• Title/Summary/Keyword: Image Processing Technology

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Quantitative Evaluation of Dislocation Density in Epitaxial GaAs Layer on Si Using Transmission Electron Microscopy

  • Kim, Kangsik;Lee, Jongyoung;Kim, Hyojin;Lee, Zonghoon
    • Applied Microscopy
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    • v.44 no.2
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    • pp.74-78
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    • 2014
  • Dislocation density and distribution in epitaxial GaAs layer on Si are evaluated quantitatively and effectively using image processing of transmission electron microscopy image. In order to evaluate dislocation density and distribution, three methods are introduced based on line-intercept, line-length measurement and our coding with line-scanning method. Our coding method based on line-scanning is used to detect the dislocations line-by-line effectively by sweeping a thin line with the width of one pixel. The proposed method has advances in the evaluation of dislocation density and distribution. Dislocations can be detected automatically and continuously by a sweeping line in the code. Variation of dislocation density in epitaxial GaAs films can be precisely analyzed along the growth direction on the film.

Deep Learning in Genomic and Medical Image Data Analysis: Challenges and Approaches

  • Yu, Ning;Yu, Zeng;Gu, Feng;Li, Tianrui;Tian, Xinmin;Pan, Yi
    • Journal of Information Processing Systems
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    • v.13 no.2
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    • pp.204-214
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    • 2017
  • Artificial intelligence, especially deep learning technology, is penetrating the majority of research areas, including the field of bioinformatics. However, deep learning has some limitations, such as the complexity of parameter tuning, architecture design, and so forth. In this study, we analyze these issues and challenges in regards to its applications in bioinformatics, particularly genomic analysis and medical image analytics, and give the corresponding approaches and solutions. Although these solutions are mostly rule of thumb, they can effectively handle the issues connected to training learning machines. As such, we explore the tendency of deep learning technology by examining several directions, such as automation, scalability, individuality, mobility, integration, and intelligence warehousing.

Position Control of an Object Using Vision Sensor (비전 센서를 이용한 물체의 위치 제어)

  • Ha, Eun-Hyeon;Choi, Goon-Ho
    • Journal of the Semiconductor & Display Technology
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    • v.10 no.2
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    • pp.49-56
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    • 2011
  • In recent years, owing to the development of the image processing technology, the research to build control system using a vision sensor is stimulated. However, the time delay must be considered, because it works of time to get the result of an image processing in the system. It can be seen as an obstacle factor to real-time control. In this paper, using the pattern matching technique, the location of two objects is recognized from one image which was acquired by a camera. And it is implemented to a position control system as feedback data. Also, a possibility was shown to overcome a problem of time delay using PID controller. A number of experiments were done to show the validity of this study.

Fashion attribute-based mixed reality visualization service (패션 속성기반 혼합현실 시각화 서비스)

  • Yoo, Yongmin;Lee, Kyounguk;Kim, Kyungsun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.2-5
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    • 2022
  • With the advent of deep learning and the rapid development of ICT (Information and Communication Technology), research using artificial intelligence is being actively conducted in various fields of society such as politics, economy, and culture and so on. Deep learning-based artificial intelligence technology is subdivided into various domains such as natural language processing, image processing, speech processing, and recommendation system. In particular, as the industry is advanced, the need for a recommendation system that analyzes market trends and individual characteristics and recommends them to consumers is increasingly required. In line with these technological developments, this paper extracts and classifies attribute information from structured or unstructured text and image big data through deep learning-based technology development of 'language processing intelligence' and 'image processing intelligence', and We propose an artificial intelligence-based 'customized fashion advisor' service integration system that analyzes trends and new materials, discovers 'market-consumer' insights through consumer taste analysis, and can recommend style, virtual fitting, and design support.

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An Image Processing System for Measuring the Weight of A Dairy Cattle (젖소 체중측정을 위한 영상처리 시스템)

  • 이대원;김현태
    • Journal of Animal Environmental Science
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    • v.7 no.3
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    • pp.183-190
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    • 2001
  • The objective of this research was to design and construct an image processing system to measure easily and accurately cow's weight. The image processing system was built for a dairy cattle to be measured and estimated it's weight using camera and personal computer. The pixel numbers, which was derived from the image processing system, were counted to estimate the weight of a dairy cattle. They were utilized various was for finding the relationships between pixel numbers and it's real weight. Based on the results of this research the following conclusions were made: 1. It's weight could be estimated by using pixel numbers, which was captured from top and side cameras to measure it. The correlations with tea-view pixel numbers, side-view pixel numbers, superficial area pixel numbers and the volume pixel numbers were 0.909, 0.939, 0.944 and 0.965. 2. 50 cattle was used to execute an experiment with the image processing system, but average errors were big to make out the good relationship between cow's weight and pixel numbers. In order measure accurately a cattle weight, cattle weight, cattle groups would be divided by the age of cattle and further study should be carried out to be based on the results of this research. 3. The average time it took to perform the image processing to be measure it was 10 seconds, but it took 10 minutes for cattle to enter for measuring it's weight into the weighting system.

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Nuclear Medicine Physics: Review of Advanced Technology

  • Oh, Jungsu S.
    • Progress in Medical Physics
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    • v.31 no.3
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    • pp.81-98
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    • 2020
  • This review aims to provide a brief, comprehensive overview of advanced technologies of nuclear medicine physics, with a focus on recent developments from both hardware and software perspectives. Developments in image acquisition/reconstruction, especially the time-of-flight and point spread function, have potential advantages in the image signal-to-noise ratio and spatial resolution. Modern detector materials and devices (including lutetium oxyorthosilicate, cadmium zinc tellurium, and silicon photomultiplier) as well as modern nuclear medicine imaging systems (including positron emission tomography [PET]/computerized tomography [CT], whole-body PET, PET/magnetic resonance [MR], and digital PET) enable not only high-quality digital image acquisition, but also subsequent image processing, including image reconstruction and post-reconstruction methods. Moreover, theranostics in nuclear medicine extend the usefulness of nuclear medicine physics far more than quantitative image-based diagnosis, playing a key role in personalized/precision medicine by raising the importance of internal radiation dosimetry in nuclear medicine. Now that deep-learning-based image processing can be incorporated in nuclear medicine image acquisition/processing, the aforementioned fields of nuclear medicine physics face the new era of Industry 4.0. Ongoing technological developments in nuclear medicine physics are leading to enhanced image quality and decreased radiation exposure as well as quantitative and personalized healthcare.

High-speed Image Processing for Blurred Image for an Object Detection (블러가 심한 물체 검출을 위한 고속 MMX 영상처리)

  • Lee, Jae-Hyeok
    • Proceedings of the KIEE Conference
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    • 2005.10b
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    • pp.177-179
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    • 2005
  • This paper suggests a high-speed blurred blob image inspection algorithm. When we inspect some products using high-resolution camera, the detected blob images usually have severe blur. And the blur makes it hard to detect an object. There are many blur-processing algorithms, but most of them have no real-time property for high-speed applications at all. In this paper, an MMX technology based algorithm is suggested. The suggested algorithm was found to be effective to detect the blurred blob images via many simulations and long time real-plant experiments.

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A Study on the Improvement of PIV Performance (PIV의 성능개선에 관한 연구)

  • 이영호;김춘식;최장운
    • Journal of Advanced Marine Engineering and Technology
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    • v.18 no.3
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    • pp.34-42
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    • 1994
  • The present study is aimed to improve the PIV performance by suggesting a two-frame particle identification technique and by introducing estimation method of wall pressure distribution from the velocity data. Adopted image processing system consists of one commercial image board slit into a personal computer, 2-D sheet light generator, flow picture recording apparatus and related particle identification software. A revised particle tracking method essential to PIV performance is obtained by particle centroid correlation pairing (CCP) and its effectiveness is ascertained by comparison with multi-frame identification.

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A Study on the Create of CAD data using Image processing Method (화상처리 방법을 이용한 도면의 전산화에 관한 연구)

  • 이이선
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2000.04a
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    • pp.133-137
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    • 2000
  • In this paper, We study on converting data transfer using Image processing method. In the program's code consist of outline trace, noise filtering methode, pont data smoothing, algorithm. We use those Algorithm to create Vectorized data file format from image data. This result can be utilized as a base part for development of Automatic recognition for mechanical drawings.

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Implementation of fall-down detection algorithm based on Image Processing (영상처리 기반 낙상 감지 알고리즘의 구현)

  • Kim, Seon-Gi;Ahn, Jong-Soo;Kim, Won-Ho
    • Journal of Satellite, Information and Communications
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    • v.12 no.2
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    • pp.56-60
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    • 2017
  • This paper describes the design and implementation of fall-down detection algorithm based on image processing. The fall-down detection algorithm separates objects by using background subtraction and binarization after grayscale conversion of the input image acquired by the camera, and recognizes the human body by using labeling operation. The recognized human body can be monitored on the display image, and an alarm is generated when fall-down is detected. By using computer simulation, the proposed algorithm has shown a detection rate of 90%. We verify the feasibility of the proposed system by verifying the function by using the prototype test implemented on the DSP image processing board.