• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.7
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• pp.490-495
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• 2018

A multielectrode electronic paper film capable of expressing a single-color image was fabricated by injecting color electronic ink into an electronic paper panel; on the basis of its reflective or transparent properties, it is possible to control the expression of six single-color images and their transmittance. In this study, a single-color image was represented by driving a multielectrode electronic paper film; color coordinates were measured. The six capable single colors were yellowish pink (0.444, 0.354), white (0.355, 0.352), black (0.241, 0.241), orange (0.514, 0.360), reddish orange (0.606, 0.338), and reddish purple (0.469, 0.145). Color particles used in this paper were black and white, by which six colors are accomplished, but more single-color images can be combined by using cyan, magenta, and yellow particles.

• Journal of Information Processing Systems
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• v.10 no.2
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• pp.283-299
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• 2014

Skin detection is used in many applications, such as face recognition, hand tracking, and human-computer interaction. There are many skin color detection algorithms that are used to extract human skin color regions that are based on the thresholding technique since it is simple and fast for computation. The efficiency of each color space depends on its robustness to the change in lighting and the ability to distinguish skin color pixels in images that have a complex background. For more accurate skin detection, we are proposing a new threshold based on RGB and YUV color spaces. The proposed approach starts by converting the RGB color space to the YUV color model. Then it separates the Y channel, which represents the intensity of the color model from the U and V channels to eliminate the effects of luminance. After that the threshold values are selected based on the testing of the boundary of skin colors with the help of the color histogram. Finally, the threshold was applied to the input image to extract skin parts. The detected skin regions were quantitatively compared to the actual skin parts in the input images to measure the accuracy and to compare the results of our threshold to the results of other's thresholds to prove the efficiency of our approach. The results of the experiment show that the proposed threshold is more robust in terms of dealing with the complex background and light conditions than others.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.267-273
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• 2017

With the development of various devices and communication technologies, the production and distribution of various multimedia contents are increasing exponentially. In order to retrieve multimedia data such as images and videos, an approach different from conventional text-based retrieval is needed. Color and shape are key features used in content-based image retrieval, which quantifies and analyzes various physical features of images and compares them to search for similar images. Color and shape have been used as independent features, but the two features are closely related in terms of cognition. In this paper, a method of describing the spatial distribution of color using a complex color model that projects three-dimensional color information onto two-dimensional complex form is proposed. Experimental results show that the proposed method can efficiently represent the shape of spatial distribution of colors by frequency transforming the complex image and reconstructing it with only a few coefficients in the low frequency.

• Journal of the Korean Geotechnical Society
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• v.38 no.5
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• pp.61-71
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• 2022

Soil color is used to determine soil classification and its physical, chemical, and biological properties. Visual determination is the most commonly used method for identifying soil color. However, it is subjective and, in many cases, non-repeatable. Digital image processing obtains useful information from digital images, accelerates soil classification, and enables the rapid identification of soil types in a field. This study develops a digital image processing-based soil color analysis technology that can consider irregular light conditions in the field. The digital image studio was designed to simulate the characteristics of natural light (illuminance and color temperature). Also, digital images of two soil samples (Jumoonjin sand and Anseong weathered soil) were captured under 12 different light conditions. For the RGB and CIELAB color systems, soil color intensities of 24 images were obtained using digital image processing. CIELAB was suitable for dealing with irregular light conditions in the field.

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.911-923
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• 2012

Recently, 3DTV and 3D displays have been released in the market. Accordingly, the production of stereoscopic images has gained much interest. Stereoscopic image being composed of left and right images are currently delivered to viewers without any modifications. The researches on the enhancement of depth perception using high-frequency components and the re-production of natural color by color compensation have been carried out for 2D images. The application of such 2D technologies to 3D stereoscopic images is an aim of this paper. This paper proposes the enhancement of 3D perception by color transformation. For this, we propose a stereo matching method for obtaining a depth map and two color transformation methods such as contrast transformation and background darkening. The effectiveness of the proposed method was verified through experiments.

• Korean Journal of Human Ecology
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• v.19 no.6
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• pp.1071-1082
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• 2010

This study examined the effects of underwear brand identity color on brand equity. A self-administered questionnaire mainly consisted of BI color, brand image, and brand equity for underwear. Five underwear brands (Calvin Klein, Yes, Solb, Venus, and Body Guard) were selected based on the frequency they were purchased in pilot study. To collect data, respondents were asked to choose a brand which they were most familiar with, and to assess BI color, brand image, and brand equity including cognitive value, emotional value and purchase intention. A total of 228 usable questionnaires were obtained from consumers aged 19 to 46. BI colors were classified into four color groups: Achromatic (white, black, gray), Vivid (red, blue, yellow), Pink, and Beige. Additionally, underwear brand images consisted of four factors: Sophisticated, Classic, Casual, and Elegant images. Findings showed significant differences in the four factors of brand image and cognitive brand value between the BI color groups. Also, the factor of cognitive value was higher for achromatic or beige brand color groups, than for vivid or pink color groups. Also, brand image factors had positive effects on cognitive or emotional brand value. Especially, the factor of emotional value was more likely to increase purchase intentions than cognitive value in the BI color groups. The implications for managerial decision marking in fashion marketing strategy were also discussed.

• Journal of Information Display
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• v.12 no.1
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• pp.37-41
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• 2011

Presented herein is a novel stereoscopic three-dimensional (3D) display system with active color filter glasses. This system provides full-color 3D images by applying the time-multiplexing technique on the original anaglyph method. By switching between the opposite anaglyph statuses, a full-color anaglyph is presented. A liquid crystal panel from a 3D monitor serves as an active color filter operating at 120 Hz. A display panel and a color filter are connected to one graphic card as a dual-link system, for synchronization. To test the quality of this system, a left/right-eye image separation test and an experiment with stereoscopic images were carried out. Although there was some crosstalk and blur, the system, as expected, provided full-color 3D display. This system overcomes a monochromatic 3D image, which is the major weakness of the original anaglyph system.

• 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.

• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.773-780
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• 2009

This study proposed a face region detection algorithm using fuzzy inference of pixel hue and intensity. The proposed algorithm is composed of light compensate and face detection. The light compensation process performs calibration for the change of light. The face detection process evaluates similarity by generating membership functions using as feature parameters hue and intensity calculated from 20 skin color models. From the extracted face region candidate, the eyes were detected with element C of color model CMY, and the mouth was detected with element Q of color model YIQ, the face region was detected based on the knowledge of an ordinary face. The result of experiment are conducted with frontal face color images of face as input images, the method detected the face region regardless of the position and size of face images.

• Journal of the Optical Society of Korea
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• v.19 no.1
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• pp.102-111
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• 2015

This paper proposes an algorithm for recovering the colors of objects from multiple near-infrared (near-IR) images. The International Commission on Illumination (CIE) color coordinates of objects are recovered from a series of gray images captured under multiple spectral near-IR illuminations using polynomial regression. The feasibility of the proposed algorithm is tested experimentally by using 24 color patches of the Color Rendition Chart. The experimental apparatus is composed of a monochrome digital camera without an IR cut-off filter and a custom-designed LED illuminator emitting multiple spectral near-IR illuminations, with peak wavelengths near the red edge of the visible band, namely at 700, 740, 780, and 860 nm. The average color difference between the original and the recovered colors for all 24 patches was found to be 11.1. However, if some particular patches with high value are disregarded, the average color difference is reduced to 4.2, and this value is within the acceptability tolerance for complex image on the display.