• Title/Summary/Keyword: ART2 algorithm

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A study on the Speaker Recognition using the Pitch (피치계수를 이용한 화자인식에 관한 연구)

  • 김에녹
    • Journal of the Korea Computer Industry Society
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    • v.2 no.4
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    • pp.471-480
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    • 2001
  • In this thesis, we perform the experiment of speaker recognition by identifying vowels in the pronunciation of each speaker using Adaptive Resource Theory 2(ART2) model. The 5 adult males and 5 adult females pronounce from 0 to 9 digits. We extract the vowels from the pronunciation of each speaker first, we are extracted characteristic coefficient through a pitch detection algorithm, a LPC analysis, and a LPC cepstral analysis to generate an input pattern of ART2. The experimental results showed that pitch coefficients are somewhat more enhanced than LPC or LPC cepstral coefficient.

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Container Image Recognition using ART2-based Self-Organizing Supervised Learning Algorithm (ART2 기반 자가 생성 지도 학습 알고리즘을 이용한 컨테이너 인식 시스템)

  • Jung, Byung-Hee;Kim, Jae-Yong;Cho, Jae-Hyun;Kim, Kwang-Baek
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.2
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    • pp.393-398
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    • 2005
  • 본 논문에서는 ART2 기반 자가 생성 지도 학습 알고리즘을 이용한 운송 컨테이너 식별자 인식 시스템을 제안한다. 일반적으로 운송 컨테이너의 식별자들은 글자의 색이 검정색 또는 흰색으로 이루어져 있는 특징이 있다. 이러한 특성을 고려하여 원 컨테이너 영상에 대해 검은색과 흰색을 제외한 모든 부분을 잡음으로 처리하기 위해 퍼지를 이용한 잡은 판단 방법을 적용하여 식별자 영역과 잡음을 구별한다. 식별자 영역을 제외한 잡음 영역을 전체 영상의 평균 픽셀값으로 대체시킨다. 그리고 Sobel 마스크를 이용하여 에지를 검출하고, 추출된 에지를 이용하여 수직 블록과 수평 블록을 검출하여 컨테이너의 식별자 영역을 추출하고 이진화한다. 이진화된 식별자 영역에 대해 검정색의 빈도수를 이용하여 흰바탕과 민바탕을 구분하고 8방향 윤곽선 추적 알고리즘을 적용하여 개별 식별자를 추출한다. 개별 식별자 인식을 위해 ART2 기반 자가 생성 지도 학습 알고리즘은 입력층과 은닉층 사이에 ART2를 적용하여 은닉층의 노드를 생성하고, 은닉층과 출력층 사이에 일반화된 델타 학습 방법과 Delta-bar-Delta 알고리즘을 적용하여 학습 성능을 개선한다. 실제 컨테이너 영상을 대상으로 실험한 결과, 기존의 식별자 추출 방법보다 제안된 식별자 추출 방법이 개선되었다. 그리고 기존의 식별자 인식 알고리즘보다 제안된 ART2 기반 자가 생성 지도 학습 알고리즘이 식별자의 학습 및 인식에 있어서 우수한 성능이 있음을 확인하였다.

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Minimum number of Vertex Guards Algorithm for Art Gallery Problem (화랑 문제의 최소 정점 경비원 수 알고리즘)

  • Lee, Sang-Un
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.6
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    • pp.179-186
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    • 2011
  • This paper suggests the minimum number of vertex guards algorithm. Given n rooms, the exact number of minimum vertex guards is proposed. However, only approximation algorithms are presented about the maximum number of vertex guards for polygon and orthogonal polygon without or with holes. Fisk suggests the maximum number of vertex guards for polygon with n vertices as follows. Firstly, you can triangulate with n-2 triangles. Secondly, 3-chromatic vertex coloring of every triangulation of a polygon. Thirdly, place guards at the vertices which have the minority color. This paper presents the minimum number of vertex guards using dominating set. Firstly, you can obtain the visibility graph which is connected all edges if two vertices can be visible each other. Secondly, you can obtain dominating set from visibility graph or visibility matrix. This algorithm applies various art galley problems. As a results, the proposed algorithm is simple and can be obtain the minimum number of vertex guards.

Automatic partial shape recognition system using adaptive resonance theory (적응공명이론에 의한 자동 부분형상 인식시스템)

  • 박영태;양진성
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.3
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    • pp.79-87
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    • 1996
  • A new method for recognizing and locating partially occluded or overlapped two-dimensional objects regardless of their size, translation, and rotation, is presented. Dominant points approximating occuluding contoures of objects are generated by finding local maxima of smoothed k-cosine function, and then used to guide the contour segment matching procedure. Primitives between the dominant points are produced by projecting the local contours onto the line between the dominant points. Robust classification of primitives. Which is crucial for reliable partial shape matching, is performed using adaptive resonance theory (ART2). The matched primitives having similar scale factors and rotation angles are detected in the hough space to identify the presence of the given model in the object scene. Finally the translation vector is estimated by minimizing the mean squred error of the matched contur segment pairs. This model-based matching algorithm may be used in diveerse factory automation applications since models can be added or changed simply by training ART2 adaptively without modifying the matching algorithm.

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Robust control using Analog Adaptive Resonance Theory

  • Son, Jun-Hyeok;Seo, Bo-Hyeok
    • Proceedings of the KIEE Conference
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    • 2006.04a
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    • pp.93-95
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    • 2006
  • In many control system applications, the system designed must not only satisfy the damping and accuracy specifications, but the control must also yield performance that is robust to external disturbance and parameter variations. We have shown that feedback in conventional control systems has the inherent ability of reducing the effects of external disturbance and parameter variations. Unfortunately, robustness with the conventional feedback configuration is achieved only with a high loop gain, which is normally detrimental to stability. The design of intelligent, autonomous machines to perform tasks that are dull, repetitive, hazardous, or that require skill, strength, or dexterity beyond the capability of humans is the ultimate goal of robotics research. This paper prove the robust control using Analog Adaptive Resonance Theorv(ART2) Algorithm about case study.

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A Fault Detection and Isolation Method for Ammunition Transport Automation System (탄약운반 자동화 시스템의 고장 검출 및 분류 기법)

  • Lee, Seung-Youn;Kang, Kil-Sun;Lyou, Joon
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.10
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    • pp.880-887
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    • 2005
  • This paper presents a fault diagnosis(detection and isolation) approach for the Ammunition Transport Automation system(ATAS). Due to limited time and information available during its cyclic operation, the on-line fault detection algorithm consists of sequential test logics referring to the normal states, which can be considered as a kind of expert system. If a failure were detected, the off-line isolation algorithm finds the fault location through trained ART2 neural network. By the results of simulations and some on-line field test, it has been shown that the presented approach is effective enough and applicable to related automation systems.

Sign Language Recognition Using ART2 Algorithm (ART2 알고리즘을 이용한 수화 인식)

  • Kim, Kwang-Baek;Woo, Young-Woon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.5
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    • pp.937-941
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    • 2008
  • People who have hearing difficulties use sign language as the most important communication method, and they can broaden personal relations and manage their everyday lives without inconvenience through sign language. But they suffer from absence of interpolation between normal people and people who have hearing difficulties in increasing video chatting or video communication services by recent growth of internet communication. In this paper, we proposed a sign language recognition method in order to solve such a problem. In the proposed method, regions of two hands are extracted by tracking of two hands using RGB, YUV and HSI color information from a sign language image acquired from a video camera and by removing noise in the segmented images. The extracted regions of two hands are teamed and recognized by ART2 algorithm that is robust for noise and damage. In the experiment by the proposed method and images of finger number from 1 to 10, we verified the proposed method recognize the numbers efficiently.

Insect Footprint Recognition using Trace Transform and a Fuzzy Method (Trace 변환과 펴지 기법을 이용한 곤충 발자국 인식)

  • Shin, Bok-Suk;Cha, Eui-Young;Woo, Young-Woon
    • Journal of Korea Multimedia Society
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    • v.11 no.11
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    • pp.1615-1623
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    • 2008
  • This paper proposes methods to classify scanned insect footprints. We propose improved SOM and ART2 algorithms for extracting segments, basic areas for feature extraction, and utilize Trace transform and fuzzy weighted mean methods for extracting feature values for classification of the footprints. In the proposed method, regions are extracted by a morphological method in the beginning, and then improved SOM and ART2 algorithms are utilized to extract segments regardless of kinds of insects. Next, A Trace transform method is used to find feature values suitable for various kinds of deformation of insect footprints. In the Trace transform method, Triple features from reconstructed combination of diverse functions, are used to classify the footprints. In general, it is very difficult to decide automatically whether the extracted footprint segment is meaningful for classification or not. So we use a fuzzy weighted mean method for not excluding uncertain footprint segments because the uncertain footprint segments may be possible candidates for classification. We present experimental results of footprint segment extraction and segment classification by the proposed methods.

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An Intelligent System for Recognition of Identifiers from Shipping Container Images using Fuzzy Binarization and Enhanced Hybrid Network

  • Kim, Kwang-Baek
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.3
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    • pp.349-356
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    • 2004
  • The automatic recognition of transport containers using image processing is very hard because of the irregular size and position of identifiers, diverse colors of background and identifiers, and the impaired shapes of identifiers caused by container damages and the bent surface of container, etc. In this paper we propose and evaluate a novel recognition algorithm for container identifiers that effectively overcomes these difficulties and recognizes identifiers from container images captured in various environments. The proposed algorithm, first, extracts the area containing only the identifiers from container images by using CANNY masking and bi-directional histogram method. The extracted identifier area is binarized by the fuzzy binarization method newly proposed in this paper. Then a contour tracking method is applied to the binarized area in order to extract the container identifiers which are the target for recognition. In this paper we also propose and apply a novel ART2-based hybrid network for recognition of container identifiers. The results of experiment for performance evaluation on the real container images showed that the proposed algorithm performs better for extraction and recognition of container identifiers compared to conventional algorithms.

A novel method for the vibration optimisation of structures subjected to dynamic loading

  • Munk, David J.;Vio, Gareth A.;Steven, Grant P.
    • Advances in aircraft and spacecraft science
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    • v.4 no.2
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    • pp.169-184
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    • 2017
  • The optimum design of structures with frequency constraints is of great importance in the aeronautical industry. In order to avoid severe vibration, it is necessary to shift the fundamental frequency of the structure away from the frequency range of the dynamic loading. This paper develops a novel topology optimisation method for optimising the fundamental frequencies of structures. The finite element dynamic eigenvalue problem is solved to derive the sensitivity function used for the optimisation criteria. An alternative material interpolation scheme is developed and applied to the optimisation problem. A novel level-set criteria and updating routine for the weighting factors is presented to determine the optimal topology. The optimisation algorithm is applied to a simple two-dimensional plane stress plate to verify the method. Optimisation for maximising a chosen frequency and maximising the gap between two frequencies are presented. This has the application of stiffness maximisation and flutter suppression. The results of the optimisation algorithm are compared with the state of the art in frequency topology optimisation. Test cases have shown that the algorithm produces similar topologies to the state of the art, verifying that the novel technique is suitable for frequency optimisation.