• Title/Summary/Keyword: Synthesize Image

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Developing a Scanner for Assessing Foliage Moisture

  • Nakajima, Isao;Ohyama, Futoshi;Juzoji, Hiroshi;Ta, Masuhisa
    • Journal of Multimedia Information System
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    • v.6 no.3
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    • pp.155-164
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    • 2019
  • We intended to confirm that microwave attenuation by tree leaves is strongly linked to water content in leaves. We sampled natural broadleaves, including Japanese cinnamon, and investigated their effects on the microwave (3 to 20 GHz) frequency characteristics using a network analyzer. Experiments determined that microwave attenuation by foliage increases as a linear function of frequency per unit weight (gram). As the frequency increases, the spatial resolution increases, but the phase difference (imaginary component) increases. So we solved the dispersion of phase difference by sweeping the frequency and taking the intermediate value. Based on these experimental results, we developed a microwave scanner on 10Ghz to describe foliage moisture as a image and to enable assessments of leaf condition. Photosynthesis is the process whereby plants synthesize oxygen and sugars from carbon dioxide and water, thereby converting light energy into chemical energy. Since water is a major parameter of photosynthesis, the quantity of water accumulated inside a leaf reflects leaf health. The equipment described here and related microwave technologies will help assess the capacity of leaves to absorb atmospheric carbon dioxide.

Knowledge based Text to Facial Sequence Image System for Interaction of Lecturer and Learner in Cyber Universities (가상대학에서 교수자와 학습자간 상호작용을 위한 지식기반형 문자-얼굴동영상 변환 시스템)

  • Kim, Hyoung-Geun;Park, Chul-Ha
    • The KIPS Transactions:PartB
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    • v.15B no.3
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    • pp.179-188
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    • 2008
  • In this paper, knowledge based text to facial sequence image system for interaction of lecturer and learner in cyber universities is studied. The system is defined by the synthesis of facial sequence image which is synchronized the lip according to the text information based on grammatical characteristic of hangul. For the implementation of the system, the transformation method that the text information is transformed into the phoneme code, the deformation rules of mouse shape which can be changed according to the code of phonemes, and the synthesis method of facial sequence image by using deformation rules of mouse shape are proposed. In the proposed method, all syllables of hangul are represented 10 principal mouse shape and 78 compound mouse shape according to the pronunciation characteristics of the basic consonants and vowels, and the characteristics of the articulation rules, respectively. To synthesize the real time facial sequence image able to realize the PC, the 88 mouth shape stored data base are used without the synthesis of mouse shape in each frame. To verify the validity of the proposed method the various synthesis of facial sequence image transformed from the text information is accomplished, and the system that can be applied the PC is implemented using the proposed method.

A Simulation Study on Image Quality of Virtual Monochromatic Image using Dual-energy Method (이중에너지 방법을 이용한 가상 단색 영상의 화질 시뮬레이션 연구)

  • Son, Ki-Hong;Lee, Soo-Yeul;Kim, Dae-Hong;Chung, Myung-Ae
    • Journal of the Korean Society of Radiology
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    • v.16 no.5
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    • pp.553-558
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    • 2022
  • The purpose of this work was a simulation study to evaluate the virtual monochromatic (VM) image quality of blood vessels compared to the monochromatic image. Dual-energy images were obtained based on the linear attenuation coefficients of five materials at 50 keV and 80 keV at low- and high-energies, respectively. A weighting factor is required to synthesize the VM image, and the liver and bone were used as basis materials to obtain the weighting factor. VM images were synthesized at energies ranging from 30 keV to 100 keV. Image quality was evaluated by Contrast to noise ratio (CNR) and noise by setting calcium and contrast medium as signals and blood as background. According to the results, the energies with the maximum CNR were 50 keV and 60 keV for calcium and contrast medium, respectively. The energies showing the minimum noise were 70 keV, 70 keV, and 60 keV in calcium, iodine contrast medium, and blood, respectively. The VM image can contribute to the improvement of diagnostic performance in CT examination because it can implement an image at the optimal energy that minimize noise and maximize CNR.

Smart Mirror to support Hair Styling (헤어 스타일링 지원 스마트 미러)

  • Noh, Hye-Min;Joo, Hye-Won;Moon, Young-Suk;Kong, Ki-Sok
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.1
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    • pp.127-133
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    • 2020
  • This paper deals with the development of a smart mirror to support changing hair styles. A key function of the service is the ability to synthesize the image into the user's face when the user chooses a desired hair image and virtually styling the hair. To check the effectiveness of the hair image synthesis function, the success rate measurement experiment of Haar-cascade algorithm's facial recognition was conducted. Experiments have confirmed that the facial recognition succeeds with a 95 percent probability, with both eyes and eyebrows visible to the subjects. It is the highest success rate. It confirmed that if either of the eyebrows of the subjects are not visible or one eyeball is covered, the success rate of facial recognition is 50% and 0% respectively.

Mutual Gaze Correction for Videoconferencing using View Morphing (모핑을 이용한 화상회의의 시선 맞춤 보정 방법)

  • Baek, Eu-Tteum;Ho, Yo-Sung
    • Smart Media Journal
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    • v.4 no.1
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    • pp.9-15
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    • 2015
  • Nonverbal communications such as eye gazing, posture, and gestures send forceful messages. In regard to nonverbal communication, eye gazing is one of the most strong forms that an individual can use. However, lack of mutual gazing occurs when we use video conferencing system. The displacement between locations of the eyes and a camera gets in the way of eye contact. The lack of eye gazing can give unapproachable and unpleasant feeling. In this paper, we propose an eye gazing correction for video conferencing. We use two cameras installed at the top and the bottom of the television. The captured two images are rendered with 2D warping at virtual position. We implement view morphing to the detected face, and synthesize the face and the warped image. The result shows that eye gazing is corrected and correctly preserved and the image was synthesized seamlessly.

Feature-Based Disparity Estimation for Intermediate View Reconstruction of Multiview Images (3차원 영상의 중간시점 영상 합성을 위한 특징 기반 변이 추정)

  • 김한성;김성식;손정영;손광훈
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.26 no.11A
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    • pp.1872-1879
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    • 2001
  • As multiview video applications become more popular, correspondence problem for stereo image matching plays an important role in expanding view points. Thus, we propose an efficient dense disparity estimation algorithm considering features of each image pair of multiview image sets. Main concepts of the proposed algorithm are based on the region-dividing-bidirectional-pixel-matching method. This algorithm makes matching process efficient and keeps the reliability of the estimated disparities. Other improvement have obtained by proposed cost function, matching window expanding technique, disparity regularization, and disparity assignment in ambiguous region. These techniques make disparities more stable by removing false disparities and ambiguous regions. The estimated disparities are used to synthesize intermediate views of multiview images. Computer simulation demonstrates the excellence of the proposed algorithm in both subjective and objective evaluations. In addition, processing time is reduced as well.

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Face Image Synthesis using Nonlinear Manifold Learning (비선형 매니폴드 학습을 이용한 얼굴 이미지 합성)

  • 조은옥;김대진;방승양
    • Journal of KIISE:Software and Applications
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    • v.31 no.2
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    • pp.182-188
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    • 2004
  • This paper proposes to synthesize facial images from a few parameters for the pose and the expression of their constituent components. This parameterization makes the representation, storage, and transmission of face images effective. But it is difficult to parameterize facial images because variations of face images show a complicated nonlinear manifold in high-dimensional data space. To tackle this problem, we use an LLE (Locally Linear Embedding) technique for a good representation of face images, where the relationship among face images is preserving well and the projected manifold into the reduced feature space becomes smoother and more continuous. Next, we apply a snake model to estimate face feature values in the reduced feature space that corresponds to a specific pose and/or expression parameter. Finally, a synthetic face image is obtained from an interpolation of several neighboring face images in the vicinity of the estimated feature value. Experimental results show that the proposed method shows a negligible overlapping effect and creates an accurate and consistent synthetic face images with respect to changes of pose and/or expression parameters.

Implementation of Hair Style Recommendation System Based on Big data and Deepfakes (빅데이터와 딥페이크 기반의 헤어스타일 추천 시스템 구현)

  • Tae-Kook Kim
    • Journal of Internet of Things and Convergence
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    • v.9 no.3
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    • pp.13-19
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    • 2023
  • In this paper, we investigated the implementation of a hairstyle recommendation system based on big data and deepfake technology. The proposed hairstyle recommendation system recognizes the facial shapes based on the user's photo (image). Facial shapes are classified into oval, round, and square shapes, and hairstyles that suit each facial shape are synthesized using deepfake technology and provided as videos. Hairstyles are recommended based on big data by applying the latest trends and styles that suit the facial shape. With the image segmentation map and the Motion Supervised Co-Part Segmentation algorithm, it is possible to synthesize elements between images belonging to the same category (such as hair, face, etc.). Next, the synthesized image with the hairstyle and a pre-defined video are applied to the Motion Representations for Articulated Animation algorithm to generate a video animation. The proposed system is expected to be used in various aspects of the beauty industry, including virtual fitting and other related areas. In future research, we plan to study the development of a smart mirror that recommends hairstyles and incorporates features such as Internet of Things (IoT) functionality.

Spine Computed Tomography to Magnetic Resonance Image Synthesis Using Generative Adversarial Networks : A Preliminary Study

  • Lee, Jung Hwan;Han, In Ho;Kim, Dong Hwan;Yu, Seunghan;Lee, In Sook;Song, You Seon;Joo, Seongsu;Jin, Cheng-Bin;Kim, Hakil
    • Journal of Korean Neurosurgical Society
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    • v.63 no.3
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    • pp.386-396
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    • 2020
  • Objective : To generate synthetic spine magnetic resonance (MR) images from spine computed tomography (CT) using generative adversarial networks (GANs), as well as to determine the similarities between synthesized and real MR images. Methods : GANs were trained to transform spine CT image slices into spine magnetic resonance T2 weighted (MRT2) axial image slices by combining adversarial loss and voxel-wise loss. Experiments were performed using 280 pairs of lumbar spine CT scans and MRT2 images. The MRT2 images were then synthesized from 15 other spine CT scans. To evaluate whether the synthetic MR images were realistic, two radiologists, two spine surgeons, and two residents blindly classified the real and synthetic MRT2 images. Two experienced radiologists then evaluated the similarities between subdivisions of the real and synthetic MRT2 images. Quantitative analysis of the synthetic MRT2 images was performed using the mean absolute error (MAE) and peak signal-to-noise ratio (PSNR). Results : The mean overall similarity of the synthetic MRT2 images evaluated by radiologists was 80.2%. In the blind classification of the real MRT2 images, the failure rate ranged from 0% to 40%. The MAE value of each image ranged from 13.75 to 34.24 pixels (mean, 21.19 pixels), and the PSNR of each image ranged from 61.96 to 68.16 dB (mean, 64.92 dB). Conclusion : This was the first study to apply GANs to synthesize spine MR images from CT images. Despite the small dataset of 280 pairs, the synthetic MR images were relatively well implemented. Synthesis of medical images using GANs is a new paradigm of artificial intelligence application in medical imaging. We expect that synthesis of MR images from spine CT images using GANs will improve the diagnostic usefulness of CT. To better inform the clinical applications of this technique, further studies are needed involving a large dataset, a variety of pathologies, and other MR sequence of the lumbar spine.

Scenario-based 3D Objects Synthesizing System Design

  • Nam, Ji-Seung;Gao, Hui;Kang, Mi-Young;Kim, Kyoung-Tae;Son, Seung-Chul;Pom, Chung-Ung;Heo, Kwon
    • Journal of Information Processing Systems
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    • v.2 no.1
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    • pp.18-22
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    • 2006
  • This paper proposes the framework of the scenario-based 3D image synthesizing system that allows common users who envision a scenario in their mind to realize it into the segments of cool animation. We focused on utilization of the existing motions to synthesize new motions for the objects. The framework is useful to build a 3D animation in game programming with a limited set of 3D objects. We also propose a practical algorithm to reuse and expand the objects. This algorithm is based on motion path modification rules. Both linear and nonlinear curve-fitting algorithms were applied to modify an animation by key frame interpolation and to make the motion appear realistic.