• Title/Summary/Keyword: Point-extraction

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A Study on Extraction of the Center Point of Steam Generator Tubes of YoungKwang Nuclear Power Plant

  • Cho, Jai-Wan;Kim, Chang-Hoi;Seo, Yong-Chil;Park, Young-Soo;Kim, Seung-Ho
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.96.5-96
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    • 2002
  • This paper describes extraction procedures for the center coordinates of steam generator tubes of Youngkwang nuclear power plant No. 6 unit. The centering coordinates of tubes are needed for monitoring whether ECT probe is exactly inserted into tube or not. However, The tube image tends to have poor contrast because steam generator bowl is sealed. The centering coordinates extraction procedure consists of two steps. The first step is to process the region with high contrast in entire image of steam generator tubes. Using the center points extracted in the first step and the geometry of tubes lined up in regular triangle patterns the centering coordinates of the rest region with low contrast...

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Korean Character Recognition by the Extraction of Feature Points and Neural Chip Design for its Preprocessing (특징점 추출에 의한 한글 문자 인식 및 전처리용 신경 칩의 설계)

  • 김종렬;정호선;이우일
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.27 no.6
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    • pp.929-936
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    • 1990
  • This paper describes the method of the Korean character recognition by means of feature points extraction. Also, the preprocessing neural chip for noise elimination, smoothing, thinning and feature point extraction has been designs. The subpatterns were separated by means of advanced index algorithm using mask, and recognized by means of feature points classification. The separation of the Korean character subpatterns was abtained about 97%, and the recognition of the Korean characters was abtained about 95%. The preprocessing neural chip was simulated on SPICE and layouted by double CMOS 2\ulcorner design rule.

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Study on 3 DoF Image and Video Stitching Using Sensed Data

  • Kim, Minwoo;Chun, Jonghoon;Kim, Sang-Kyun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.9
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    • pp.4527-4548
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    • 2017
  • This paper proposes a method to generate panoramic images by combining conventional feature extraction algorithms (e.g., SIFT, SURF, MPEG-7 CDVS) with sensed data from inertia sensors to enhance the stitching results. The challenge of image stitching increases when the images are taken from two different mobile phones with no posture calibration. Using inertia sensor data obtained by the mobile phone, images with different yaw, pitch, and roll angles are preprocessed and adjusted before performing stitching process. Performance of stitching (e.g., feature extraction time, inlier point numbers, stitching accuracy) between conventional feature extraction algorithms is reported along with the stitching performance with/without using the inertia sensor data. In addition, the stitching accuracy of video data was improved using the same sensed data, with discrete calculation of homograph matrix. The experimental results for stitching accuracies and speed using sensed data are presented in this paper.

Extraction and Regularization of Various Building Boundaries with Complex Shapes Utilizing Distribution Characteristics of Airborne LIDAR Points

  • Lee, Jeong-Ho;Han, Soo-Hee;Byun, Young-Gi;Kim, Yong-Il
    • ETRI Journal
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    • v.33 no.4
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    • pp.547-557
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    • 2011
  • This study presents an approach for extracting boundaries of various buildings, which have concave boundaries, inner yards, non-right-angled corners, and nonlinear edges. The approach comprises four steps: building point segmentation, boundary tracing, boundary grouping, and regularization. In the second and third steps, conventional algorithms are improved for more accurate boundary extraction, and in the final step, a new algorithm is presented to extract nonlinear edges. The unique characteristics of airborne light detection and ranging (LIDAR) data are considered in some steps. The performance and practicality of the presented algorithm were evaluated for buildings of various shapes, and the average omission and commission error of building polygon areas were 0.038 and 0.033, respectively.

A study on the Measurement Algorithm for the Ball Height of BGA Device Using Stereo Vision (스테레오 비젼을 이용한 BGA 소자의 볼 높이 측정 알고리즘에 관한 연구)

  • Kim, Joon-Seek;Park, Young-Soon
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.20 no.6
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    • pp.26-34
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    • 2006
  • In this paper, We proposed he algorithm for defect extraction and a study of the stereo image modeling o inspect defect for the ball height of BGA(ball grid way) device using 2-dimensional images captured by the BGA device of using the high resolution CCD cameras. This paper propose the package/ball area extraction of BGA device part, the FOV(field of view) calibration part, the top point matching part, and ball height measurement method. Each BGA device propose extraction method by defect, Through the experiment, we verified the result.

A Study on the Extraction of Linear Features from Satellite Images and Automatic GCP Filing (위성영상의 선형특징 추출과 이를 이용한 자동 GCP 화일링에 관한 연구)

  • 김정기;강치우;박래홍;이쾌희
    • Korean Journal of Remote Sensing
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    • v.5 no.2
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    • pp.133-145
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    • 1989
  • This paper describes an implementation of linear feature extraction algorithms for satellite images and a method of automatic GCP(Ground Control Point) filing using the extracted linear feature. We propose a new linear feature extraction algorithm which uses magnitude and direction information of edges. The result of applying the proposed algorithm to satellite images are presented and compared with those of the other algorithms. By using the proposed algorithm, automatic GCP filing was successfully performed.

Compressive sensing-based two-dimensional scattering-center extraction for incomplete RCS data

  • Bae, Ji-Hoon;Kim, Kyung-Tae
    • ETRI Journal
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    • v.42 no.6
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    • pp.815-826
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    • 2020
  • We propose a two-dimensional (2D) scattering-center-extraction (SCE) method using sparse recovery based on the compressive-sensing theory, even with data missing from the received radar cross-section (RCS) dataset. First, using the proposed method, we generate a 2D grid via adaptive discretization that has a considerably smaller size than a fully sampled fine grid. Subsequently, the coarse estimation of 2D scattering centers is performed using both the method of iteratively reweighted least square and a general peak-finding algorithm. Finally, the fine estimation of 2D scattering centers is performed using the orthogonal matching pursuit (OMP) procedure from an adaptively sampled Fourier dictionary. The measured RCS data, as well as simulation data using the point-scatterer model, are used to evaluate the 2D SCE accuracy of the proposed method. The results indicate that the proposed method can achieve higher SCE accuracy for an incomplete RCS dataset with missing data than that achieved by the conventional OMP, basis pursuit, smoothed L0, and existing discrete spectral estimation techniques.

Term Frequency-Inverse Document Frequency (TF-IDF) Technique Using Principal Component Analysis (PCA) with Naive Bayes Classification

  • J.Uma;K.Prabha
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.113-118
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    • 2024
  • Pursuance Sentiment Analysis on Twitter is difficult then performance it's used for great review. The present be for the reason to the tweet is extremely small with mostly contain slang, emoticon, and hash tag with other tweet words. A feature extraction stands every technique concerning structure and aspect point beginning particular tweets. The subdivision in a aspect vector is an integer that has a commitment on ascribing a supposition class to a tweet. The cycle of feature extraction is to eradicate the exact quality to get better the accurateness of the classifications models. In this manuscript we proposed Term Frequency-Inverse Document Frequency (TF-IDF) method is to secure Principal Component Analysis (PCA) with Naïve Bayes Classifiers. As the classifications process, the work proposed can produce different aspects from wildly valued feature commencing a Twitter dataset.

A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus

  • Daoud, Mosaab
    • Genomics & Informatics
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    • v.18 no.1
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    • pp.7.1-7.7
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    • 2020
  • In this paper, we present few technical notes about the distance distribution paradigm for Mosaab-metric using 1, 2, and 3 grams feature extraction techniques to analyze composite data points in high dimensional feature spaces. This technical analysis will help the specialist in bioinformatics and biotechnology to deeply explore the biodiversity of influenza virus genome as a composite data point. Various technical examples are presented in this paper, in addition, the integrated statistical learning pipeline to process segmented genomes of influenza virus is illustrated as sequential-parallel computational pipeline.

A study on the extraction of boundary points of point group segmented from LIDAR point cloud (LIDAR 포인트 cloud에서 분리된 포인트 군집의 윤곽 포인트 추출에 관한 연구)

  • Han, Soo-Hee;Lee, Jeong-Ho;Yu, Ki-Yun;Kim, Yong-Il
    • Proceedings of the KSRS Conference
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    • 2007.03a
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    • pp.148-152
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    • 2007
  • 본 연구에서는 LIDAR 포인트 자료로부터 분리된 포인트 군집의 윤곽 포인트 추출을 위하여,가상격자를 이용한 검색 영역의 제한을 통한 윤곽 포인트 추출 방식을 제안하였으며 성능을 평가하기 위해 보편적으로 사용되는 TIN을 이용한 방식과 비교하였다. 실제 건물 포인트 자료에 대하여 적용한 결과 TIN을 이용한 방식보다 빠른 처리가 가능하며 시각적인 평가를 통해 결과물의 품질 면에서도 두 가지 방식이 거의 유사함을 확인할 수 있었다.

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