• 제목/요약/키워드: Binary Pattern

검색결과 395건 처리시간 0.027초

이진 격자 패턴 이미지를 이용한 비접촉식 평면 구동기의 면내 위치(x, y, $\theta$) 측정 방법 (A Novel Measuring Method of In-plane Position of Contact-Free Planar Actuator Using Binary Grid Pattern Image)

  • 정광석;정광호;백윤수
    • 한국정밀공학회지
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    • 제20권7호
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    • pp.120-127
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    • 2003
  • A novel three degrees of freedom sensing method utilizing binary grid pattern image and vision camera is presented. The binary grid pattern image is designed by Pseudo-Random Binary Arrays and referenced to encode in-plane position of a moving stage of the contact-free planar actuator. First, the yaw motion of the stage is detected using fast image processing and then the other planar positions, x and y, are decoded with a sequence of images. This method can be applied to the system that needs feedback of in-plane position, with advantages of a good accuracy and high resolution comparable with the encoder, a relatively compact structure, no friction, and a low cost. In this paper, all the procedures of the above sensing mechanism are described in detail, including simulation and experiment results.

Finger Vein Recognition Using Generalized Local Line Binary Pattern

  • Lu, Yu;Yoon, Sook;Xie, Shan Juan;Yang, Jucheng;Wang, Zhihui;Park, Dong Sun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권5호
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    • pp.1766-1784
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    • 2014
  • Finger vein images contain rich oriented features. Local line binary pattern (LLBP) is a good oriented feature representation method extended from local binary pattern (LBP), but it is limited in that it can only extract horizontal and vertical line patterns, so effective information in an image may not be exploited and fully utilized. In this paper, an orientation-selectable LLBP method, called generalized local line binary pattern (GLLBP), is proposed for finger vein recognition. GLLBP extends LLBP for line pattern extraction into any orientation. To effectually improve the matching accuracy, the soft power metric is employed to calculate the matching score. Furthermore, to fully utilize the oriented features in an image, the matching scores from the line patterns with the best discriminative ability are fused using the Hamacher rule to achieve the final matching score for the last recognition. Experimental results on our database, MMCBNU_6000, show that the proposed method performs much better than state-of-the-art algorithms that use the oriented features and local features, such as LBP, LLBP, Gabor filter, steerable filter and local direction code (LDC).

NETLA Based Optimal Synthesis Method of Binary Neural Network for Pattern Recognition

  • Lee, Joon-Tark
    • 한국지능시스템학회논문지
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    • 제14권2호
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    • pp.216-221
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    • 2004
  • This paper describes an optimal synthesis method of binary neural network for pattern recognition. Our objective is to minimize the number of connections and the number of neurons in hidden layer by using a Newly Expanded and Truncated Learning Algorithm (NETLA) for the multilayered neural networks. The synthesis method in NETLA uses the Expanded Sum of Product (ESP) of the boolean expressions and is based on the multilayer perceptron. It has an ability to optimize a given binary neural network in the binary space without any iterative learning as the conventional Error Back Propagation (EBP) algorithm. Furthermore, NETLA can reduce the number of the required neurons in hidden layer and the number of connections. Therefore, this learning algorithm can speed up training for the pattern recognition problems. The superiority of NETLA to other learning algorithms is demonstrated by an practical application to the approximation problem of a circular region.

Bayesian Pattern Mixture Model for Longitudinal Binary Data with Nonignorable Missingness

  • Kyoung, Yujung;Lee, Keunbaik
    • Communications for Statistical Applications and Methods
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    • 제22권6호
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    • pp.589-598
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    • 2015
  • In longitudinal studies missing data are common and require a complicated analysis. There are two popular modeling frameworks, pattern mixture model (PMM) and selection models (SM) to analyze the missing data. We focus on the PMM and we also propose Bayesian pattern mixture models using generalized linear mixed models (GLMMs) for longitudinal binary data. Sensitivity analysis is used under the missing not at random assumption.

Binary Nature Revealed in Circumstellar Spiral-Shell Patterns

  • Kim, Hyosun;Hsieh, I-Ta;Liu, Sheng-Yuan;Taam, Ronald E.
    • 천문학회보
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    • 제39권1호
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    • pp.56.1-56.1
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    • 2014
  • With the advent of high-resolution high-sensitivity observations, spiral patterns have been revealed around several asymptotic giant branch (AGB) stars. Such patterns can provide possible evidence for the existence of central binary stars embedded in outflowing circumstellar envelopes. It is, however, not generally recognized that the binary induced pattern, vertically extended from the orbital plane, exhibits a ring-like pattern with an inclined viewing angle. I will first review the binary-induced spiral-shell patterns on the AGB circumstellar envelopes with the effect of inclination angle with respect to the orbital plane, of which large inclination cases reveal incomplete ring-like patterns. I will describe a method of extracting such spiral-shell from the gas kinematics of an incomplete ring-like pattern to place constraints on the characteristics of the (unknown) central binary stars. This first success may open the possibility of connecting the ring-like patterns commonly found in the AGB circumstellar envelopes and in the outer parts of (pre-)planetary nebulae and pointing to the conceivable presence of central binary systems, which may give a clue for the onset of asymmetrical planetary nebulae.

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중간값 국소이진패턴 사이의 동시발생 빈도 기반 패턴인식 (A Pattern Recognition Based on Co-occurrence among Median Local Binary Patterns)

  • 조용현
    • 한국지능시스템학회논문지
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    • 제26권4호
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    • pp.316-320
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    • 2016
  • 본 논문에서는 질감영상의 마이크로패턴 간 공간적인 동시발생 빈도를 고려한 패턴인식을 제안한다. 여기서 마이크로패턴은 블록영상의 중간값에 기반한 국소이진패턴(local binary pattern : LBP)으로 추출되고, 추출된 국소이진패턴들 사이의 동시발생빈도를 고려하여 패턴인식을 수행한다. 중간값 이진패턴은 영상의 국소속성을 고려할 뿐만 아니라 잡음에 강건한 패턴분석을 위함이고, 동시발생빈도는 영상의 전역속성을 고려하여 인식성능을 좀 더 향상시키기 위함이다. 제안된 기법을 120*120 픽셀의 17개 RGB 질감 패턴영상을 대상으로 유클리디언(Euclidean) 거리에 기반한 실험결과, 우수한 인식성능이 있음을 확인하였다.

2진 패턴분류를 위한 신경망 해밍 MAXNET설계 (Neural Hamming MAXNET Design for Binary Pattern Classification)

  • 김대순;김환용
    • 전자공학회논문지B
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    • 제31B권12호
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    • pp.100-107
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    • 1994
  • This article describes the hardware design scheme of Hamming MAXNET algorithm which is appropriate for binary pattern classification with minimum HD measurement between stimulus vector and storage vector. Circuit integration is profitable to Hamming MAXNET because the structure of hamming network have a few connection nodes over the similar neuro-algorithms. Designed hardware is the two-layered structure composed of hamming network and MAXNET which enable the characteristics of low power consumption and fast operation with biline volgate sensing scheme. Proposed Hamming MAXNET hardware was designed as quantize-level converter for simulation, resulting in the expected binary pattern convergence property.

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Blur Detection through Multinomial Logistic Regression based Adaptive Threshold

  • Mahmood, Muhammad Tariq;Siddiqui, Shahbaz Ahmed;Choi, Young Kyu
    • 반도체디스플레이기술학회지
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    • 제18권4호
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    • pp.110-115
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    • 2019
  • Blur detection and segmentation play vital role in many computer vision applications. Among various methods, local binary pattern based methods provide reasonable blur detection results. However, in conventional local binary pattern based methods, the blur map is computed by using a fixed threshold irrespective of the type and level of blur. It may not be suitable for images with variations in imaging conditions and blur. In this paper we propose an effective method based on local binary pattern with adaptive threshold for blur detection. The adaptive threshold is computed based on the model learned through the multinomial logistic regression. The performance of the proposed method is evaluated using different datasets. The comparative analysis not only demonstrates the effectiveness of the proposed method but also exhibits it superiority over the existing methods.

지역적 이진패턴을 이용한 2차원 바코드 검출 알고리즘 (A 2-D Barcode Detection Algorithm based on Local Binary Patterns)

  • 최영규
    • 반도체디스플레이기술학회지
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    • 제8권2호
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    • pp.23-29
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    • 2009
  • To increase the data capacity of one-dimensional symbology, 2D barcodes have been proposed a decade ago. In this paper, a new 2D barcode detection algorithm based on Local Binary Pattern is presented. To locate 2D barcode symbols, a texture analysis scheme based on the Local Binary Pattern is adopted, and a gray-scale projection with sub-pixel operation is utilized to separate the symbol precisely from the input image. Finally, the segmented symbol is normalized using the inverse perspective transformation for the decoding process. The proposed method ensures high performances under various lighting/printing conditions and strong perspective deformations. Experiments show that our method is very robust and efficient in detecting the symbol area for the various types of 2D barcodes.

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이진 영상 워터마킹 알고리즘에 관한 연구 (A Study on Watermarking Algorithm for Binary Images)

  • 이덕;최종욱
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2003년도 춘계학술발표논문집 (하)
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    • pp.2189-2192
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    • 2003
  • 전자정부, 전자상거래의 활성화로 디지털 문서가 빠른 속도로 유통되고 있기에 이에 대한 효과적인 보호대책이 필요한 실정이다. 본 논문에서는 Window Pattern을 이용하여 Binary Image에 저작권 정보를 삽입하는 방안을 제안한다. 삽입대상 Window Pattern을 결정하고 이러한 Pattern으로 원본 영상을 Scan하면서 픽셀 값에 변화를 주게 된다. 이렇게 되어 하나의 Pattern에 1bit의 정보의 삽입이 가능하게 되고 추출 시 원본을 필요로 하지 않으며 실용성이 높고 적용분야도 넓다.

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