index is more consistent with the other methods.

• Science of Emotion and Sensibility
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• v.13 no.2
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• pp.337-346
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• 2010

The purposes of this research were to evaluate the color sensibility and preferences, and to analyze the effect of the tactile preferences and purchasing preference on structural properties, color characteristics and color sensibility for the black color fabrics. Male and female university students were asked to evaluate the color sensibility, tactile preference and purchasing preference to the nine different black fabrics which were selected on the basis of the previous research results. Data were analyzed by using frequency analysis, mean, factor analysis, t-test, Kruskal-Wallis test, correlation and regression analysis. The color sensibility for black color fabrics was classified into four factors: simplicity/classic, elegance, modernity and dignity. This color sensibility factors showed a significant correlative relationship to the structural properties and color characteristics of black color fabrics. On the other hand, fabrics which were evaluated with good tactile preference among the black color fabrics tended to show higher purchasing preference. Also, among the color sensibility, the structural properties and color characteristics of black color fabrics, major variable factor of influencing on the tactile preference and the purchasing preference was turned out to be the color sensibility.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.203-207
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• 2001

In this Paper, we propose the neural network based emotion recognition method for intelligently recognizing the human's emotion using CCD color image. To do this, we first acquire the color image from the CCD camera, and then propose the method for recognizing the expression to be represented the structural correlation of man's feature Points(eyebrows, eye, nose, mouse) It is central technology that the Process of extract, separate and recognize correct data in the image. for representation is expressed by structural corelation of human's feature Points In the Proposed method, human's emotion is divided into four emotion (surprise, anger, happiness, sadness). Had separated complexion area using color-difference of color space by method that have separated background and human's face toughly to change such as external illumination in this paper. For this, we propose an algorithm to extract four feature Points from the face image acquired by the color CCD camera and find normalization face picture and some feature vectors from those. And then we apply back-prapagation algorithm to the secondary feature vector. Finally, we show the Practical application possibility of the proposed method.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.3
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• pp.503-515
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• 2018

In this research, the three-dimensional structural and colorimetrical modeling of yarn-dyed woven fabrics was conducted based on the Kubelka-Munk theory (K-M theory) for their accurate color predictions. In the K-M theory for textile color formulation, the absorption and scattering coefficients, denoted K and S, respectively, of a colored fabric are represented using those of the individual colorants or color components used. One-hundred forty woven fabric samples were produced in a wide range of structures and colors using red, yellow, green, and blue yarns. Through the optimization of previous two-dimensional color prediction models by considering the key three-dimensional structural parameters of woven fabrics, three three-dimensional K/S-based color prediction models, that is, linear K/S, linear log K/S, and exponential K/S models, were developed. To evaluate the performance of the three-dimensional color prediction models, the color differences, ${\Delta}L^*$, ${\Delta}C^*$, ${\Delta}h^{\circ}$, and ${\Delta}E_{CMC(2:1)}$, between the predicted and the measured colors of the samples were calculated as error values and then compared with those of previous two-dimensional models. As a result, three-dimensional models have proved to be of substantially higher predictive accuracy than two-dimensional models in all lightness, chroma, and hue predictions with much lower ${\Delta}L^*$, ${\Delta}C^*$, ${\Delta}h^{\circ}$, and the resultant ${\Delta}E_{CMC(2:1)}$ values.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1252-1255
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• 2002

In this paper, face recognition algorithm, by using skin color information of HSI color coordinate collected from face images, elliptical mask, fratures of face including eyes, nose and mouth, and geometrical feature vectors of face and facial angles, is proposed. The proposed algorithm improved face region extraction efficacy by using HSI information relatively similar to human's visual system along with color tone information about skin colors of face, elliptical mask and intensity information. Moreover, it improved face recognition efficacy with using feature information of eyes, nose and mouth, and Θ1(ACRED), Θ2(AMRED) and Θ 3(ANRED), which are geometrical face angles of face. In the proposed algorithm, it enables exact face reading by using color tone information, elliptical mask, brightness information and structural characteristic angle together, not like using only brightness information in existing algorithm. Moreover, it uses structural related value of characteristics and certain vectors together for the recognition method.

• The Research Journal of the Costume Culture
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• v.19 no.3
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• pp.556-564
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• 2011

The purpose of this study was to analyze the effect of the structural properties, the color characteristics and the texture of sight and touch on the tactile preferences for the black fabrics. Male and female university students were asked to evaluate the texture of sight and touch and tactile preference to the nine different black fabrics which were selected on the basis of the previous research results. Data were analyzed by using frequency analysis, mean, factor analysis, t-test, F-test, correlation and regression analysis. The texture of sight and touch for black fabrics was classified into four factors: smoothness, bulkiness, extensibility, firmness. This texture of sight and touch factors showed a significant correlative relationship to the structural properties and color characteristics of the black fabrics. There were significant differences according to black fabrics on the point of texture of sight and touch. The velvet was evaluated the most smooth fabric, while the velvet and fake leather were evaluated the most bulky fabrics. Also, the jersey and lace fabrics were evaluated the most extensible fabrics, while the melton was evaluated as the most firm fabrics. There were significant correlative relationships not only between the structural properties and the texture of sight and touch but also between the color characteristics and the texture for black fabrics. Also, among the structural properties, the color characteristics and the texture of sight and touch of black fabrics, major variable factor of influencing on the tactile preference was turned out to be the texture of sight and touch.