• Title/Summary/Keyword: Image Processing Technology

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Vision Inspection and Correction for DDI Protective Film Attachment

  • Kang, Jin-Su;Kim, Sung-Soo;Lee, Yong-Hwan;Kim, Young-Hyung
    • Journal of Advanced Information Technology and Convergence
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    • v.10 no.2
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    • pp.153-166
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    • 2020
  • DDI(Display Driver IC) are used to drive numerous pixels that make up display. For stable driving of DDI, it is necessary to attach a protective film to shield electromagnetic waves. When the protective film is attached, defects often occur if the film is inclined or the center point is not aligned. In order to minimize such defects, an algorithm for correcting the center point and the inclined angle using camera image information is required. This technology detects the corner coordinates of the protective film by image processing in order to correct the positional defects where the protective film is attached. Corner point coordinates are detected using an algorithm, and center point position finds and correction values are calculated using the detected coordinates. LUT (Lookup Table) is used to quickly find out whether the angle is inclined or not. These algorithms were described by Verilog HDL. The method using the existing software requires a memory to store the entire image after processing one image. Since the method proposed in this paper is a method of scanning by adding a line buffer in one scan, it is possible to scan even if only a part of the image is saved after processing one image. Compared to those written in software language, the execution time is shortened, the speed is very fast, and the error is relatively small.

A study on the Flat Zone Length of Workpiece at Flexible Disk Grinder Cutting Process Measurement and Prediction using Image Processing (화상처리시스템을 이용한 유연성디스크 절삭가공에서 평면구간 측정 및 예측에 관한 연구)

  • Shin, Kwan Soo;Roh, Dae Ho
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.22 no.3
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    • pp.402-407
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    • 2013
  • In this paper, the image processing for flexible disk grinding and the effect of the grinding conditions on the flat zone length of a workpiece are investigated, with the purpose of automating the grinding process. To accomplish this, three issues should be carefully studied. The first is finding the relationship between the flat zone length and the grinding conditions such as the cutting speed and feeding speed. The second is developing a neural network algorithm to predict the flat zone. The third is developing an image processing algorithm to measure the flat zone length of a workpiece. Slope analysis is used to determine straight and curved sections during the image processing. For verification, the estimated length and the length from the image processing are compared with the length measured by a projector. There is a minimum difference of 1.7% between the predicted and measured values. The results of this paper will be useful in compiling a database for process automation.

A Study on the Transformation of CAD Data Using the Image Data Processing (화상처리를 이용한 CAD 데이터의 생성에 관한 연구)

  • Koo, Bon-Kwon;Roh, Woo-Joon
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.7 no.6
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    • pp.72-79
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    • 1998
  • In this paper, image processing algorithm is studied to enhance the preciseness of the geometry while converting captured images to CAD data. A program is developed as a result. The code, in the image processing, utilizes outline trace, point data smoothing algorithm. It is capable of automatically generating design data by converting input image data to the CAD data. The output can be made in DXF, IGES formats. The current research can be utilized as a base data for the development of factory automation or flexible manufacturing system which adopt image processing based automatic inspection and measuring system.

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Unsupervised Segmentation of Images Based on Shuffled Frog-Leaping Algorithm

  • Tehami, Amel;Fizazi, Hadria
    • Journal of Information Processing Systems
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    • v.13 no.2
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    • pp.370-384
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    • 2017
  • The image segmentation is the most important operation in an image processing system. It is located at the joint between the processing and analysis of the images. Unsupervised segmentation aims to automatically separate the image into natural clusters. However, because of its complexity several methods have been proposed, specifically methods of optimization. In our work we are interested to the technique SFLA (Shuffled Frog-Leaping Algorithm). It's a memetic meta-heuristic algorithm that is based on frog populations in nature searching for food. This paper proposes a new approach of unsupervised image segmentation based on SFLA method. It is implemented and applied to different types of images. To validate the performances of our approach, we performed experiments which were compared to the method of K-means.

Observation of Fatigue Crack Growth Behavior in 1Cr-1Mo-0.25V Steel Using Image Processing Technology (영상처리기법을 이용한 1Cr-1Mo-0.25V 강의 피로균열 성장거동 관찰)

  • Nahm, Seung-Hoon;Kim, Yong-Il;Ryu, Dae-Hyun
    • Journal of the Korean Society for Nondestructive Testing
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    • v.22 no.1
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    • pp.14-21
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    • 2002
  • The development of a new experimental method is required to easily observe the growth behavior of fatigue cracks. To satisfy the requirement, an image processing technique was introduced to fatigue testing. The length of surface fatigue crack could be successfully measured by the image processing system. At first, the image data of cracks were stored into the computer while the cyclic loading was interrupted. After testing, crack length was determined using an image processing software which was developed by authors. Various image processing techniques like a block matching method was applied tc the detection of surface fatigue cracks. By comparing the data measured by the image processing system with those by the manual measurement with a microscope, the effectiveness of the image processing system was established. If the proposed method is used to monitor and observe the crack growth behavior automatically, the time and efforts for fatigue test could be dramatically reduced.

A High Quality Steganographic Method Using Morphing

  • Bagade, Anant M.;Talbar, Sanjay N.
    • Journal of Information Processing Systems
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    • v.10 no.2
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    • pp.256-270
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    • 2014
  • A new morphed steganographic algorithm is proposed in this paper. Image security is a challenging problem these days. Steganography is a method of hiding secret data in cover media. The Least Significant Bit is a standard Steganographic method that has some limitations. The limitations are less capacity to hide data, poor stego image quality, and imperceptibility. The proposed algorithm focuses on these limitations. The morphing concept is being used for image steganography to overcome these limitations. The PSNR and standard deviation are considered as a measure to improve stego image quality and morphed image selection, respectively. The stego keys are generated during the morphed steganographic embedding and extracting process. Stego keys are used to embed and extract the secret image. The experimental results, which are based on hiding capacity and PSNR, are presented in this paper. Our research contributes towards creating an improved steganographic method using image morphing. The experimental result indicates that the proposed algorithm achieves an increase in hiding capacity, stego image quality, and imperceptibility. The experimental results were compared with state of the art steganographic methods.

Convolutional Neural Network Based Image Processing System

  • Kim, Hankil;Kim, Jinyoung;Jung, Hoekyung
    • Journal of information and communication convergence engineering
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    • v.16 no.3
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    • pp.160-165
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    • 2018
  • This paper designed and developed the image processing system of integrating feature extraction and matching by using convolutional neural network (CNN), rather than relying on the simple method of processing feature extraction and matching separately in the image processing of conventional image recognition system. To implement it, the proposed system enables CNN to operate and analyze the performance of conventional image processing system. This system extracts the features of an image using CNN and then learns them by the neural network. The proposed system showed 84% accuracy of recognition. The proposed system is a model of recognizing learned images by deep learning. Therefore, it can run in batch and work easily under any platform (including embedded platform) that can read all kinds of files anytime. Also, it does not require the implementing of feature extraction algorithm and matching algorithm therefore it can save time and it is efficient. As a result, it can be widely used as an image recognition program.

Medical Image Processing System for Morphometric and Functional Analysis of a Human Brain (인간 뇌의 형태적 및 기능적 분석을 위한 의료영상 처리시스템)

  • Kim, Tae-U
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.3
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    • pp.977-991
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    • 2000
  • In this paper, a medical image processing system was designed and implemented for morphometric and functional analysis of a human brain. The system is composed of image registration, ROI(region of interest) analysis, functional analysis, image visualization, 3D medical image database management system(DBMS), and database. The software processes an anatomical and functional image as input data, and provides visual and quantitative results. Input data and intermediate or final output data are stored to the database as several data types by the DBMS for other further image processing. In the experiment, the ROI analysis, for a normal, a tumor, a Parkinson's decease, and a depression case, showed that the system is useful for morphometric and functional analysis of a human brain.

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A Survey on User Interface Considering Social Acceptability based on Smart Glasses (스마트 글라스 기반의 사회적 수용성을 고려한 사용자 인터페이스 기존 연구 분석)

  • Lee, Minho;Heo, Hwan;Kim, Jaewoo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.10a
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    • pp.1160-1161
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    • 2019
  • Augmented Reality(AR) 기반의 스마트 글라스가 제공하는 일반적인 사용자 인터페이스는 카페 혹은 도서관 등과 같은 공공장소에서 사용이 꺼려지는 경향이 있다. 콘텐츠 조작 시 주변 사람들에게 관심을 받거나 프라이버시를 지키기 어렵기 때문이다. 이런 문제는 사회적으로 수용 가능한 범위 내에서의 사용자 인터페이스를 수행함으로써 해결할 수 있다. 본 논문에서는 스마트 글라스에서 사회적 수용성을 고려한 사용자 인터페이스의 기존 연구들을 분석하고자 한다.

Cloud-based Satellite Image Processing Service by Open Source Stack: A KARI Case

  • Lee, Kiwon;Kang, Sanggoo;Kim, Kwangseob;Chae, Tae-Byeong
    • Korean Journal of Remote Sensing
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    • v.33 no.4
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    • pp.339-350
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    • 2017
  • In recent, cloud computing paradigm and open source as a huge trend in the Information Communication Technology (ICT) are widely applied, being closely interrelated to each other in the various applications. The integrated services by both technologies is generally regarded as one of a prospective web-based business models impacting the concerned industries. In spite of progressing those technologies, there are a few application cases in the geo-based application domains. The purpose of this study is to develop a cloud-based service system for satellite image processing based on the pure and full open source. On the OpenStack, cloud computing open source, virtual servers for system management by open source stack and image processing functionalities provided by OTB have been built or constructed. In this stage, practical image processing functions for KOMPSAT within this service system are thresholding segmentation, pan-sharpening with multi-resolution image sets, change detection with paired image sets. This is the first case in which a government-supporting space science institution provides cloud-based services for satellite image processing functionalities based on pure open source stack. It is expected that this implemented system can expand with further image processing algorithms using public and open data sets.