• Title/Summary/Keyword: Extraction of feature line

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An improved cross-correlation method based on wavelet transform and energy feature extraction for pipeline leak detection

  • Li, Suzhen;Wang, Xinxin;Zhao, Ming
    • Smart Structures and Systems
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    • v.16 no.1
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    • pp.213-222
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    • 2015
  • Early detection and precise location of leakage is of great importance for life-cycle maintenance and management of municipal pipeline system. In the past few years, acoustic emission (AE) techniques have demonstrated to be an excellent tool for on-line leakage detection. Regarding the multi-mode and frequency dispersion characteristics of AE signals propagating along a pipeline, the direct cross-correlation technique that assumes the constant AE propagation velocity does not perform well in practice for acoustic leak location. This paper presents an improved cross-correlation method based on wavelet transform, with due consideration of the frequency dispersion characteristics of AE wave and the contribution of different mode. Laboratory experiments conducted to simulate pipeline gas leakage and investigate the frequency spectrum signatures of AE leak signals. By comparing with the other methods for leak location identification, the feasibility and superiority of the proposed method are verified.

Intelligent Fault Diagnosis of Induction Motors Using Vibration Signals (진동신호를 이용한 유도전동기의 지능적 결함 진단)

  • Han, Tian;Yang, Bo-Suk;Kim, Jae-Sik
    • Proceedings of the KSME Conference
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    • 2004.04a
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    • pp.822-827
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    • 2004
  • In this paper, an intelligent fault diagnosis system is proposed for induction motors through the combination of feature extraction, genetic algorithm (GA) and neural network (ANN) techniques. Features are extracted from motor vibration signals, while reducing data transfers and making on-line application available. GA is used to select most significant features from whole feature database and optimize the ANN structure parameter. Optimized ANN diagnoses the condition of induction motors online after trained by the selected features. The combination of advanced techniques reduces the learning time and increases the diagnosis accuracy. The efficiency of the proposed system is demonstrated through motor faults of electrical and mechanical origin on the induction motors. The results of the test indicate that the proposed system is promising for real time application.

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Recognition of Handwritten Numerals using Eigenvectors (고유벡터를 이용한 필기체 숫자인식)

  • 박중조;김경민;송명현
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.6
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    • pp.986-991
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    • 2002
  • This paper presents off-line handwritten numeral recognition method by using Eigen-Vectors. In this method, numeral features are extracted statistically by using Eigen-Vectors through KL transform and input numeral is recognized in the feature space by the nearest-neighbor classifier. In our feature extraction method, basis vectors which express best the property of each numeral type within the extensive database of sample numeral images are calculated, and the numeral features are obtained by using this basis vectors. Through the experiments with the unconstrained handwritten numeral database of Concordia University, we have achieved a recognition rate of 96.2%.

A Verification Method for Handwritten text in Off-line Environment Using Dynamic Programming (동적 프로그래밍을 이용한 오프라인 환경의 문서에 대한 필적 분석 방법)

  • Kim, Se-Hoon;Kim, Gye-Young;Choi, Hyung-Il
    • Journal of KIISE:Software and Applications
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    • v.36 no.12
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    • pp.1009-1015
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    • 2009
  • Handwriting verification is a technique of distinguishing the same person's handwriting specimen from imitations with any two or more texts using one's handwriting individuality. This paper suggests an effective verification method for the handwritten signature or text on the off-line environment using pattern recognition technology. The core processes of the method which has been researched in this paper are extraction of letter area, extraction of features employing structural characteristics of handwritten text, feature analysis employing DTW(Dynamic Time Warping) algorithm and PCA(Principal Component Analysis). The experimental results show a superior performance of the suggested method.

AUTOMATIC DETECTION Of NARROW OPEN WATER STREAMS IN AMAZON FORESTS FROM JERS-1 SAR IMAGERY

  • Amano, Takako-Sakurai;Iisaka, Joji;Kamiyama, Masataka;Takagi, Mikio
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.310-315
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    • 1999
  • We extracted narrow open water streams from JERS-1 SAR images of the Amazon rain forest. The extracted range of these streams were almost comparable to a high level extraction of the same streams from near-IR images of JERS-1 VNIR data notwithstanding that these features in SAR images show the strong dependence of the observation angle. Large water bodies are relatively easy to extract from JERS-1 SAR images, as they tend to appear as very dark areas; but streams whose width is nearly equal to or less than the spatial resolution no longer appear as very dark features. By using strong scatterers distributed sparsely along the radar facing sides of the streams, we can successfully estimate approximate ranges of waterways and then extract relatively dark line-like features within these ranges.

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Feature Extraction Techniques from Micro Drill Bits Images (마이크로 드릴 비트 영상에서의 특징 추출 기법)

  • Oh, Se-Jun;Kim, Nak-Hyun
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.919-920
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    • 2008
  • In this paper, we present early processing techniques for visual inspection of metallic parts. Since metallic surfaces give rise to specular reflections, it is difficult to extract object boundaries using elementary segmentation techniques such as edge detection or binary thresholding. In this paper, we present two techniques for finding object boundaries on micro bit images. First, we explain a technique for detecting blade boundaries using a directional correlation mask. Second, a line and angle extraction technique based on Harris corner detector and Hough transform is described. These techniques have been effective for detecting blade boundaries, and a number of experimental results are presented using real images.

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A study on the modified hough transform for hangul feature extraction using generalized sampling rule (한글 특징점 추출을 위한 일반화된 표본화 알고리즘을 이용한 수정된 Hough Transform에 관한 연구)

  • 구하성;고형화
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.9
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    • pp.142-149
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    • 1994
  • Hangul is expressed by the basic elements, twenty-four characters. Because these characters are composed of a circle and lines, Hough transform(HT), which has a powerful performance on the noise in extracting lines, is introduced. Many difficulties often occur when the original HT is used to extract strokes and it's direction, position and length from handwritten Hangul characters. Original HT has eight direction selected as samples in the transformed image should be calculated for these eight directions. In this paper, the generalized sampling rule is suggested. According to the rule, those directions which are possible to a line are the only thing to be calculated. The experoment result turned out to be higher than the method that Chen suggested in sampling rate. Anogher experiment result is done on the 1800 handwritten Hangul characters that 10 persons wrote. By feature extracting the oritinal HT and sampling HT. And as a result of six type classification, the suggested method came out higher than original HT.

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Feature Extraction for Off-line Handwritten Character Recognition using SIFT Descriptor (SIFT 서술자를 이용한 오프라인 필기체 문자 인식 특징 추출 기법)

  • Park, Jung-Guk;Kim, Kyung-Joong
    • Proceedings of the Korean Information Science Society Conference
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    • 2010.06c
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    • pp.496-500
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    • 2010
  • 본 논문에서는 SIFT(Scale Invariant Feature Transform) 기술자를 이용하여 오프라인 필기체 문자 인식을 위한 특징 추출방법을 제안한다. 제안하는 방법은 문자의 획의 방향 정보를 제공하는 특징 벡터를 추출함으로써 오프라인 문자 인식에서 성능 향상을 기대할 수 있다. 테스트를 위해 MNIST 필기체 데이터베이스와 UJI Penchar2 필기체 데이터베이스를 이용하였고, BP(backpropagation)신경망과 LDA(Linear Discriminant Analysis), SVM(Support Vector Machine) 분류기에서 성능 테스트를 하였다. 본 논문의 실험결과에서는 일반적으로 사용되는 특징추출로부터 얻어진 특징에 제안된 특징추출을 정합하여 성능항샹을 보인다.

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Bio- Information Extraction of On-line Signature Based on Pen-Input Informations and Feature Extraction with Independent Component Analysis (펜 입력정보를 기반으로 한 온라인 서명의 생체정보 추출 및 ICA를 이용한 특징 추출)

  • 성한호;윤성수;이일병
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10d
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    • pp.577-579
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    • 2002
  • 향후 보안시장을 이끌어갈 생체인식 기술은 현재까지 많은 발전을 거듭하고 있다. 이미 알려진 바와 같이 생체인식은 신체의 여러 부분들과 신체적 특징, 개인의 습관들이 이용되는데 전자의 경우 지문, 얼굴, 홍채, 망막, 음성, 필체, 정맥 등의 인식이 있고 후자의 경우 타이핑 습관, 걸음걸이 습관, 필기 습관 등이 해당된다. 본 연구에서는 서명인식을 필체 자체의 특징에 관련된 정보를 추출하여 인식하는 방법과는 달리 개개인의 필기 습관에 주목하여 서명을 할 때 펜을 눌러쓴 정도, 펜을 사용하는 위치 및 펜을 얼마나 뉘어 쓰는지 세워 쓰는지, 왼손잡이인지 오른손잡이인지 등의 동적 정보에 따른 특성을 알 수 있는 펜의 방위각과 기울임 정도에 대한 생체정보를 추출하고 현재 음성인식 등 여러 분야에서 사용되는 ICA를 사용하여 추출한 서명데이터의 생체정보를 분리.추출하여 이를 개개인의 검증데이터로 활용하는 방법을 제안한다.

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The Extraction of Exact Building Contours in Aerial Images (항공 영상에서의 인공지물의 정확한 경계 추출)

  • 최성한;이쾌희
    • Korean Journal of Remote Sensing
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    • v.11 no.1
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    • pp.47-64
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    • 1995
  • In this paper, an algorithm that finds man-made structures in a praylevel aerial images is proposed to perform stereo matching. An extracted contour of buildings must have a high accuracy in order to get a good feature-based stereo matching result. Therefore this study focuses on the use of edge following in the original image rather than use of ordinary edge filters. The Algorithm is composed of two main categories; one is to find candidate regions in the whole image and the other is to extract exact contours of each building which each candidate region.. The region growing method using the centroid linkage method of variance value is used to find candidate regions of building and the contour line tracing algorithm based on an adge following method is used to extract exact contours. The result shows that the almost contours of building composed of line segments are extracted.