• 제목/요약/키워드: probabilistic matching

검색결과 43건 처리시간 0.025초

Probabilistic Model for Performance Analysis of a Heuristic with Multi-byte Suffix Matching

  • Choi, Yoon-Ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권4호
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    • pp.711-725
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    • 2013
  • A heuristic with multi-byte suffix matching plays an important role in real pattern matching algorithms. By skipping many characters at a time in the process of comparing a given pattern with the text, the pattern matching algorithm based on a heuristic with multi-byte suffix matching shows a faster average search time than algorithms based on deterministic finite automata. Based on various experimental results and simulations, the previous works show that the pattern matching algorithms with multi-byte suffix matching performs well. However, there have been limited studies on the mathematical model for analyzing the performance in a standard manner. In this paper, we propose a new probabilistic model, which evaluates the performance of a heuristic with multi-byte suffix matching in an average-case search. When the theoretical analysis results and experimental results were compared, the proposed probabilistic model was found to be sufficient for evaluating the performance of a heuristic with suffix matching in the real pattern matching algorithms.

신뢰성 높은 위치 인식을 위하여 방향을 고려한 확률적 스캔 매칭 기법 (Direction Augmented Probabilistic Scan Matching for Reliable Localization)

  • 최민용;최진우;정완균
    • 제어로봇시스템학회논문지
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    • 제17권12호
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    • pp.1234-1239
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    • 2011
  • The scan matching is widely used in localization and mapping of mobile robots. This paper presents a probabilistic scan matching method. To improve the performance of the scan matching, a direction of data point is incorporated into the scan matching. The direction of data point is calculated using the line fitted by the neighborhood data. Owing to the incorporation, the performance of the matching was improved. The number of iterations in the scan matching decreased, and the tolerance against a high rotation between scans increased. Based on real data of a laser range finder, experiments verified the performance of the proposed direction augmented probabilistic scan matching algorithm.

A Probabilistic Dissimilarity Matching for the DFT-Domain Image Hashing

  • Seo, Jin S.;Jo, Myung-Suk
    • International Journal of Advanced Culture Technology
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    • 제5권1호
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    • pp.76-82
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    • 2017
  • An image hash, a discriminative and robust summary of an image, should be robust against quality-preserving signal processing steps, while being pairwise independent for perceptually different inputs. In order to improve the hash matching performance, this paper proposes a probabilistic dissimilarity matching. Instead of extracting the binary hash from the query image, we compute the probability that the intermediate hash vector of the query image belongs to each quantization bin, which is referred to as soft quantization binning. The probability is used as a weight in comparing the binary hash of the query with that stored in a database. A performance evaluation over sets of image distortions shows that the proposed probabilistic matching method effectively improves the hash matching performance as compared with the conventional Hamming distance.

실내 환경 이미지 매칭을 위한 GMM-KL프레임워크 (GMM-KL Framework for Indoor Scene Matching)

  • Kim, Jun-Young;Ko, Han-Seok
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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    • pp.61-63
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    • 2005
  • Retreiving indoor scene reference image from database using visual information is important issue in Robot Navigation. Scene matching problem in navigation robot is not easy because input image that is taken in navigation process is affinly distorted. We represent probabilistic framework for the feature matching between features in input image and features in database reference images to guarantee robust scene matching efficiency. By reconstructing probabilistic scene matching framework we get a higher precision than the existing feaure-feature matching scheme. To construct probabilistic framework we represent each image as Gaussian Mixture Model using Expectation Maximization algorithm using SIFT(Scale Invariant Feature Transform).

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확률적 확산을 이용한 스테레오 정합 알고리듬 (New stereo matching algorithm based on probabilistic diffusion)

  • 이상화;이충웅
    • 전자공학회논문지S
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    • 제35S권4호
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    • pp.105-117
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    • 1998
  • In this paper, the general formula of disparity estimation based on Bayesian Maximum A Posteriori (MAP) algorithm is derived and implemented with simplified probabilistic models. The probabilistic models are independence and similarity among the neighboring disparities in the configuration.The formula is the generalized probabilistic diffusion equation based on Bayesian model, and can be implemented into the some different forms corresponding to the probabilistic models in the disparity neighborhood system or configuration. And, we proposed new probabilistic models in order to simplify the joint probability distribution of disparities in the configuration. According to the experimental results, the proposed algorithm outperformed the other ones, such as sum of swuared difference(SSD) based algorithm and Scharstein's method. We canconclude that the derived formular generalizes the probabilistic diffusion based on Bayesian MAP algorithm for disparity estimation, and the propsoed probabilistic models are reasonable and approximate the pure joint probability distribution very well with decreasing the computations to 0.01% of the generalized formula.

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희소 신호의 복원을 위한 확률적 배제 기반의 직교 정합 추구 알고리듬 (Probabilistic Exclusion Based Orthogonal Matching Pursuit Algorithm for Sparse Signal Reconstruction)

  • 김시현
    • 전기전자학회논문지
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    • 제17권3호
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    • pp.339-345
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    • 2013
  • 본 논문에서는 희소한 신호의 압축센싱를 위해 확률적 배제에 기반한 직교정합추구 (PEOMP) 신호 복원 알고리듬을 제안하였다. CoSaMP, gOMP, BAOMP 등의 알고리듬들은 매 반복 단계에서 새로운 atom들을 support set에 추가할 뿐만 아니라 부적절하다고 판단되어지는 atom들은 삭제하기 때문에 우수한 신호 복원 성능을 보인다. 그러나 반복 과정 중에 support set의 구성이 국소 최저점에서 벗어나지 못하여 신호 복원에 실패하는 경우가 발생하는 단점을 가지고 있다. 제안된 알고리듬은 매 반복 단계에서 확률적으로 임의의 atom을 배제하여 support set이 국소 최저점에 빠져 있는 경우 그곳에서 탈출하는데 도움을 준다. 모의실험을 통해 PEOMP가 기존의 OMP 기반의 알고리듬들과 $l_1$ 최적화 방법보다 신호 복원 능력 관점에서 우수한 성능을 보임을 확인하였다.

입력 단 저장 방식 ATM 스위치의 예약 대역폭에 기반 한 셀 스케쥴링 알고리듬 (A Reserved Band-Based Probabilistic Cell Scheduling Algorithm for Input Buffered ATM Switches)

  • 이영근;김진상;김진상
    • 한국통신학회논문지
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    • 제25권1A호
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    • pp.114-121
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    • 2000
  • 입력 단 저장방식의 스위치는 최대 수율을 제한하는 HOL(Head-of-line) 블록킹이라는 단점을 지니고 있지만 구현의 간단함을 지닌다는 장점이 있다. 그러나 현재 VOQ(Virtual Output Queueing) 기술을 이용하면 입력 단 저장방식의 스위치에서 보이는 HOL 블록킹에서 완전히 벗어날 수 있어 간단한 구조로 높은 수율을 얻을 수 있게 된다. 본 논문에서 입력 단 저장방식의 ATM 스위치를 위한 새로운 셀 스케쥴링 알고리듬 PPIM(Probabilistic Parallel Iterative Matching)을 제안 한다. 제안된 새로운 알고리듬은 예약 대역폭에 비례하는 가중치를 각각의 입력-출력 링크에 부여함으로써, 기존의 PIM(Parallel Iterative Matching)이 제공하지 못하는 예약된 전송률 보장이 가능하게 한다. 이 알고리듬을 이용한 ATM 스위치는 높은 수율과 낮은 지연 값뿐만 아니라 지터 성능에 있어 기존의 WPIM(Weighted PIM)에 비해 더욱 향상된 성능을 보여준다.

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Probabilistic localization of the service robot by mapmatching algorithm

  • Lee, Dong-Heui;Woojin Chung;Kim, Munsang
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2002년도 ICCAS
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    • pp.92.3-92
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    • 2002
  • A lot of localization algorithms have been developed in order to achieve autonomous navigation. However, most of localization algorithms are restricted to certain conditions. In this paper, Monte Carlo localization scheme with a map-matching algorithm is suggested as a robust localization method for the Public Service Robot to accomplish its tasks autonomously. Monte Carlo localization can be applied to local, global and kidnapping localization problems. A range image based measure function and a geometric pattern matching measure function are applied for map matching algorithm. This map matching method can be applied to both polygonal environments and un-polygonal environments and achieves...

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음소인식 오류에 강인한 N-gram 기반 음성 문서 검색 (N-gram Based Robust Spoken Document Retrievals for Phoneme Recognition Errors)

  • 이수장;박경미;오영환
    • 대한음성학회지:말소리
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    • 제67호
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    • pp.149-166
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    • 2008
  • In spoken document retrievals (SDR), subword (typically phonemes) indexing term is used to avoid the out-of-vocabulary (OOV) problem. It makes the indexing and retrieval process independent from any vocabulary. It also requires a small corpus to train the acoustic model. However, subword indexing term approach has a major drawback. It shows higher word error rates than the large vocabulary continuous speech recognition (LVCSR) system. In this paper, we propose an probabilistic slot detection and n-gram based string matching method for phone based spoken document retrievals to overcome high error rates of phone recognizer. Experimental results have shown 9.25% relative improvement in the mean average precision (mAP) with 1.7 times speed up in comparison with the baseline system.

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Statistical Error Compensation Techniques for Spectral Quantization

  • Choi, Seung-Ho;Kim, Hong-Kook
    • 음성과학
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    • 제11권4호
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    • pp.17-28
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    • 2004
  • In this paper, we propose a statistical approach to improve the performance of spectral quantization of speech coders. The proposed techniques compensate for the distortion in a decoded line spectrum pairs (LSP) vector based on a statistical mapping function between a decoded LSP vector and its corresponding original LSP vector. We first develop two codebook-based probabilistic matching (CBPM) methods based on linear mapping functions according to different assumption of distribution of LSP vectors. In addition, we propose an iterative procedure for the two CBPMs. We apply the proposed techniques to a predictive vector quantizer used for the IS-641 speech coder. The experimental results show that the proposed techniques reduce average spectral distortion by around 0.064dB.

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