• Title/Summary/Keyword: Image generation

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Research on AI Painting Generation Technology Based on the [Stable Diffusion]

  • Chenghao Wang;Jeanhun Chung
    • International journal of advanced smart convergence
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    • v.12 no.2
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    • pp.90-95
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    • 2023
  • With the rapid development of deep learning and artificial intelligence, generative models have achieved remarkable success in the field of image generation. By combining the stable diffusion method with Web UI technology, a novel solution is provided for the application of AI painting generation. The application prospects of this technology are very broad and can be applied to multiple fields, such as digital art, concept design, game development, and more. Furthermore, the platform based on Web UI facilitates user operations, making the technology more easily applicable to practical scenarios. This paper introduces the basic principles of Stable Diffusion Web UI technology. This technique utilizes the stability of diffusion processes to improve the output quality of generative models. By gradually introducing noise during the generation process, the model can generate smoother and more coherent images. Additionally, the analysis of different model types and applications within Stable Diffusion Web UI provides creators with a more comprehensive understanding, offering valuable insights for fields such as artistic creation and design.

A Study on the Clothing Culture for New Generation of Korea and Japan (2002 한.일 국민교류년 기념' 한국과 일본의 신세대의 복식업화에 대한 연구 - Street Fashion을 중심으로 -)

  • 백샘이;간호섭
    • Journal of the Korean Society of Costume
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    • v.53 no.3
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    • pp.31-49
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    • 2003
  • The Purpose of this research is to examine and contrast the cultural characteristics of the street fashion in new generations of Korea and Japan. We also intended to help clothing companies understand the current trend in this new generation. As the method for street fashion analysis. various literature, internet information and new media materials were utilized. Key observations obtained are as following First, they pursue a complex image. New generations seem to admix images from different areas to create a synthetic image, rather than adopting a single image; Second, practicality is an important factor. They Pursue a sense of their own unique trend: Third, distinction. The difference in society values between Koreans and Japanese is incorporated. The Korean new generation considers the traditional moral principles as important social values. In contrast the Japanese new generation is greatly influenced by the open sexuality culture ; Fourth. public ownership and sharing of the culture. There is a gradual deviation from a dominating unidirectional influence from one country on another. Now the two countries are influencing each other ; Fifth, sense. There are numerous fashion items and generalized total coordination. New generations express more active and creative fashion sense in those fashion items.

A Study of Background Edge Generation for Moving Object Detection under Moving Camera (이동카메라에서 이동물체 감지를 위한 배경에지 생성에 관한 연구)

  • Lee, June-Hyung;Chae, Ok-Sam
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.6 s.44
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    • pp.151-156
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    • 2006
  • This paper presents an background edge generation based automatic algorithm for detection of moving objects under moving camera. Background image is generated by rotating the fixed the camera on the tripod horizontally, aligning and reorganizing this images. We develop an efficient approach for robust panoramic background edge generation as well as method of edge matching between input image and background image. We applied the proposed algorithm to real image sequences. The proposed method can be successfully realized in various monitoring systems like intrusion detection as well as video surveillance.

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Development of car driving trainer under PC environment (PC 기반형 자동차 운전 연습기 개발)

  • Lee, Seung-Ho;Kim, Sung-Duck
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.4
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    • pp.415-421
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    • 1997
  • A car driving trainer for beginners developed under PC-based environment is described in this paper. For this trainer, a hardware is implemented as a practice car, and a trainer program is designed by computer image generation method to display 3-dimensional images on a CRT monitor. The trainer program consists of 3 main parts, that is, a speed estimate part, a wheel trace calculation part and a driving image generation part. Furthermore, a map editor is also installed for taking any test drive. After comparing this driving trainer to specify it was verified that the developed car driving trainer showed has good performances, such as lower cost, higher resolution and better image display speed.

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The Surface Information Acquisition of Rock Slope using 3D Digital Image (3차원 수치영상을 이용한 암반사면의 지표정보 획득)

  • 엄대용;강준묵
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2004.04a
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    • pp.203-208
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    • 2004
  • Recently, digital image is increasing greatly practical use degree in several industry fields including construction. And interest about 3D digital image that can express practical object realistically is augmented greatly. In this study, developed 3D digital image generation system based on digital photogrammetry and created 3D digital image for object. And, wished to verify of 3D digital image through comparative analysis with processing result by digital photogrammetry system been using much the latest for acquisition of 3D information. Also, wished to apply to surface information acquisition about rock slope and execute investigation about discontinuity of joint etc. As the result, could created 3D digital image for object using the 3D digital image generation system developing in this study, and acquire surface information about rock slope efficiently.

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Depth Map Generation Algorithm from Single Defocused Image (흐린 초점의 단일영상에서 깊이맵 생성 알고리즘)

  • Lee, Yong-Hwan;Kim, Youngseop
    • Journal of the Semiconductor & Display Technology
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    • v.15 no.3
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    • pp.67-71
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    • 2016
  • This paper addresses a problem of defocus map recovery from single image. We describe a simple effective approach to estimate the spatial value of defocus blur at the edge location of the image. At first, we perform a re-blurring process using Gaussian function with input image, and calculate a gradient magnitude ratio with blurring amount between input image and re-blurred image. Then we get a full defocus map by propagating the blur amount at the edge location. Experimental result reveals that our method outperforms a reliable estimation of depth map, and shows that our algorithm is robust to noise, inaccurate edge location and interferences of neighboring edges within input image.

A Study on the Stereo Image Map Generation of Chuncheon Area using Satellite Overlay Images (위성영상을 이용한 춘천지역의 3차원 입체영상지도 생성에 관한 연구)

  • Yeon, Sang-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.3 no.4
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    • pp.1-10
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    • 2000
  • Satellite remote sensing images have much more information compared to a paper map. But these images are generally handled as particular image format gained from optical sensor, and must be processed and analyzed by computer with high priced digital image processing system. For the extraction of digital elevation model(DEM) from satellite image, we used the overlay image by SPOT-3 of Chuncheon area at the Kangwon province. According to the image condition, the precious geometric correction, the bundle adjustment for ortho-image generation and the stereo image mapping by several technical approaches were processed. So that we developed the methods of automatic DEM extraction and efficient stereo image map generation which can improve the digital image processing steps. Also, we applied the multiple direction birdeye view image for modeling and analysis using the remotely sensed overlay images with high resolution.

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Image Generation Method for Malware Detection Based on Machine Learning (기계학습 기반 악성코드 검출을 위한 이미지 생성 방법)

  • Jeon, YeJin;Kim, Jin-e;Ahn, Joonseon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.2
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    • pp.381-390
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    • 2022
  • Many attempts have been made to apply image recognition based on machine learning which has recently advanced dramatically to malware detection. They convert executable files to images and train deep learning networks like CNN to recognize or categorize dangerous executable files, which shows promising results. In this study, we are looking for an effective image generation method that may be used to identify malware using machine learning. To that end, we experiment and assess the effectiveness of various image generation methods in relation to malware detection. Then, we suggest a linear image creation method which represents control flow more clearly and our experiment shows our method can result in better precision in malware detection.

A Research on 3D Texture Production Using Artificial Intelligence Softwear

  • Ke Ma;Jeanhun Chung
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.4
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    • pp.178-184
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    • 2023
  • AI image generation technology has become a popular research direction in the field of AI, which is widely used in the field of digital art and conceptual design, and can also be used in the process of 3D texture mapping. This paper introduces the production process of 3D texture mapping using AI image technology, and discusses whether it can be used as a new way of 3D texture mapping to enrich the 3D texture mapping production process. Two AI deep learning models, Stable Diffusion and Midjourney, were combined to generate high-quality AI textures. Finally, the lmage to material function of substance 3D Sampler was used to convert the AI-generated textures into PBR 3D texture maps. And applied in 3D environment. This study shows that 3D texture maps generated by AI image generation technology can be used in 3D environment, which not only has short production time and high production efficiency, but also has rich changes in map styles, which can be quickly adjusted and modified according to the design scheme. However, some AI texture maps need to be manually modified before they can be used. With the continuous development of AI technology, there will be great potential for further development and innovation of AI-generated image technology in the 3D content production process in the future.

Omni-directional Image Generation Algorithm with Parametric Image Compensation (변수화된 영상 보정을 통한 전방향 영상 생성 방법)

  • Kim, Yu-Na;Sim, Dong-Gyu
    • Journal of Broadcast Engineering
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    • v.11 no.4 s.33
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    • pp.396-406
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    • 2006
  • This paper proposes an omni-directional image generation algorithm with parametric image compensation. The algorithm generates an omni-directional image by transforming each planar image to the spherical image on spherical coordinate. Parametric image compensation method is presented in order to compensate vignetting and illumination distortions caused by properties of a camera system and lighting condition. The proposed algorithm can generates realistic and seamless omni-directional video and synthesize any point of view from the stitched omni-directional image on the spherical image. Experimental results show that the proposed omni-directional system with vignetting and illumination compensation is approximately $1{\sim}4dB$ better than that which does not consider the said effects.