• Title/Summary/Keyword: character image

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A Study on Character Design Using [Midjourney] Application

  • Chen Xi;Jeanhun Chung
    • International Journal of Advanced Culture Technology
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    • v.11 no.2
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    • pp.409-414
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    • 2023
  • In recent years, the emergence of a number of AI image generation software represented by [Midjourney] has brought great impetus to the development of the field of AI-assisted art creation. Compared with the traditional hand-painted digital painting with the aid of electronic equipment, broke the traditional sense of animation character creation logic.This paper analyzes the application of AI technology in the field of animation character design through the practice of two-dimensional animation character . This is having a significant impact on the productivity and innovation of animation design and character modeling. The key results of the analysis indicate that AI technology, particularly through the utilization of "Midjourney,"enables the automation of certain design tasks, provides innovative approaches, and generates visually appealing and realistic characters. In conclusion, the integration of AI technology, specifically the application of "Midjourney," brings a new dimension to animation character design. The utilization of AI image generation software facilitates streamlined workflows, sparks creativity, and improves the overall quality of animated characters. As the animation industry continues to evolve, AI-assisted tools like "Midjourney" hold great potential for further advancement and innovation.

Lour-Quality Printed Character Recognition Considering of image Blurredness (찌그러짐을 고려한 저품질 인쇄체 문자인식)

  • 김성원;김형원;양윤모
    • Proceedings of the IEEK Conference
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    • 2000.11d
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    • pp.219-222
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    • 2000
  • Character recognition has already been studied in a lot of fields. But, if input-characters have noise in practical application system, the ability decreases markedly. Special consideration should be taken into account in the recognition of blurred data. This paper proposes low-quality printed character recognition methods that extracts blurred parts of the character image, deletes them and carry out accurate character recognition.

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Slant Correction and Character String Segmentation using Vertical Transition (수직 천이점 검출을 통한 인쇄체 우편 영상에서의 회전각 보정 및 문자열 추출)

  • 이재용;오현화;장승익;진성일
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.469-472
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    • 2003
  • Skew is inevitably occurred in a scanned document image Thus, character recognition systems are generally very sensitive to a skew angle. In this paper, we propose a robust slant correction algorithm based on dithering and estimating vortical transition. Character strings are segmented by projecting the vertical transition point and the slant corrected image. The segmentation method using the vertical transition point can effectively split the character strings touching vertically each other. Experimental results show that the proposed method has achieved robust slant correction and good performance of character string segmentation.

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Facial Feature Based Image-to-Image Translation Method

  • Kang, Shinjin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.12
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    • pp.4835-4848
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    • 2020
  • The recent expansion of the digital content market is increasing the technical demand for various facial image transformations within the virtual environment. The recent image translation technology enables changes between various domains. However, current image-to-image translation techniques do not provide stable performance through unsupervised learning, especially for shape learning in the face transition field. This is because the face is a highly sensitive feature, and the quality of the resulting image is significantly affected, especially if the transitions in the eyes, nose, and mouth are not effectively performed. We herein propose a new unsupervised method that can transform an in-wild face image into another face style through radical transformation. Specifically, the proposed method applies two face-specific feature loss functions for a generative adversarial network. The proposed technique shows that stable domain conversion to other domains is possible while maintaining the image characteristics in the eyes, nose, and mouth.

A Study on the Romantic Image in Modern Fashion (현대패션의 로맨틱 이미지에 관한 연구)

  • Kim Young-Hyun;Yang Chieu-Kyung
    • Journal of the Korean Society of Costume
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    • v.55 no.1 s.91
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    • pp.1-12
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    • 2005
  • The modern society which is going through the big turbulence of civilization experiences the lost of humanity and the phenomenon that the standard of our thoughts, like those for good and evil, truth and false is not clear anymore as the technology is being improved. This makes us miss the past when everything is simple and the standards are very clear and being attracted by the metaphorical culture symbolizing something from the past, like memories of youth, fantasies, fairy tales or myths and we are now having a great interest in the joy of life and the affluent life. Influenced by this kind of tendency in modern society, the minimalism, which had the great influence in the nineties, went out of fashion and at last the romantic susceptibility seems to be the trend forming the major mood of the late 20th century - the early 21st century. This study focus is: (1) the theoretical aspects of romantic images such as the concept, the historical tendency and the character are considered. (2) the variety and multiplicity of the romantic images is discussed after the romantic image is classified into four types of retro character, natural character, ethnic character, erotic character according to major trends in our modern. The purpose of this study is to understand the romantic images in modern fashion, by analyzing the fashion trends together with the various features of romantic images.

Few-Shot Image Synthesis using Noise-Based Deep Conditional Generative Adversarial Nets

  • Msiska, Finlyson Mwadambo;Hassan, Ammar Ul;Choi, Jaeyoung;Yoo, Jaewon
    • Smart Media Journal
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    • v.10 no.1
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    • pp.79-87
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    • 2021
  • In recent years research on automatic font generation with machine learning mainly focus on using transformation-based methods, in comparison, generative model-based methods of font generation have received less attention. Transformation-based methods learn a mapping of the transformations from an existing input to a target. This makes them ambiguous because in some cases a single input reference may correspond to multiple possible outputs. In this work, we focus on font generation using the generative model-based methods which learn the buildup of the characters from noise-to-image. We propose a novel way to train a conditional generative deep neural model so that we can achieve font style control on the generated font images. Our research demonstrates how to generate new font images conditioned on both character class labels and character style labels when using the generative model-based methods. We achieve this by introducing a modified generator network which is given inputs noise, character class, and style, which help us to calculate losses separately for the character class labels and character style labels. We show that adding the character style vector on top of the character class vector separately gives the model rich information about the font and enables us to explicitly specify not only the character class but also the character style that we want the model to generate.

Character Recognition Algorithm in Low-Quality Legacy Contents Based on Alternative End-to-End Learning (대안적 통째학습 기반 저품질 레거시 콘텐츠에서의 문자 인식 알고리즘)

  • Lee, Sung-Jin;Yun, Jun-Seok;Park, Seon-hoo;Yoo, Seok Bong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.11
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    • pp.1486-1494
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    • 2021
  • Character recognition is a technology required in various platforms, such as smart parking and text to speech, and many studies are being conducted to improve its performance through new attempts. However, with low-quality image used for character recognition, a difference in resolution of the training image and test image for character recognition occurs, resulting in poor accuracy. To solve this problem, this paper designed an end-to-end learning neural network that combines image super-resolution and character recognition so that the character recognition model performance is robust against various quality data, and implemented an alternative whole learning algorithm to learn the whole neural network. An alternative end-to-end learning and recognition performance test was conducted using the license plate image among various text images, and the effectiveness of the proposed algorithm was verified with the performance test.

CGS System based on Three-Dimensional Character Modeling I (Part1:About Non-Digital Process) (3차원 캐릭터 모델기반 CGS System 구축 I (Part1:Non-Digital Process에 관하여))

  • Cho, Dong-Min
    • Journal of Korea Multimedia Society
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    • v.11 no.11
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    • pp.1592-1600
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    • 2008
  • This study is to help creative idea generation based on the theory of the 'reconstruction of character shape image elements', and aims to extrusion of creative and diverse shapes with combination of image elements upon computing creative image generation. In order to suggest the design generation methodology for the maximization of idea generation ability and to overcome restriction of thinking out of existing idea generation methodology, it has suggested the CGS(Character Generation System) that is a creative idea generation methodology identified and complemented the problem of the existing computerized idea generation(PDS with Proportion) method out of the preceded studies on the creative idea generation methodologies. this study is expected to have effectives as one method for idea generation or creative image generation assistance during the 3D character development process, and to serve as an assistance to overcome the restriction of the character shape image generation through diverse idea generations.

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Character Region Detection in Natural Image Using Edge and Connected Component by Morphological Reconstruction (에지 및 형태학적 재구성에 의한 연결요소를 이용한 자연영상의 문자영역 검출)

  • Gwon, Gyo-Hyeon;Park, Jong-Cheon;Jun, Byoung-Min
    • Journal of Korea Entertainment Industry Association
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    • v.5 no.1
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    • pp.127-133
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    • 2011
  • Characters in natural image are an important information with various context. Previous work of character region detection algorithms is not detect of character region in case of image complexity and the surrounding lighting, similar background to character, so this paper propose an method of character region detection in natural image using edge and connected component by morphological reconstructions. Firstly, we detect edge using Canny-edge detector and connected component with local min/max value by morphological reconstructed-operation in gray-scale image, and labeling each of detected connected component elements. lastly, detected candidate of text regions was merged for generation for one candidate text region, Final text region detected by checking the similarity and adjacency of neighbor of text candidate individual character. As the results of experiments, proposed algorithm improved the correctness of character regions detection using edge and connected components.

A Study on Character Consistency Generated in [Midjourney V6] Technology

  • Xi Chen;Jeanhun Chung
    • International journal of advanced smart convergence
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    • v.13 no.2
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    • pp.142-147
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    • 2024
  • The emergence of programs like Midjourney, particularly known for its text-to-image capability, has significantly impacted design and creative industries. Midjourney continually updates its database and algorithms to enhance user experience, with a focus on character consistency. This paper's examination of the latest V6 version of Midjourney reveals notable advancements in its characteristics and design principles, especially in the realm of character generation. By comparing V6 with its predecessors, this study underscores the significant strides made in ensuring consistent character portrayal across different plots and timelines.Such improvements in AI-driven character consistency are pivotal for storytelling. They ensure coherent and reliable character representation, which is essential for narrative clarity, emotional resonance, and overall effectiveness. This coherence supports a more immersive and engaging storytelling experience, fostering deeper audience connection and enhancing creative expression.The findings of this study encourage further exploration of Midjourney's capabilities for artistic innovation. By leveraging its advanced character consistency, creators can push the boundaries of storytelling, leading to new and exciting developments in the fusion of technology and art.