• Journal of dental hygiene science
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• v.21 no.4
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• pp.219-226
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• 2021

Background: Proper detection and management of dental plaque are essential for individual oral health. We aimed to evaluate the maturation level of dental plaque using a two-tone disclosing agent and to compare it with the fluorescence of dental plaque on the quantitative light-induced fluorescence (QLF) image to obtain primary data for the development of a new dental plaque scoring system. Methods: Twenty-eight subjects who consented to participate after understanding the purpose of the study were screened. The images of the anterior teeth were obtained using the QLF device. Subsequently, dental plaque was stained with a two-tone disclosing solution and a photograph was obtained with a digital single-lens reflex (DSLR) camera. The staining scores were assigned as follows: 0 for no staining, 1 for pink staining, and 2 for blue staining. The marked points on the DSLR images were selected for RGB color analysis. The relationship between dental plaque maturation and the red/green (R/G) ratio was evaluated using Spearman's rank correlation. Additionally, different red fluorescence values according to dental plaque accumulation were assessed using one-way analysis of variance followed by Scheffe's post-hoc test to identify statistically significant differences between the groups. Results: A comparison of the intensity of red fluorescence according to the maturation of the two-tone stained dental plaque confirmed that R/G ratio was higher in the QLF images with dental plaque maturation (p<0.001). Correlation analysis between the stained dental plaque and the red fluorescence intensity in the QLF image confirmed an excellent positive correlation (p<0.001). Conclusion: A new plaque scoring system can be developed based on the results of the present study. In addition, these study results may also help in dental plaque management in the clinical setting.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.975-986
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• 2022

Deep learning is attracting great attention, showing excellent performance in image processing, but is vulnerable to adversarial attacks that cause the model to misclassify through perturbation on input data. Adversarial examples generated by adversarial attacks are minimally perturbated where it is difficult to identify, so visual features of the images are not generally changed. Unlikely deep learning models, people are not fooled by adversarial examples, because they classify the images based on such visual features of images. This paper proposes adversarial attack detection method using Symbolic Representation, which is a visual and symbolic features such as color, shape of the image. We detect a adversarial examples by comparing the converted Symbolic Representation from the classification results for the input image and Symbolic Representation extracted from the input images. As a result of measuring performance on adversarial examples by various attack method, detection rates differed depending on attack targets and methods, but was up to 99.02% for specific target attack.

• The Journal of Information Systems
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• v.31 no.4
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• pp.145-160
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• 2022

Purpose The purpose of this study is to develop a virtual try-on deep learning model that can efficiently learn front and back clothes images. It is expected that the application of virtual try-on clothing service in the fashion and textile industry field will be vitalization. Design/methodology/approach The data used in this study used 232,355 clothes and product images. The image data input to the model is divided into 5 categories: original clothing image and wearer image, clothing segmentation, wearer's body Densepose heatmap, wearer's clothing-agnosting. We advanced the HR-VITON model in the way of Mixed-Precison, Gradient Accumulation, and sharing model weights. Findings As a result of this study, we demonstrated that the weight-shared MP-GA HR-VITON model can efficiently learn front and back fashion images. As a result, this proposed model quantitatively improves the quality of the generated image compared to the existing technique, and natural fitting is possible in both front and back images. SSIM was 0.8385 and 0.9204 in CP-VTON and the proposed model, LPIPS 0.2133 and 0.0642, FID 74.5421 and 11.8463, and KID 0.064 and 0.006. Using the deep learning model of this study, it is possible to naturally fit one color clothes, but when there are complex pictures and logos as shown in <Figure 6>, an unnatural pattern occurred in the generated image. If it is advanced based on the transformer, this problem may also be improved.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.27-39
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• 2024

Soil texture is determined by the proportions of sand, silt, and clay within the soil, which influence characteristics such as porosity, water retention capacity, electrical conductivity (EC), and pH. Traditional classification of soil texture requires significant sample preparation including oven drying to remove organic matter and moisture, a process that is both time-consuming and costly. This study aims to explore an alternative method by developing an AI model capable of predicting soil texture from images of pre-sorted soil samples using computer vision and deep learning technologies. Soil samples collected from agricultural fields were pre-processed using sieve analysis and the images of each sample were acquired in a controlled studio environment using a smartphone camera. Color distribution ratios based on RGB values of the images were analyzed using the OpenCV library in Python. A convolutional neural network (CNN) model, built on PyTorch, was enhanced using Digital Image Processing (DIP) techniques and then trained across nine distinct conditions to evaluate its robustness and accuracy. The model has achieved an accuracy of over 80% in classifying the images of pre-sorted soil samples, as validated by the components of the confusion matrix and measurements of the F1 score, demonstrating its potential to replace traditional experimental methods for soil texture classification. By utilizing an easily accessible tool, significant time and cost savings can be expected compared to traditional methods.

• Progress in Medical Physics
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• v.21 no.2
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• pp.153-164
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• 2010

To determine the clinical target volumes considering vascularity and cellularity of tumors, the software was developed for mapping of the analyzed biological clinical target volumes on anatomical images using regional cerebral blood volume (rCBV) maps and apparent diffusion coefficient (ADC) maps. The program provides the functions for integrated registrations using mutual information, affine transform and non-rigid registration. The registration accuracy is evaluated by the calculation of the overlapped ratio of segmented bone regions and average distance difference of contours between reference and registered images. The performance of the developed software was tested using multimodal images of a patient who has the residual tumor of high grade gliomas. Registration accuracy of about 74% and average 2.3 mm distance difference were calculated by the evaluation method of bone segmentation and contour extraction. The registration accuracy can be improved as higher as 4% by the manual adjustment functions. Advanced MR images are analyzed using color maps for rCBV maps and quantitative calculation based on region of interest (ROI) for ADC maps. Then, multi-parameters on the same voxels are plotted on plane and constitute the multi-functional parametric maps of which x and y axis representing rCBV and ADC values. According to the distributions of functional parameters, tumor regions showing the higher vascularity and cellularity are categorized according to the criteria corresponding malignant gliomas. Determined volumes reflecting pathological and physiological characteristics of tumors are marked on anatomical images. By applying the multi-functional images, errors arising from using one type of image would be reduced and local regions representing higher probability as tumor cells would be determined for radiation treatment plan. Biological tumor characteristics can be expressed using image registration and multi-functional parametric maps in the developed software. The software can be considered to delineate clinical target volumes using advanced MR images with anatomical images.

• The Research Journal of the Costume Culture
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• v.7 no.6
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• pp.129-139
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• 1999

This paper analyzes the trend of fashion and make-up in 1990s and their relevancy to each other. Based on the chronological analysis, we propose a new category for the fashion and make-up trend in 1990s, which is 1) traditional ecology period(1990∼1994), 2) versatile trial or decadent period(1995∼1997), and 3) soft landing period based on the minimal neo-ecology and romanticism(1998∼2000). Between 1990 and 1994, there was no differentiation in seasons. It appeared that spring/summer and fall/winter trend have had no big differences. At the beginning in 1990s, it was basically based on ecology concept that emphasizes the natural image. However after 1995, seasonal differences in trend are appeared and there were various make-up designs. The trends of spring/summer in 1996 could be named as color revolution period that emphasized the unique and individual expression of each person. In 1997, black, pastel, and brown colors were the result of reinterpreting the classic and sexy images of 1960s to natural and modernistic image of 1997. Purple color started to be introduced to us. In 1998, pastel tone, pink, and purple color expresses the glamorous look based on the romantic feminism. S/S of 1999 is mainly represented by minimalism and avant garde. For fall/winter trends, brown color lines make-up comes to mix with romantic image and developed into wine, orange, neon colors in 1995 and 1996. These colors were the symbol of property and sentiment. Gold make-up emphasizing the eye area was the tendency of that period. In 1997, the fear of coming end of century was expressed as decadent image. At that time, ethnic and romantic image appeared with vivid color lines, gold, red and violet. In 1998, romanticism was popular again with modernism and ethnic mood. It expressed the romantic elegant image. The trend has returned to the ecology mood again in 1999. This ecology is somewhat different from the previous ecology. It adds a sofistaiced feeling and sportic fashion. To express natural and sportic image, they choose pink blush. In coming 2000 as a new millennium, the yellow color will be main the stream to express vision, dream, and happiness in both fashion and make-up as an accent color. The minimal design and minimal tools will be used for the design and make-up, respectively. In addition, the fusion concept will dominate the fashion and make-up industry in the globalized and boundariless age. Through this paper, we hope that make-up can be accepted as a part of total fashion in its relationship with other elements such as shoes, clothes and accessory and that it can be considered as a independent art that has direct influence on people and industry.

• The Transactions of the Korea Information Processing Society
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• v.7 no.9
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• pp.3037-3047
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• 2000

This paper describes a method of tracking a close leading vehicle by color image processing using the pairs of tail and brake lights. which emit red light and are housed on the rear of the vehicle in stop-and-go traffic condition. In the color image converted as an HSV color model. candidate regions of rear lights are identified using the color features of a pair of lights. Then. the pair of tailor brake lights are detected by means of the geometrical features and location features for the pattern of the tail and brake lights. The location of the leading vehicle can be estimated by the location of the detected lights and the vehicle can be tracked continuously. It is also possible to detect the braking status of the leading vehicle by measuring the change in HSV color components of the pair of lights detected. In the experiment. this method tracked a leading vehicle successfully from urban road images and was more useful at night than in the daylight. The KAV-Ill (Korea Autonomous Vehicle- Ill) equipped with a color vision system implementing this algorithm was able to follow a leading vehicle autonomously at speeds of up to 15km!h on a paved road at night. This method might be useful for developing an LSA (Low Speed Automation) system that can relieve driver's stress in the stop-and-go traffic conditions encountered on urban roads.

• Cartoon and Animation Studies
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• s.50
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• pp.215-237
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• 2018

I analyze orange that is consistently used, even though not consciously, in the films whose function and meaning are clear. In detail, there are examples of color in films, psychological phenomena of colors expressed in posters and opening titles, color characteristics of clothes and costumes, and semiotic analysis of color names in film titles. (1) Fact and Truth; civilization and criticism. The film tries to tell the truth than the fact. It represents facts as it is, but it presupposes truth. This is a unique characteristic of media films. The truth of the fact is not important. The film tells the truth believing and wanting to show off. The film, which has inherent characteristics of the gap between fact and truth, represents nature and civilization. It carries nature as it is and criticizes the harm of civilization. Orange is nature and civilization. Realistic films such as Hong Sang Soo and Kim Ki Duk, fall into this category. For example, there are A Taxi Driver(2017) and I Can Speak(2017). (2) Virtual History; fake images and memories. In Hollywood SF genres like The Matrix(1999), orange was dealt with virtual reality. However, in Korean films they are replaced by historical dramas. The representation of history becomes a virtual reality. Films such as The Fortress(2017), Masquerade(2012), and Roaring Currents(2014) deal with virtual history. In these films, orange is a fake image and memory. (3) Light=color; Aura. The color and light of orange is aura. At sunrise and sunset, the orange of the incandescent light is almost similar to that of the artificial light. Orange of tungsten makes the real characters surrealistic and mysterious. For example, there are The City of Madness(2016), The Man from Nowhere(2010), and Coinlocker Girl(2014). (4) Fantasy; communication with other worlds. Orange is a sweet fantasy. In our daily life, we go to a supermarket, share a chat with friends in a coffee shop, and spend time in front of a television. Orange makes our life free and dreams. It is the communication between the former being and the other world. This can be found in the sexual fantasy scenes of all genres. For example, there are Sunny(2011), Welcome To Dongmakgol(2005), and 200 Pounds Beauty(2006).

• Cartoon and Animation Studies
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• s.39
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• pp.393-412
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• 2015

See and feel the emotion recognition is the image of a person variously changed according to the environment, personal disposition. Thus, the image recognition has been focused on the emotional sensibilities computer you want to control the number studies. However, existing emotional computing model is numbered and the objective is clearly insufficient measurement conditions. Thus, through quantifiable image Emotion Recognition and emotion computing, is a study of the situation requires an objective assessment scheme. In this paper, the sensitivity was represented by numbered sizes quantified according to the image recognition calculation emotion. So apply the principal attributes of the color image emotion recognition as a configuration parameter. In addition, in calculating the color sensitivity by applying a digital computing focused research. Image color emotion computing research approach is the color of emotion attribute, brightness, and saturation reflects the weighted according to importance to the emotional scores. And free-degree by applying the sensitivity point to the image sensitivity formula (X), the tone (Y-axis) is calculated as a number system. There pleasure degree (X-axis), the tension and position the position of the image point that the sensitivity of the emotional coordinate crossing (Y-axis). Image color coordinates by applying the core emotional effect of Russell (Core Affect) is based on the 16 main representatives emotion. Thus, the image recognition sensitivity and compares the number size. Depending on the magnitude of the sensitivity scores demonstrate this sensitivity must change. Compare the way the images are divided up the top five of emotion recognition emotion emotions associated with 16 representatives, and representatives analyzed the concentrated emotion sizes. Future studies are needed emotional computing method of calculation to be more similar sensibility and human emotion recognition.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.125-135
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• 2009

Owing to its fast computing capability for fusing images, the FIHS(Fast Intensity Hue Saturation) fusion is widely used for fusion purposes. However, the FIHS fusion also distorts color in the same way such as the IHS(Intensity Hue Saturation) fusion technique. In this paper, a FIHS fusion technique(FIHS-BR) which reduces color distortion by using the ratio of each spectral band and an adaptive FIHS fusion(FIHS-SABR) using spatial information and the ratio of each spectral band are proposed. The proposed FIHS-BR fusion reduces color distortion by adding different spatial detail improvement values for each spectral band. The spatial detail improvement values are derived from the ratio of spectral band. And the proposed FIHS-SABR fusion reduces more color distortion by readjusting the spatial detail improvement values for each spectral band according to the ratio of the spectral bands. The spatial detail improvement values are derived adaptively from the characteristics of spatial information of the local image. To evaluate the performance of the proposed FIHS-BR fusion and FIHS-SABR fusion, a computer simulation is performed for IKONOS remote sensing image. Results from the experiments show that the proposed methods have less color distortion for the forest regions which reveal severe color distortion in the traditional FIHS fusion. From the evaluation results of the characteristics of spectral information for fused image, we show that the proposed methods have best results.