• Title/Summary/Keyword: Patten Recognition

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Similarity Measurement Using Open-Ball Scheme for 2D Patterns in Comparison with Moment Invariant Method (Open-Ball Scheme을 이용한 2D 패턴의 상대적 닮음 정도 측정의 Moment Invariant Method와의 비교)

  • Kim, Seong-Su
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.1
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    • pp.76-81
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    • 1999
  • The degree of relative similarity between 2D patterns is obtained using Open-Ball Scheme. Open-Ball Scheme employs a method of transforming the geometrical information on 3D objects or 2D patterns into the features to measure the relative similarity for object(patten) recognition, with invariance on scale, rotation, and translation. The feature of an object is used to obtain the relative similarity and mapped into [0, 1] the interval of real line. For decades, Moment-Invariant Method has been used as one of the excellent methods for pattern classification and object recognition. Open-Ball Scheme uses the geometrical structure of patterns while Moment Invariant Method uses the statistical characteristics. Open-Ball Scheme is compared to Moment Invariant Method with respect to the way that it interprets two-dimensional patten classification, especially the paradigms are compared by the degree of closeness to human's intuitive understanding. Finally the effectiveness of the proposed Open-Ball Scheme is illustrated through simulations.

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Combining Different Distance Measurements Methods with Dempster-Shafer-Theory for Recognition of Urdu Character Script

  • Khan, Yunus;Nagar, Chetan;Kaushal, Devendra S.
    • International Journal of Ocean System Engineering
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    • v.2 no.1
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    • pp.16-23
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    • 2012
  • In this paper we discussed a new methodology for Urdu Character Recognition system using Dempster-Shafer theory which can powerfully estimate the similarity ratings between a recognized character and sampling characters in the character database. Recognition of character is done by five probability calculation methods such as (similarity, hamming, linear correlation, cross-correlation, nearest neighbor) with Dempster-Shafer theory of belief functions. The main objective of this paper is to Recognition of Urdu letters and numerals through five similarity and dissimilarity algorithms to find the similarity between the given image and the standard template in the character recognition system. In this paper we develop a method to combine the results of the different distance measurement methods using the Dempster-Shafer theory. This idea enables us to obtain a single precision result. It was observed that the combination of these results ultimately enhanced the success rate.

A Study on Voice Recognition using Noise Cancel DTW for Noise Environment (잡음환경에서의 Noise Cancel DTW를 이용한 음성인식에 관한 연구)

  • Ahn, Jong-Young;Kim, Sung-Su;Kim, Su-Hoon;Koh, Si-Young;Hur, Kang-In
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.11 no.4
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    • pp.181-186
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    • 2011
  • In this paper, we propose the Noise Cancel DTW that to use a kind of feature compensation. This method is not to use estimated noise but we use real life environment noise data for Voice Recognition. And we applied this contaminated data for recognition reference model that suitable for noise environment. NCDTW is combined with surround noise when generating reference patten. We improved voice recognition rate at mobile environment to use NCDTW.

A study on Voice Recognition using Model Adaptation HMM for Mobile Environment (모델적응 HMM을 이용한 모바일환경에서의 음성인식에 관한 연구)

  • Ahn, Jong-Young;Kim, Sang-Bum;Kim, Su-Hoon;Hur, Kang-In
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.11 no.3
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    • pp.175-179
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    • 2011
  • In this paper, we propose the MA(Model Adaption) HMM that to use speech enhancement and feature compensation. Normally voice reference data is not consider for real noise data. This method is not to use estimated noise but we use real life environment noise data. And we applied this contaminated data for recognition reference model that suitable for noise environment. MAHMM is combined with surround noise when generating reference patten. We improved voice recognition rate at mobile environment to use MAHMM.

Design of 2D face recognition security planning to vulnerability (2차원 안면인식의 취약성 보안 방안 설계)

  • Lee, Jaeung;Jang, Jong-wook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.05a
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    • pp.243-245
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    • 2017
  • In the face recognition technology, which has been studied a lot, the security of the face recognition technology is improved by receiving the depth data as a weak point for the 2D. In this paper, we expect the effect of cost reduction by enhancing the security of 2D by taking new features of eye flicker that each person possesses as new data information.

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A study on the Automatic Recognition of Hand Printed Hangeul patterns by the Computer (전자계산기에 의한 필기체 한글 인식에 관한 연구)

  • 남궁재찬;김영건
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.5 no.1
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    • pp.44-48
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    • 1980
  • This paper proposes a method of the automatic recognition of the handprinted Hanguel patterns. A certain pattern oriented basic letters is normalized to the prototype Hanguel patten by the linking compansation and nomalization algorithm. Tree grammar is used in recognition process. Compared with the previous method. automata processing is simplified and the error is reduced by the new parsing method. This method shows the effectiveness for the constrained pattern. We expect that the new parsing method is very useful for the on-line pattern recognition.

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Speech Emotion Recognition by Speech Signals on a Simulated Intelligent Robot (모의 지능로봇에서 음성신호에 의한 감정인식)

  • Jang, Kwang-Dong;Kwon, Oh-Wook
    • Proceedings of the KSPS conference
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    • 2005.11a
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    • pp.163-166
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    • 2005
  • We propose a speech emotion recognition method for natural human-robot interface. In the proposed method, emotion is classified into 6 classes: Angry, bored, happy, neutral, sad and surprised. Features for an input utterance are extracted from statistics of phonetic and prosodic information. Phonetic information includes log energy, shimmer, formant frequencies, and Teager energy; Prosodic information includes pitch, jitter, duration, and rate of speech. Finally a patten classifier based on Gaussian support vector machines decides the emotion class of the utterance. We record speech commands and dialogs uttered at 2m away from microphones in 5different directions. Experimental results show that the proposed method yields 59% classification accuracy while human classifiers give about 50%accuracy, which confirms that the proposed method achieves performance comparable to a human.

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Convergent Properties of Fuzzy Spheres (퍼지 구의 수렴성질)

  • Kim, Mi-Hye;Kim, Tea-Soo;Kim, Mi-Suk
    • The Journal of the Korea Contents Association
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    • v.3 no.4
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    • pp.103-110
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    • 2003
  • In this paper, we investigate the properties of fuzzy spheres and estabilish convergence theorems of them. We expect that convergence theorems of fuzzy spheres may be useful for computer graphics and patten recognition.

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Machine Fault Diagnosis Method based on DWT Power Spectral Density using Multi Patten Recognition (다중 패턴 인식 기법을 이용한 DWT 전력 스펙트럼 밀도 기반 기계 고장 진단 기법)

  • Kang, Kyung-Won;Lee, Kyeong-Min;Vununu, Caleb;Kwon, Ki-Ryong
    • Journal of Korea Multimedia Society
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    • v.22 no.11
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    • pp.1233-1241
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    • 2019
  • The goal of the sound-based mechanical fault diagnosis technique is to automatically find abnormal signals in the machine using acoustic emission. Conventional methods of using mathematical models have been found to be inaccurate due to the complexity of industrial mechanical systems and the existence of nonlinear factors such as noise. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose an automatic fault diagnosis method using discrete wavelet transform and power spectrum density using multi pattern recognition. First, we perform DWT-based filtering analysis for noise cancelling and effective feature extraction. Next, the power spectral density(PSD) is performed on each subband of the DWT in order to effectively extract feature vectors of sound. Finally, each PSD data is extracted with the features of the classifier using multi pattern recognition. The results show that the proposed method can not only be used effectively to detect faults as well as apply to various automatic diagnosis system based on sound.

Customized Pattern-Recognition Technique using Vision Measurement System Development in New Car Manufacturing Process (패턴인식 기법을 적용한 신차 제조공정 맞춤식 비젼 계측시스템 개발)

  • Lee, Gyung-Il;Kim, Jae-yeol;Roh, Chi-sung;Choi, Choul Jun
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.15 no.4
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    • pp.51-59
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    • 2016
  • Measurements of the automobile manufacturers are available anywhere and anytime, directly based on the criterion of failure is measured. The maintenance of high-precision production activities is direct evidence of the fact that competitive manufacturing activities are very important in determining the success of companies to recall defective starting from raw material costs. The current manufacturing sites produce calipers and clearance gauge the degree of tool only specific. Therefore, judging the quality, including the number of errors, requires a lot of attention to the dimension failures in day-to-day measurements and measurement tasks and duties repeated in difficult situations. In this paper, we aim to develop a vehicle manufacturing plant site using each of the manufacturing processes while operating a measurement tool. We display it using the Image Processing PC-based S/W with all those visual facts by management and recorded as image information a more accurate and current situation to obtain information and share visual measurements. We carry out research on the design and development vision inspection algorithm applied for pattern-recognition techniques that can help manufacturing site quality control.