• Journal of Service Research and Studies
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• v.12 no.2
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• pp.106-116
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• 2022

As part of the Fire Evacuation Service scenario using mobile applications, this study aims to find the appropriate colors to be used in the interface of the application and to define and apply colors that can positively and reliably affect human unstable psychology in the course of evacuating the room in case of fire. In the situation of fire, proper design and placement of the colored escape guidance interface is important, taking into account the psychology of the occupants. However, literature and previous research have shown that colors used to induce evacuation are not suitable for effective evacuation in case of fire. In this study, the purpose of the study was to provide a color that would provide psychological stability in the event of a evacuation in consideration of the psychological issues of those who are still in need of shelter, and to use it to help induce an efficient evacuation in the event of a disaster. Using the image evaluation method, the form and color of images have been derived through frequency analysis to a number of unspecified people, and the main and secondary colors of images were analyzed through KSCA color analysis. Finally, the final application color was constructed through mutual verification between the results by comparing and analyzing the colors obtained through the image evaluation analysis results and the KSCA color analysis results. The results of the study showed that the green line can help stabilize the human mind through comparative analysis with prior research. Therefore, the main color for guiding calm and calm applications in case of fire escape is proposed in the green line. In this study, the experiment with image evaluation cannot accurately measure the effect of factors on color among complex factors. A subsequent study of this will help quantify images if it allows the subject matter of color and image to be defined to some extent through factor analysis.

• Journal of Korea Multimedia Society
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• v.9 no.2
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• pp.215-225
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• 2006

Binary images, such as cartoon character images, text images and signature images, which consist of two values with black and white have more difficulties inserting imperceptible secret data than color images. Steganography using binary cover images is not easy to satisfy requirements for both the imperceptibility of stego images and a high embedding rate of secret data at the same time. In this paper, we propose a scheme that can get both the high quality of stego images and a high embedding rate by supplementing the advantages of previous research. In addition, the insertion of the proposed method changes only existing pixels of the imperceptible position and can embed the secret data of [$log_2(mn+1)-2$] bits in a block with size of $m{\times}n$.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.693-701
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• 2016

To make a mosaicked image, we need to estimate the geometric relationship between individual images. For such estimation, we needs tiepoint information. In general, feature-based methods are used to extract tiepoints. However, in the case of textureless images, feature-based methods are hardly applicable. In this paper, we propose a frequency domain matching method for automated mosaicking of textureless images. There are three steps in the proposed method. The first step is to convert color images to grayscale images, remove noise, and extract edges. The second step is to define a Region Of Interest (ROI). The third step is to perform phase correlation between two images and select the point with best correlation as tiepoints. For experiments, we used GOCI image slots and general frame camera images. After the three steps, we produced reliable tiepoints from textureless as well as textured images. We have proved application possibility of the proposed method.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.10
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• pp.1188-1198
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• 2011

This study proposes the use of firework shapes to design fashion accessories in the judgment that they are appropriate for the expression of creative images in consideration of the display of fireworks as a kind of entertainment and a festive symbol. This study promotes the sustainable application of firework shapes to develop the designs of fashion culture items that feature a distinctive personality and uniqueness. In this present study, the proposed fashion accessory design was intended to create an entertaining new atmosphere that uses an Organic Light Emitting Diode (OLED) that draws attention as a futuristic display. In terms of methodology, a literature review of firework shapes and OLED was conducted; in addition, Adobe Illustrator CS2 and Adobe Photoshop CS2 were used to develop six different standard motive designs with formative design elements represented by a variety of firework shapes. Each of the six motifs was further expanded with different color combinations. Rich images are produced with the use of pink, blue, purple, green, yellow, orange, and red, in conjunction with various OLED effects to express the three-dimensional images of fireworks. The motifs are applied to three types of items: bags, bracelets, and necklaces. For the video images, evening and tote bags, pendants, and bangles were used. Shifting images and lights should produce unique images as well as satisfy the consumer desire for entertainment. The Adobe Image Ready software was used to present the motive of fireworks applied to the design of fashion accessories in video images but not in still-cut images due to physical constraints of this paper.

• Journal of Animal Science and Technology
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• v.65 no.3
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• pp.638-651
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• 2023

The objective of this study was to quantitatively estimate the level of grazing area damage in outdoor free-range pig production using a Unmanned Aerial Vehicles (UAV) with an RGB image sensor. Ten corn field images were captured by a UAV over approximately two weeks, during which gestating sows were allowed to graze freely on the corn field measuring 100 × 50 m². The images were corrected to a bird's-eye view, and then divided into 32 segments and sequentially inputted into the YOLOv4 detector to detect the corn images according to their condition. The 43 raw training images selected randomly out of 320 segmented images were flipped to create 86 images, and then these images were further augmented by rotating them in 5-degree increments to create a total of 6,192 images. The increased 6,192 images are further augmented by applying three random color transformations to each image, resulting in 24,768 datasets. The occupancy rate of corn in the field was estimated efficiently using You Only Look Once (YOLO). As of the first day of observation (day 2), it was evident that almost all the corn had disappeared by the ninth day. When grazing 20 sows in a 50 × 100 m² cornfield (250 m²/sow), it appears that the animals should be rotated to other grazing areas to protect the cover crop after at least five days. In agricultural technology, most of the research using machine and deep learning is related to the detection of fruits and pests, and research on other application fields is needed. In addition, large-scale image data collected by experts in the field are required as training data to apply deep learning. If the data required for deep learning is insufficient, a large number of data augmentation is required.

• The International Journal of Costume Culture
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• v.13 no.2
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• pp.141-153
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• 2010

Fashion needs to be understood as practicality and creative behavior and various movements of paintings act as inspirations of original design for fashion designers. This study seeks to find sources of fashion designs in the works of Mark Rothko who is in the center of color-field abstract. Color-field of Rothko provides infinite inspirations as colors are identically treated as shapes and lighting and textures are all included on top of it. In this study, the purpose is to create color focused artistic fashion design by exploring the possibility of expression with the colors of Rothko as the main motive. The study method is as follows. First, the concept and significance of color-field abstract are researched through documented data. Works of Rothko is divided into three periods according to their characteristics. The background of the formation of color-field abstract of Rothko is understood by analyzing the trends of the works in each period. Second, twenty representative works from 1949 to 1969 are selected and analyzed in formative components of color, shape and textures in order to more accurately understand shape of colors, brilliance, simplicity that appear in the mature color-field abstract of Rothko. Third, preexisting methods of color-field of paintings developed into motives of clothing are studied focusing on the collections from 1997 to 2006. Examples of applications of color-field images in modern fashion designs are analyzed. Fourth, motives are selected based on general characteristics of color-field abstract of Rothko and the results of the formative analysis. Clothing is produced that expresses the colors of the paintings of Rothko more effectively. As the results of the study, restrained shapes and textures and various forms of color combinations shown in color-field abstract of Rothko provided deep inspirations on material composition and color planning for fashion design focused on colors. Additionally, needle-punching technique using wool for the production technique enabled relief texture expressions of materials by colors and effective applications of soft and warm atmosphere of color-field abstract of Rothko on clothing. Especially, the ideology of color-field abstract of Rothko of shaping of colors could be expressed and the direction of the development of motives could be presented at the same time by specifically applying color combination method using horizontal division of atypical color-field from the formative characteristics of color-field abstract of Rothko.

• Imaging Science in Dentistry
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• v.32 no.3
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• pp.135-139
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• 2002

Purpose: To determine the proper reference step wedge for digital Cu-Equivalent Image analyzing systems for measurement of bone density. Meterials and Methods : Radiograms of lumbar vertebrae phantom (1g/㎠) with 3 test copper step wedges of 0.03, 0.05 and, 0.1 mm thickness unit were taken and analyzed using NIH image software on a Macintosh personal computer. Measured densities of the lumbar areas in the Cu-Equivalent images made by utilizing 3 different copper stepwedges were compared with a known bone density. Results: The values of r2 for all copper equivalent images were over 0.99. The mean Cu-Eq value of lumbar in copper equivalent image made by a 0.1 mm copper stepwedge was 0.22 ± 0.06 mm and converted to hydroxyapatite density of 1.03 g/㎠. The stepwedges of 0.03 and 0.05 mm produced results having higher values than the actual known bone density. They did not show the blue and green color level that appeared in lumbar on color enhanced image. Conclusion : A copper stepwedge of adequate thickness and range of steps which can express the range of density of bone being measured should be used.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.4
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• pp.333-337
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• 2002

A content-based image retrieval method using color, texture, and shape features is proposed in this paper. A region segmentation technique using PIM(Picture Information Measure) entropy is used for similarity indexing. For segmentation, a color image is first transformed to a gray image and it is divided into n$\times$n non-overlapping blocks. Entropy using PIM is obtained from each block. Adequate variance to perform good segmentation of images in the database is obtained heuristically. As variance increases up to some bound, objects within the image can be easily segmented from the background. Therefore, variance is a good indication for adequate image segmentation. For high variance image, the image is segmented into two regions-high and low entropy regions. In high entropy region, hue-saturation-intensity and canny edge histograms are used for image similarity calculation. For image having lower variance is well represented by global texture information. Experiments show that the proposed method displayed similar images at the average of 4th rank for top-10 retrieval case.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.8
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• pp.837-841
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• 2010

This paper proposes an effective similarity measure for content-based image retrieval using MPEG-7 DCD. The proposed method can measure the similarity of images with the percentage of dominant colors extracted from images. As the result of experiments, we achieved a significant improvement of 18.92% with global DCD and 47.22% with local DCD in ANMRR than the result by QHDM. This result shows that the proposed method is an effective similarity measure for content-based image retrieval. Especially, our method is useful for region-based image retrieval.

• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.257-264
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• 2009

This paper proposes a novel face detection method that finds tiny faces located at a long range even with low-resolution input images captured by a mobile robot. The proposed approach can locate extremely small-sized face regions of $12{\times}12$ pixels. We solve a tiny face detection problem by organizing a system that consists of multiple detectors including a mean-shift color tracker, short- and long-rage face detectors, and an omega shape detector. The proposed method adopts the long-range face detector that is well trained enough to detect tiny faces at a long range, and limiting its operation to only within a search region that is automatically determined by the mean-shift color tracker and the omega shape detector. By focusing on limiting the face search region as much as possible, the proposed method can accurately detect tiny faces at a long distance even with a low-resolution image, and decrease false positives sharply. According to the experimental results on realistic databases, the performance of the proposed approach is at a sufficiently practical level for various robot applications such as face recognition of non-cooperative users, human-following, and gesture recognition for long-range interaction.