• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1794-1806
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• 2023

This study presents a method for capturing photographs of users as input and converting them into 2D character animation sprites using a generative adversarial network-based artificial intelligence network. Traditionally, 2D character animations have been created by manually creating an entire sequence of sprite images, which incurs high development costs. To address this issue, this study proposes a technique that combines motion videos and sample 2D images. In the 2D sprite generation process that uses the proposed technique, a sequence of images is extracted from real-life images captured by the user, and these are combined with character images from within the game. Our research aims to leverage cutting-edge deep learning-based image manipulation techniques, such as the GAN-based motion transfer network (impersonator) and background noise removal (U² -Net), to generate a sequence of animation sprites from a single image. The proposed technique enables the creation of diverse animations and motions just one image. By utilizing these advancements, we focus on enhancing productivity in the game and animation industry through improved efficiency and streamlined production processes. By employing state-of-the-art techniques, our research enables the generation of 2D sprite images with various motions, offering significant potential for boosting productivity and creativity in the industry.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.19-26
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• 2021

Cultural assets excavated in historical areas have their own characteristics based on the background of the times, and it can be seen that their patterns and characteristics change little by little according to the history and the flow of the spreading area. Cultural properties excavated in some areas represent the culture of the time and some maintain their intact appearance, but most of them are damaged/lost or divided into parts, and many experts are mobilized to research the composition and repair the damaged parts. The purpose of this research is to learn patterns and characteristics of the past through artificial intelligence neural networks for such restoration research, and to restore the lost parts of the excavated cultural assets based on Generative Adversarial Network(GAN)[1]. The research is a process in which the rest of the damaged/lost parts are restored based on some of the cultural assets excavated based on the GAN. To recover some parts of dammed of cultural asset, through training with the 2D image of a complete cultural asset. This research is focused on how much recovered not only damaged parts but also reproduce colors and materials. Finally, through adopted this trained neural network to real damaged cultural, confirmed area of recovered area and limitation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.363-373
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• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.

• Smart Media Journal
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• v.10 no.2
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• pp.30-37
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• 2021

Recently, 3D contents used in various fields have been attracting people's attention due to the development of virtual reality and augmented reality technology. In order to produce 3D contents, it is necessary to model the objects as vertices. However, high-quality modeling is time-consuming and costly. In order to convert a 2D character into a 3D model, it is necessary to express it as line drawings through feature line extraction. The extraction of consistent line drawings from 2D cartoon cartoons is difficult because the styles and techniques differ depending on the designer who produces them. Therefore, it is necessary to extract the line drawings that show the geometrical characteristics well in 2D cartoon shapes of various styles. This study proposes a method of automatically extracting line drawings. The 2D Cartoon shading image and line drawings are learned by using adversarial network model, which is artificial intelligence technology and outputs 2D cartoon artwork of various styles. Experimental results show the proposed method in this research can be obtained as a result of the line drawings representing the geometric characteristics when a 2D cartoon painting as input.

• Imaging Science in Dentistry
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• v.52 no.4
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• pp.393-398
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• 2022

Purpose: This study proposed a generative adversarial network (GAN) model for T2-weighted image (WI) synthesis from proton density (PD)-WI in a temporomandibular joint(TMJ) magnetic resonance imaging (MRI) protocol. Materials and Methods: From January to November 2019, MRI scans for TMJ were reviewed and 308 imaging sets were collected. For training, 277 pairs of PD- and T2-WI sagittal TMJ images were used. Transfer learning of the pix2pix GAN model was utilized to generate T2-WI from PD-WI. Model performance was evaluated with the structural similarity index map (SSIM) and peak signal-to-noise ratio (PSNR) indices for 31 predicted T2-WI (pT2). The disc position was clinically diagnosed as anterior disc displacement with or without reduction, and joint effusion as present or absent. The true T2-WI-based diagnosis was regarded as the gold standard, to which pT2-based diagnoses were compared using Cohen's ĸ coefficient. Results: The mean SSIM and PSNR values were 0.4781(±0.0522) and 21.30(±1.51) dB, respectively. The pT2 protocol showed almost perfect agreement(ĸ=0.81) with the gold standard for disc position. The number of discordant cases was higher for normal disc position (17%) than for anterior displacement with reduction (2%) or without reduction (10%). The effusion diagnosis also showed almost perfect agreement(ĸ=0.88), with higher concordance for the presence (85%) than for the absence (77%) of effusion. Conclusion: The application of pT2 images for a TMJ MRI protocol useful for diagnosis, although the image quality of pT2 was not fully satisfactory. Further research is expected to enhance pT2 quality.

• Journal of architectural history
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• v.14 no.1 s.41
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• pp.71-87
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• 2005

4 royal palaces are currently remained from capital city (Seoul) of 'Cho-Sun(朝鮮)' period. In these palaces, 'Main hall of Royal Palace(正殿)' is the center of the Royal Palaces. The 'Main hall of Royal Palace' of the Royal Palace was the best building of that time. Therefore there were many studies about the 'Main hall of Royal Palace'. But these studies were individual studies of these 'Main hall of Royal Palace'. Therefore, this study is to analyze and compare 4 'Main hall of Royal Palace' of the Royal palaces. It is to study the proportion regarding the Diameter of the pillar, the Height, the pillar and pillar Interval's Distance, and the arrangement of 'Kong-Po(bracket sets)'. With these studies, it is to prove that the 'Main hall of Royal Palace' is the building which high construction technique of this time is expressed. Result of this study is as followings; First, the proportion of pillar height(H) to its diameter(D) average from H=8.0 to 8.5D. Only the Myeong-Jeong-Jeon omitted the 'Go-Ju(高柱)' in the 'Toi-Kan (退間)' to place Ea-Jwa(御座). Second, Second, the proportion of diameter of the pillar of 'Eoi-Bu-Pyeong-Ju(外部平柱)' and 'Nae-Jin-Go-Ju(內陣高柱)' average D1(Diameter of 'Eoi-Bu-Pyeong-Ju') =0.91D2 (Diameter of 'Nae-Jin-Go-Ju'). In regards to the height, the single floor 'Main hall of Royal Palace' and double floor 'Main hall of Royal Palace' seems to be different. The height proportion of the double floor 'Main hall of royal palace' is H1(Height of 'Eoi-Bu-Pyeong-Ju')=0.34H2(Height of 'Nae-Jin-Go-Ju') and single floor 'Main hall of Royal Palace' has a proportion of H1=0.62H2. Third, in Geun-Jeong-Jeon, with the proportion of height and diameter of the pillar, interval's distance between pillars and diameter, the pillar interval distance and height, of 'Ea-kan(御間)' from the 'Toi-Kan' is different from 'Main hall of Royal Palace'. This is because the structure of 'Toi-Kan' of Geun-Jeong-Jeon is not stable. In order to reinforce this, 'Gui-Go-Ju(隅高柱)' of the Geun-Jeong-Jeon jut out $4{\sim}7%$ more compared to In-Jeong-Jeon. Fourth, when comparing double floor 'Main hall of royal palace' of Geun-Jeong-Jeon and In-Jeong-Jeon, based on distance of 'Eoi-Bu-Pyeong-Ju' and 'Nae-Jin-Go-Ju' of lower level, the 'Sang-Bu-Pyeong-Ju(上部平柱)' of Geun-Jeong-Jeon jut out $4{\sim}7%$ more compared to the In-Jeong-Jeon and also It becomes thicker. Fifth, the arrangement of 'Kong-Po' on the front row of 'Gan(間)' had to do with the change of side 'Gan'. Even though the Geun-Jeong-Jeon and the In-Jeong-Jeon were double floors, the arrangement of the 'Kong-Po' is different because the number of side bay is different.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.6
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• pp.25-34
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• 2019

VTON (Virtual try-on) is a key technology that can activate the online commerce of fashion items. However, the early 3D graphics-based methods require the 3D information of the clothing or the human body, which is difficult to secure realistically. In order to overcome this problem, Image-based deep-learning algorithms such as VITON (Virtual image try-on) and CP-VTON (Characteristic preserving-virtual try-on) has been published, but only a sampled results on performance is presented. In order to examine the strength and weakness for their commercialization, the performance analysis is needed according to the complexity of the clothes, the object posture and body shape, and the degree of occlusion of the clothes. In this paper, IoU and SSIM were evaluated for the performance of transformation and synthesis stages, together with non-DL SCM based method. As a result, CP-VTON shows the best performance, but its performance varies significantly according to posture and complexity of clothes. The reasons for this were attributed to the limitations of secondary geometric deformation and the limitations of the synthesis technology through GAN.

• Corrosion Science and Technology
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• v.11 no.1
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• pp.9-14
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• 2012

The formation of the Fe-Al inhibition layer in hot-dip galvanizing is a confusing issue for a long time. This study presents a characterization result on the inhibition layer formed on C-Mn-Cr and C-Mn-Si dual-phase steels after a short time galvanizing. The samples were annealed at $800^{\circ}C$ for 60 s in $N_{2}$-10% $H_{2}$ atmosphere with a dew point of $-30^{\circ}C$, and were then galvanized in a bath containing 0.2 %Al. X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) was employed for characterization. The TEM electron diffraction shows that only $Fe_{2}Al_{5}$ intermetallic phase was formed. No orientation relationship between the $Fe_{2}Al_{5}$ phase and the steel substrate could be identified. Two peaks of Al 2p photoelectrons, one from metallic aluminum and the other from $Al^{3+}$ ions, were detected in the inhibition layer, indicating that the layer is in fact a mixture of $Fe_{2}Al_{5}$ and $Al_{2}O_{3}$. TEM/EDS analysis verifies the existence of $Al_{2}O_{3}$ in the boundaries of $Fe_{2}Al_{5}$ grains. The nucleation of $Fe_{2}Al_{5}$ and the reduction of the surface oxide probably proceeded concurrently on galvanizing, and the residual oxides prohibited the heteroepitaxial growth of $Fe_{2}Al_{5}$.

• Proceedings of the Acoustical Society of Korea Conference
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• 1985.10a
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• pp.68-71
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• 1985

In this paper, Sentence-Sip E Il Ka Gi Seo U1 E Gan Da was spoken by 4 men and 3 see sound is used for the experiment. A/D conversion time is 30 sec. Data are obtained using the microcomputer and compressed by ADPCM Rate of compression is 1/8. Data compressed by ADPCM are synthesized and compared to the original sound. Rate of speech identification is analysed using the sound pressure, white noise. Coding of ADPCM is done for 5bit. As the result of fixing starting voltage by 2.6V. It is acertained that variable value increases in initial speech signal and then process is made by minimum value "3". From the result of processing, synthesized sound is almost eaual to original sound. Minimum values cause distorition, Dummy Head System is used in this experiment.xperiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6C
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• pp.384-390
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• 2011

The paper derives formulas for the mean-squared error distortion and resulting signal-to-noise (SNR) ratio of a fixed-rate scalar quantizer designed optimally in the minimum mean-squared error sense for a Gaussian density with the standard deviation ${\sigma}_q$ when it is mismatched to a Laplacian density with the standard deviation ${\sigma}_q$. The SNR formulas, based on the key parameter and Bennett's integral, are found accurate for a wide range of $p\({\equiv}\frac{\sigma_p}{\sigma_q}\){\geqq}0.25$. Also an upper bound to the SNR is derived, which becomes tighter with increasing rate R and indicates that the SNR behaves asymptotically as $\frac{20\sqrt{3{\ln}2}}{{\rho}{\ln}10}\;{\sqrt{R}}$ dB.