• Title/Summary/Keyword: Image synthesis

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Boundary Noise Removal and Hole Filling Algorithm for Virtual Viewpoint Image Generation (가상시점 영상 생성을 위한 경계 잡음 제거와 홀 채움 기법)

  • Ko, Min-Soo;Yoo, Ji-Sang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.8A
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    • pp.679-688
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    • 2012
  • In this paper, performance improved hole-filling algorithm including boundary noise removing pre-process which can be used for an arbitrary view synthesis with given two views is proposed. Boundary noise usually occurs because of the boundary mismatch between the reference image and depth map and common-hole is defined as the occluded region. These boundary noise and common-hole created while synthesizing a virtual view result in some defects and they are usually very difficult to be completely recovered by using only given two images as references. The spiral weighted average algorithm gives a clear boundary of each object by using depth information and the gradient searching algorithm is able to preserve details. In this paper, we combine these two algorithms by using a weighting factor ${\alpha}$ to reflect the strong point of each algorithm effectively in the virtual view synthesis process. The experimental results show that the proposed algorithm performs much better than conventional algorithms.

Implementation of a Deep Learning based Realtime Fire Alarm System using a Data Augmentation (데이터 증강 학습 이용한 딥러닝 기반 실시간 화재경보 시스템 구현)

  • Kim, Chi-young;Lee, Hyeon-Su;Lee, Kwang-yeob
    • Journal of IKEEE
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    • v.26 no.3
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    • pp.468-474
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    • 2022
  • In this paper, we propose a method to implement a real-time fire alarm system using deep learning. The deep learning image dataset for fire alarms acquired 1,500 sheets through the Internet. If various images acquired in a daily environment are learned as they are, there is a disadvantage that the learning accuracy is not high. In this paper, we propose a fire image data expansion method to improve learning accuracy. The data augmentation method learned a total of 2,100 sheets by adding 600 pieces of learning data using brightness control, blurring, and flame photo synthesis. The expanded data using the flame image synthesis method had a great influence on the accuracy improvement. A real-time fire detection system is a system that detects fires by applying deep learning to image data and transmits notifications to users. An app was developed to detect fires by analyzing images in real time using a model custom-learned from the YOLO V4 TINY model suitable for the Edge AI system and to inform users of the results. Approximately 10% accuracy improvement can be obtained compared to conventional methods when using the proposed data.

Improvement of Maskless Photolithography of Bio Pattern with Single Crystalline Silicon Micromirror Array

  • Jang, Yun-Ho;Lee, Kook-Nyung;Park, Jae-Hyoung;Shin, Dong-Sik;Lee, Yoon-Sik;Kim, Yong-Kweon
    • Journal of Electrical Engineering and Technology
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    • v.2 no.2
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    • pp.274-279
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    • 2007
  • This study focuses on the enhancement of maskless photolithography as well as the peptide synthesis application with single crystalline silicon micromirrors. A single crystalline silicon micromirror array has been designed and fabricated in order to improve its application to the peptide synthesis. A micromirror rotates about ${\pm}\;9^{\circ}$ at the pull-in voltage, which can range from 90.7 V to 115.1 V. A $210\;{\mu}m-by-210\;{\mu}m$ micromirror device with $270\;{\mu}m$ mirror pitch meets the requirements of an adequately precise separation for peptide synthesis. Synthetic 16 by 16 peptide array corresponds to the same number of micromirrors. The large size of peptide pattern and the separation facilitate biochip experiments using fluorescence assay. The peptide pattern has been synthesized on the GPTS-PEG200 surface with BSA-blocking and thereupon the background was acetylated to reject non-specific bindings. Hence, an averaged slope at the pattern edge has been distinguishably improved in comparison to patterning results from an aluminum micromirror.

Voxel-wise UV parameterization and view-dependent texture synthesis for immersive rendering of truncated signed distance field scene model

  • Kim, Soowoong;Kang, Jungwon
    • ETRI Journal
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    • v.44 no.1
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    • pp.51-61
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    • 2022
  • In this paper, we introduced a novel voxel-wise UV parameterization and view-dependent texture synthesis for the immersive rendering of a truncated signed distance field (TSDF) scene model. The proposed UV parameterization delegates a precomputed UV map to each voxel using the UV map lookup table and consequently, enabling efficient and high-quality texture mapping without a complex process. By leveraging the convenient UV parameterization, our view-dependent texture synthesis method extracts a set of local texture maps for each voxel from the multiview color images and separates them into a single view-independent diffuse map and a set of weight coefficients for an orthogonal specular map basis. Furthermore, the view-dependent specular maps for an arbitrary view are estimated by combining the specular weights of each source view using the location of the arbitrary and source viewpoints to generate the view-dependent textures for arbitrary views. The experimental results demonstrate that the proposed method effectively synthesizes texture for an arbitrary view, thereby enabling the visualization of view-dependent effects, such as specularity and mirror reflection.

Efficient Layered Depth Image Representation of Multi-view Image with Color and Depth Information (컬러와 깊이 정보를 포함하는 다시점 영상의 효율적 계층척 깊이 영상 표현)

  • Lim, Joong-Hee;Kim, Min-Tae;Shin, Jong-Hong;Jee, Inn-Ho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.9 no.1
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    • pp.53-59
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    • 2009
  • Multi-view video is necessary to develop a new compression encoding technique for storage and transmission, because of a huge amount of data. Layered depth image is an efficient representation method of multi-view video data. This method makes a data structure that is synthesis of multi-view color and depth image. This paper proposed enhanced compression method by presentation of efficient layered depth image using real distance comparison, solution of overlap problem, and interpolation. In experimental results, confirmed high compression performance.

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Image Completion using Belief Propagation Based on Planar Priorities

  • Xiao, Mang;Li, Guangyao;Jiang, Yinyu;Xie, Li;He, Ye
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.9
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    • pp.4405-4418
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    • 2016
  • Automatic image completion techniques have difficulty processing images in which the target region has multiple planes or is non-facade. Here, we propose a new image completion method that uses belief propagation based on planar priorities. We first calculate planar information, which includes planar projection parameters, plane segments, and repetitive regularity extractions within the plane. Next, we convert this planar information into planar guide knowledge using the prior probabilities of patch transforms and offsets. Using the energy of the discrete Markov Random Field (MRF), we then define an objective function for image completion that uses the planar guide knowledge. Finally, in order to effectively optimize the MRF, we propose a new optimization scheme, termed Planar Priority-belief propagation that includes message-scheduling-based planar priority and dynamic label cropping. The results of experiment show that our approach exhibits advanced performance compared with existing approaches.

Rapid Stitching Method of Digital X-ray Images Using Template-based Registration (템플릿 기반 정합 기법을 이용한 디지털 X-ray 영상의 고속 스티칭 기법)

  • Cho, Hyunji;Kye, Heewon;Lee, Jeongjin
    • Journal of Korea Multimedia Society
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    • v.18 no.6
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    • pp.701-709
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    • 2015
  • Image stitching method is a technique for obtaining an high-resolution image by combining two or more images. In X-ray image for clinical diagnosis, the size of the imaging region taken by one shot is limited due to the field-of-view of the equipment. Therefore, in order to obtain a high-resolution image including large regions such as a whole body, the synthesis of multiple X-ray images is required. In this paper, we propose a rapid stitching method of digital X-ray images using template-based registration. The proposed algorithm use principal component analysis(PCA) and k-nearest neighborhood(k-NN) to determine the location of input images before performing a template-based matching. After detecting the overlapping position using template-based matching, we synthesize input images by alpha blending. To improve the computational efficiency, reduced images are used for PCA and k-NN analysis. Experimental results showed that our method was more accurate comparing with the previous method with the improvement of the registration speed. Our stitching method could be usefully applied into the stitching of 2D or 3D multiple images.

Fingerprint Image Enhancement Based on a Directional Filter (방향성 필터 뱅크에 기반한 지문영상의 향상)

  • 오상근;박철현;윤옥경;이준재;박길흠
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.4A
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    • pp.345-355
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    • 2002
  • This paper describes a new method of directional filter-based analysis for fingerprint enhancement. Fingerprint cages can be represented by direction field of regular structure of ridge patterns. The dominant directional component of ridge plays a very important role in pre-processing steps of fingerprint image analysis such as ridge's linking and noise removal for minutiae extraction. A directional filter bank analyzes input image into directional subband images and synthesizes them to the perfectly reconstructed image. In this paper, a new fingerprint enhancement algorithm based on a directional filter bank is proposed. The algorithm decomposes the fingerprint image into subband images in the analysis stage, accomplishes an enhance procedure by processing subband images in the enhance stage and synthesizes them to the enhanced image in the synthesis stage.

IR Image Processing IP Design, Implementation and Verification For SoC Design

  • Yoon, Hee-Jin
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.1
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    • pp.33-39
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    • 2018
  • In this paper, We studied the possibility of SoC(System On Chip) design using infrared image processing IP(Intellectual Property). And, we studied NUC(Non Uniformity Correction), BPR(Bad Pixel Recovery), and CEM(Contrast Enhancement) processing, the infrared image processing algorithm implemented by IP. We showed the logic and timing diagram implemented through the hardware block designed based on each algorithm. Each algorithm was coded as RTL(Register Transfer Level) using Verilog HDL(Hardware Description Language), ALTERA QUARTUS synthesis, and programed in FPGA(Field Programmable Gated Array). In addition, we have verified that the image data is processed at each algorithm without any problems by integrating the infrared image processing algorithm. Particularly, using the directly manufactured electronic board, Processor, SRAM, and FLASH are interconnected and tested and the verification result is presented so that the SoC type can be realized later. The infrared image processing IP proposed and verified in this study is expected to be of high value in the future SoC semiconductor fabrication. In addition, we have laid the basis for future application in the camera SoC industry.