• 제목/요약/키워드: Adaptive inspection

검색결과 65건 처리시간 0.027초

적응적 이진화 기법과 Bresenham's algorithm을 이용한 안경 렌즈 제품의 자동 흠집 검출 (Automatic Defect Inspection with Adaptive Binarization and Bresenham's Algorithm for Spectacle Lens Products)

  • 김광백;송두헌
    • 한국정보통신학회논문지
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    • 제21권7호
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    • pp.1429-1434
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    • 2017
  • 기존의 안경 렌즈 흠집 검출 방법은 영상내의 미세 잡음이 제거되지 않아 렌즈 영역이 정확히 추출되지 않는 경우가 발생하여 흠집 영역을 검출할 수 없다는 문제점이 발생한다. 따라서 본 논문에서는 이러한 문제점을 개선하기 위해 적응적 이진화 기법과 Bresenham algorithm을 적용하여 흠집 영역을 검출한다. 제안된 방법은 안경 렌즈 영상에서 명암 대비를 적용하여 렌즈의 명암을 강조한다. 명암이 강조된 영상에서 렌즈 밖의 배경 영역은 흠집 검출에 불필요하므로 이진화 기법을 적용한 후에 Bresenham algorithm을 적용하여 렌즈의 윤곽선을 검출하고 렌즈 이외의 배경을 제거한다. 렌즈 이외의 배경이 제거된 렌즈 영상에서 렌즈 내부의 배경과 흠집의 명암 대비를 높인다. 명암이 강조된 렌즈 내부 영역에서 적응적 이진화 기법을 적용하여 흠집과 잡음을 검출한다. 잡음은 중간값 필터를 적용하여 제거한 후에 흠집 영역을 추출한다. 추출된 흠집 영역에서 렌즈의 중심으로부터의 거리와 흠집의 크기를 퍼지 추론 규칙에 적용하여 눈에 미치는 영향 정도를 분석한다. 제안된 방법의 성능을 분석하기 위해 CHEMI, MID, HL, HM과 같은 시력 보정용 렌즈 영상을 대상으로 실험한 결과, 12개의 시력 보정용 렌즈 영상 중에서 10개에서 결함을 성공적으로 추출하였다.

냉연 표면흠 검사 알고리듬 개발에 관한 연구 (Development of surface defect inspection algorithms for cold mill strip)

  • 김경민;박귀태;박중조;이종학;정진양;이주강
    • 제어로봇시스템학회논문지
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    • 제3권2호
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    • pp.179-186
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    • 1997
  • In this paper we suggest a development of surface defect inspection algorithms for cold mill strip. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment and co-occurrence matrix features are calculated. For the defect classification, multilayer neural network is used. The proposed algorithm showed 15% error rate.

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국제공동연구 PARTRIDGE를 통한 확률론적 건전성 평가 기술 개발 현황 (Current Status of an International Co-Operative Research Program, PARTRIDGE (Probabilistic Analysis as a Regulatory Tool for Risk-Informed Decision GuidancE))

  • 김선혜;박정순;김진수;이진호;윤은섭;양준석;이재곤;박홍선;오영진;강선예;윤기석;박재학
    • 한국압력기기공학회 논문집
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    • 제9권1호
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    • pp.62-69
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    • 2013
  • A probabilistic assessment code, PRO-LOCA ver. 3.7 which was developed in an international co-operative research program, PARTRIDGE was evaluated by conducting sensitivity analysis. The effect of some variables such as simulation methods (adaptive sampling, iteration numbers, weld residual stress model), crack features(Poisson's arrival rate, maximum numbers of cracks, initial flaw size, fabrication flaws), operating and loading conditions(temperature, primary bending stress, earthquake strength and frequency), and inspection model(inspection intervals, detectable leak rate) on the failure probabilities of a surge line nozzle was investigated. The results of sensitivity analysis shows the remaining problems of the PRO-LOCA code such as the instability of adaptive sampling and unexpected trend of failure probabilities at an early stage.

Software Design of Packet Analyzer based on Byte-Filtered Packet Inspection Mechanism for UW-ASN

  • Muminov, Sardorbek;Yun, Nam-Yeol;Park, Soo-Hyun
    • 한국멀티미디어학회논문지
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    • 제14권12호
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    • pp.1572-1582
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    • 2011
  • The rapid growth of UnderWater Acoustic Sensor Networks (UW-ASNs) has led researchers to enhance underwater MAC protocols against limitations existing in underwater environment. We propose the customized robust real-time packet inspection mechanism with addressing the problem of the search for the data packet loss and network performance quality analysis in UW-ASNs, and describe our experiences using this approach. The goal of this work is to provide a framework to assess the network real-time performance quality. We propose a customized and adaptive mechanism to detect, monitor and analyze the data packets according to the MAC protocol standards in UW-ASNs. The packet analyzing method and software we propose is easy to implement, maintain, update and enhance. We take input stream as real data packets from sniffer node in capture mode and perform fully analysis. We were interested in developing software and hardware designed tool with the same capabilities which almost all terrestrial network packet sniffers have. Experimental results confirm that the best way to achieve maximum performance requires the most adaptive algorithm. In this paper, we present and offer the proposed packet analyzer, which can be effectively used for implementing underwater MAC protocols.

Robust Controller with Adaptation within the Boundary Layer Application to Nuclear Underwater Inspection Robot

  • Park, Gee-Yong;Yoon, Ji-Sup;Hong, Dong-Hee;Jeong, Jae-Hoo
    • Nuclear Engineering and Technology
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    • 제34권6호
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    • pp.553-565
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    • 2002
  • In this paper, the robust control scheme with the improved control performance within the boundary layer is proposed. In the control scheme, the robust controller based on the traditional variable structure control method is modified to have the adaptation within the boundary layer. From this controller, the width of the boundary layer where the robust control input is smoothened out can be given by an appropriate value. But the improved control performance within the boundary layer can be achieved without the so-called control chattering because the role of adaptive control is to compensate for the uncovered portions of the robust control occurred from the continuous approximation within the boundary layer Simulation tests for circular navigation of an underwater wall-ranging robot developed for inspection of wall surfaces in the research reactor, TRIGA MARK III, confirm the performance improvement. Notational Conventions Vectors are written in boldface roman lower-case letters, e.g., x and y. Matrices are written in upper-case roman letters, e.g., G and B. And ∥.∥ means the Euclidean norm.

ICT 기술을 융합한 자동차 실러도포 공정 모니터링 시스템 (Car Sealer Monitoring System Using ICT Technology)

  • 김호연;박종섭;박요한;조재수
    • 한국IT서비스학회지
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    • 제17권3호
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    • pp.53-61
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    • 2018
  • In this paper, we propose a car sealing monitoring system combined with ICT Technology. The automobile sealer is an adhesive used to bond inner and outer panels of doors, hoods and trunks of an automobile body. The proposed car sealer monitoring system is a system that can accurately and automatically inspect the condition of the automobile sealer coating process in the general often factory production line where the lighting change is very severe. The sealer inspection module checks the state of the applied sealer using an area scan camera. The vision inspection algorithm is adaptive to various lighting environments to determine whether the sealer is defective or not. The captured images and test results are configured to send the task results to the task manager in real-time as a smartphone app. Vision inspection algorithms in the plant outdoors are very vulnerable to time-varying external light sources and by configuring a monitoring system based on smart mobile equipment, it is possible to perform production monitoring regardless of time and place. The applicability of this method was verified by applying it to an actual automotive sealer application process.

냉연 표면흠 검사를 위한 전처리 알고리듬에 관한 연구 (A Study on the Development of Surface Defect Inspection Preprocessing Algorithm for Cold Mill Strip)

  • 김종웅;김경민;문윤식;박귀태;이종학;정진양
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 B
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    • pp.1240-1242
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    • 1996
  • In a still mill, the effective surface defect inspection algorithm is necessary. For this purpose, this paper proposed the preprocessing algorithm for surface defect inspection of cold mill strip. This consists of live steps. They are edge detection, binarizing, noise deletion, combining of fragmented defect and selecting the largest defect. Especially, binarizing is a critical problem. Bemuse the performance of the preprocessing is largely depend on the binarized image. So, we develope the adaptive thresholding method, which is multilevel thresholding. The thresholding value is varied according to the mean graylevel value of each test image. To investigate the performance of the proposed algorithm, we classified the detected defect using neural network. The test image is 20 defect images captured at German Sick Co. This algorithm is proved to have good property in cold mill strip surface inspection.

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Video Quality Representation Classification of Encrypted HTTP Adaptive Video Streaming

  • Dubin, Ran;Hadar, Ofer;Dvir, Amit;Pele, Ofir
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권8호
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    • pp.3804-3819
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    • 2018
  • The increasing popularity of HTTP adaptive video streaming services has dramatically increased bandwidth requirements on operator networks, which attempt to shape their traffic through Deep Packet inspection (DPI). However, Google and certain content providers have started to encrypt their video services. As a result, operators often encounter difficulties in shaping their encrypted video traffic via DPI. This highlights the need for new traffic classification methods for encrypted HTTP adaptive video streaming to enable smart traffic shaping. These new methods will have to effectively estimate the quality representation layer and playout buffer. We present a new machine learning method and show for the first time that video quality representation classification for (YouTube) encrypted HTTP adaptive streaming is possible. The crawler codes and the datasets are provided in [43,44,51]. An extensive empirical evaluation shows that our method is able to independently classify every video segment into one of the quality representation layers with 97% accuracy if the browser is Safari with a Flash Player and 77% accuracy if the browser is Chrome, Explorer, Firefox or Safari with an HTML5 player.

Adaptive Processing for Feature Extraction: Application of Two-Dimensional Gabor Function

  • Lee, Dong-Cheon
    • 대한원격탐사학회지
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    • 제17권4호
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    • pp.319-334
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    • 2001
  • Extracting primitives from imagery plays an important task in visual information processing since the primitives provide useful information about characteristics of the objects and patterns. The human visual system utilizes features without difficulty for image interpretation, scene analysis and object recognition. However, to extract and to analyze feature are difficult processing. The ultimate goal of digital image processing is to extract information and reconstruct objects automatically. The objective of this study is to develop robust method to achieve the goal of the image processing. In this study, an adaptive strategy was developed by implementing Gabor filters in order to extract feature information and to segment images. The Gabor filters are conceived as hypothetical structures of the retinal receptive fields in human vision system. Therefore, to develop a method which resembles the performance of human visual perception is possible using the Gabor filters. A method to compute appropriate parameters of the Gabor filters without human visual inspection is proposed. The entire framework is based on the theory of human visual perception. Digital images were used to evaluate the performance of the proposed strategy. The results show that the proposed adaptive approach improves performance of the Gabor filters for feature extraction and segmentation.

트리 구조를 이용한 냉연 표면흠 검사 알고리듬 개발에 관한 연구 (Development of surface defect inspection algorithms for cold mill strip using tree structure)

  • 김경민;정우용;이병진;류경;박귀태
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.365-370
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    • 1997
  • In this paper we suggest a development of surface defect inspection algorithms for cold mill strip using tree structure. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment, co-occurrence matrix, histogram-ratio features are calculated. The histogram-ratio feature is taken from the gray-level image. For the defect classification, we suggest a tree structure of which nodes are multilayer neural network clasifiers. The proposed algorithm reduced error rate comparing to one stage structure.

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