• Title, Summary, Keyword: Image Processing Algorithm

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Scale Invariant Auto-context for Object Segmentation and Labeling

  • Ji, Hongwei;He, Jiangping;Yang, Xin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.8
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    • pp.2881-2894
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    • 2014
  • In complicated environment, context information plays an important role in image segmentation/labeling. The recently proposed auto-context algorithm is one of the effective context-based methods. However, the standard auto-context approach samples the context locations utilizing a fixed radius sequence, which is sensitive to large scale-change of objects. In this paper, we present a scale invariant auto-context (SIAC) algorithm which is an improved version of the auto-context algorithm. In order to achieve scale-invariance, we try to approximate the optimal scale for the image in an iterative way and adopt the corresponding optimal radius sequence for context location sampling, both in training and testing. In each iteration of the proposed SIAC algorithm, we use the current classification map to estimate the image scale, and the corresponding radius sequence is then used for choosing context locations. The algorithm iteratively updates the classification maps, as well as the image scales, until convergence. We demonstrate the SIAC algorithm on several image segmentation/labeling tasks. The results demonstrate improvement over the standard auto-context algorithm when large scale-change of objects exists.

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.

Application of Image Processing Technique to Improve Production Efficiency of Fine Pitch Hole Based on Laser (레이저 미세피치 홀 가공의 생산효율성 향상을 위한 영상처리 측정 기법 적용)

  • Pyo, C.R.
    • Transactions of Materials Processing
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    • v.19 no.5
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    • pp.320-324
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    • 2010
  • Multi-Layer Ceramic Circuit(MLCC) in the face of thousands of fine pitch multi hole is processed. However, the fine pitch multi hole has a size of only a few micrometers. Therefore, in order to curtail the measurement time and reduce error, the image processing measurement method is required. So, we proposed an image processing measurement algorithm which is required to accurately measure the fine pitch multi hole. The proposed algorithm gets image of the fine pitch multi hole, extracts object from the image by morphological process, and extracts the parameters of its position and feature by edge detecting process. In addition, we have used the sub-pixel algorithm to improve accuracy. As a result, the proposed algorithm shows 97% test-retest measurement reliability within 2 ${\mu}m$. We found that the algorithm was wellsuited for measuring the fine pitch multi hole.

Development of Pattern Classifying System for cDNA-Chip Image Data Analysis

  • Kim, Dae-Wook;Park, Chang-Hyun;Sim, Kwee-Bo
    • 제어로봇시스템학회:학술대회논문집
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    • pp.838-841
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    • 2005
  • DNA Chip is able to show DNA-Data that includes diseases of sample to User by using complementary characters of DNA. So this paper studied Neural Network algorithm for Image data processing of DNA-chip. DNA chip outputs image data of colors and intensities of lights when some sample DNA is putted on DNA-chip, and we can classify pattern of these image data on user pc environment through artificial neural network and some of image processing algorithms. Ultimate aim is developing of pattern classifying algorithm, simulating this algorithm and so getting information of one's diseases through applying this algorithm. Namely, this paper study artificial neural network algorithm for classifying pattern of image data that is obtained from DNA-chip. And, by using histogram, gradient edge, ANN and learning algorithm, we can analyze and classifying pattern of this DNA-chip image data. so we are able to monitor, and simulating this algorithm.

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Used the Computer Vision System Develop of Algorithm for Aluminium Mill Strip Defect Inspection (컴퓨터 비젼 시스템을 이용한 알루미늄표면 검사 알고리즘 개발)

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    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • pp.115-120
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    • 2000
  • This study is on the application the image processing algorithm for inspection of the aluminium mill strip surface defect. The image of surface defect data was obtained using the CCD camera with the digital signal board. The edge was found from the difference of pixel intensity between the normal image and defect image. Two step were taken to find the edge in the image processing algorithm. First, noise was removed by using the median filter in the image. Second, the edge was sharpened in detail by using the sharpening convolution filter in the image. Canny algorithm was used to defect the exact edge. The defect section was separated from the original image is to find the coordination point p1 and p2 which include the defect image

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Image-based structural dynamic displacement measurement using different multi-object tracking algorithms

  • Ye, X.W.;Dong, C.Z.;Liu, T.
    • Smart Structures and Systems
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    • v.17 no.6
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    • pp.935-956
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    • 2016
  • With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.

Development of Robot System for Colony Picking (I) - Image processing algorithm for detecting colony - (콜로니 픽킹 로봇 시스템의 개발 (I) - 콜로니 검출 영상처리 알고리즘 -)

  • 이현동;김기대;나건영;임용표
    • Journal of Biosystems Engineering
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    • v.28 no.5
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    • pp.439-448
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    • 2003
  • An image processing algorithm was developed for a robot system which was used in gene study. The robot system achieved a job of colony picking. The colony included DNA of an organism. The robot picked up the colony in petri-dish, which included the cultivated colony in medium, by a picking pin, and moved the colony to wellplates. The vision system consisted of an image acquisition system which acquired the image information of colony, an illumination device which irradiated the object once when it got the image of it, a computer and so on. The image processing algorithm distinguished the colony and detected colony positions. Performance test of the developed algorithm showed that the distinguishing success rate of colony and detecting success rate of colony positions were over 96%.

Design and Implementation of Sensor Network based Autonomous Vehicle Control System (센서 네트워크 기반 자율주행 자동차 제어 시스템 설계 및 구현)

  • Jang, Won-Chul;Kim, Jong-Myon
    • IEMEK Journal of Embedded Systems and Applications
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    • v.7 no.5
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    • pp.247-253
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    • 2012
  • This paper presents sensor network based autonomous vehicle system using a proposed image processing algorithm. The proposed image processing algorithm consists of pre-processing and five-stage image processing: coordinate calculation, driving area decision, line segment calculation, steeling decision, and acceleration decision. We evaluate the performance of the proposed algorithm on both straight road and curved road. Experimental results indicate that the proposed algorithm works well for autonomous vehicles. However, control accuracy of the proposed algorithm decreases as speed is increasing.

Development of Green-Sheet Measurement Algorithm by Image Processing Technique (영상처리기법을 이용한 그린시트 측정알고리즘 개발)

  • Pyo, C.R.;Yang, S.M.;Kang, S.H.;Yoon, S.M.
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • pp.51-54
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    • 2007
  • The purpose of this paper is the development of measurement algorithm for green-sheet based on the digital image processing technique. The Low Temperature Cofired Ceramic (LTCC) technology can be defined as a way to produce multilayer circuits with the help of single tapes, which are used to apply conductive, dielectric and / or resistive pastes on. These single green-sheets have to be laminated together and fired in one step all. Main functionality of the green-sheet film measurement algorithm is to measure the position and size of the punching hole in each single layer. The line scan camera coupled with motorized X-Y stage is used for developing the algorithm. In order to measure the entire film area using several scanning steps, the overlapping method is used. In the process of development of the algorithm based on the image processing and analysis, strong background technology and know-how have been accumulated.

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Improved Watershed Image Segmentation Using the Morphological Multi-Scale Gradient

  • Gelegdorj, Jugdergarav;Chu, Hyung-Suk;An, Chong-Koo
    • Journal of the Institute of Convergence Signal Processing
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    • v.12 no.2
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    • pp.91-95
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    • 2011
  • In this paper, we present an improved multi-scale gradient algorithm. The proposed algorithm works the effectively handling of both step and blurred edges. In the proposed algorithm, the image sharpening operator is sharpening the edges and contours of the objects. This operation gives an opportunity to get noise reduced image and step edged image. After that, multi-scale gradient operator works on noise reduced image in order to get a gradient image. The gradient image is segmented by watershed transform. The approach of region merging is used after watershed transform. The region merging is carried out according to the region area and region homogeneity. The region number of the proposed algorithm is 36% shorter than that of the existing algorithm because the proposed algorithm produces a few irrelevant regions. Moreover, the computational time of the proposed algorithm is relatively fast in comparison with the existing one.