• Title/Summary/Keyword: recognition-rate

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A Parallel Thinning Algorithm by the 8-Neighbors Connectivity Value (8-이웃 연결값에 의한 병렬세선화 알고리즘)

  • Won, Nam-Sik;Son, Yoon-Koo
    • The Transactions of the Korea Information Processing Society
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    • v.2 no.5
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    • pp.701-710
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    • 1995
  • A thinning algorithm is a very important procedure in order to increase recognition rate in the character recognition. This paper is the study of a parallel thinning algorithm available for the recognition of various characters, and it proposes the parallel thinning algorithm using the 8-neighbors connectivity value. Characteristics of the proposed algorithm are easiness of implementation of parallelism, the result of thinning is perfectly-8 connectivity and represented by numeric information. The proposed algorithm is very suitable for characters having many curve segments such as English, Japanese etc. Performance evaluation was performed by the measure of similarity to reference skeleton.

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Aging Diagnosis of Model Coil of HV Induction Motor Using HFPD and Neural Networks (HFPD 및 신경회로망을 이용한 고압 유도전동기 모델코일 열화진단)

  • Kim, Deok-Geun;Im, Jang-Seop;Yeo, In-Seon
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.51 no.8
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    • pp.361-367
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    • 2002
  • Many failures in high voltage equipment are preceded by partial discharge activity. In this paper deals with the application of the high frequency partial discharge measurement technique in motorette. HFPD measurement is very effective method to detect the PD occurred in motorette which is the called name of test specimen for accelerating test of stator winding[1] In this study, CT type HFPD sensor is used to detect the partial discharges and a measured HFPD pattern is analyzed by fractal mathematics. The neural network algorithm is used to pattern recognition and ageing diagnosis. As a result of this study, the fractal dimensions are increased along to applied voltage and HFPD pattern recognition using neural network shown excellent recognition rate. Also, the ageing diagnosis of motorette has been Possible.

Implementation of recognition system on extracting inferior goods of radiation fin (방열판 불량품 추출을 위한 식별 시스템 구현)

  • Sim, Woo-Sung;Huh, Do-Geun;Lee, Yong-Sik
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.1
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    • pp.91-97
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    • 2000
  • In this paper, the illuminator is designed to recognize the shape and the existence of holes of radiation fin in the point that the light reflection characteristics are different according to the roughness of the material. The threshold value, the positions of holes and the black pixel nembers in the positon are obtained under the illuminator, in accordance with the reference image, by applying binary conversion and hole segmentation algorithm, as they are suggested in this paper, The existence and shape of hole are recognized by calculating the distance and feature value in the test image, which is obtained from the parameters of reference image. It is programmed to apply to GUI(Graphic User the Interface) in windows. More than 98% of recognition rate is shown, as it is applied to three different sizes of the radiation fin.

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A Study on an Optical Pattern Recognition Via the Radon Transform (라돈변환을 통한 광 패턴인식에 관한 연구)

  • Pan, Jae-Kyung;Kim, Nam;Park, Han-Kyu
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.24 no.5
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    • pp.880-886
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    • 1987
  • This paper proposes a new pattern recognition system using Radon transform and analyzes the performances of the system for given input patterns. The proposed system uses many optical parts in order to utilize the high speed characteristics of light and processes a signal easily by transforming 2-D image into a 1-D signal to increase flexibility. The squared Mahalanobis distance obtained from means and standard deviations of the features for the given input patterns is used for discrimination. As a result, this system represents a better recognition rate than any other systems using the same input patterns.

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Back-Propagation Algorithm through Omitting Redundant Learning (중복 학습 방지에 의한 역전파 학습 알고리듬)

  • 백준호;김유신;손경식
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.9
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    • pp.68-75
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    • 1992
  • In this paper the back-propagation algorithm through omitting redundant learning has been proposed to improve learning speed. The proposed algorithm has been applied to XOR, Parity check and pattern recognition of hand-written numbers. The decrease of the number of patterns to be learned has been confirmed as learning proceeds even in early learning stage. The learning speed in pattern recognition of hand-written numbers is improved more than 2 times in various cases of hidden neuron numbers. It is observed that the improvement of learning speed becomes better as the number of patterns and the number of hidden numbers increase. The recognition rate of the proposed algorithm is nearly the same as that conventional method.

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A Study on the Highly Accurate Korean Character Recognition Algorithm, by analyzing Vowel and Consonant Models - Selectiong of candidates using pattern matching method and discriminating similar characters by structural analysis - (자. 모 해석적 모델에 의한 고정도 한글 인식 알고리즘에 관한 연구 - 패턴정합법에 기초한 후보문자 선정 및 구조해석적인 방법에 의한 유사문자 판별 -)

  • 강선미;김봉석;김덕진
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.7
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    • pp.24-30
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    • 1993
  • In this paper, a new method is proposed to recognize a character from its similar characters, which are selected by pattern matching method in Korean character recognition. This new method, which couples the merits of already suggested methods, can choose the character to be in the candidate set and discriminate it from the others correctly. To evaluate performance of this algorithm, we used 15 kinds of different laser printer fonts and obtained about 97% of recognition rate.

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Noise removal algorithm for intelligent service robots in the high noise level environment (원거리 음성인식 시스템의 잡음 제거 기법에 대한 연구)

  • Woo, Sung-Min;Lee, Sang-Hoon;Jeong, Hong
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.413-414
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    • 2007
  • Successful speech recognition in noisy environments for intelligent robots depends on the performance of preprocessing elements employed. We propose an architecture that effectively combines adaptive beamforming (ABF) and blind source separation (BSS) algorithms in the spatial domain to avoid permutation ambiguity and heavy computational complexity. We evaluated the structure and assessed its performance with a DSP module. The experimental results of speech recognition test shows that the proposed combined system guarantees high speech recognition rate in the noisy environment and better performance than the ABF and BSS system.

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Group Separation Anti-collision Algorithm for RFID Tag Recognition (효율적인 RFID 태그의 인식을 위한 Group Separation 충돌 방지 알고리즘 개발)

  • Lee, Hyun-Soo;Ko, Young-Eun;Bang, Sung-Il
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.29-30
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    • 2007
  • In this paper, we propose Group Separation(GS) algorithm for RFID tag recognition. In GS algorithm, reader calculates tag ID by collision point, stores memory with the collision table. And reader classifies according to total number of tag ID's 1, requests each group. If tag comes into collision with the other tag, reader searches tag ID in collision table. As a result, we observes that transmitted data rate, the recognition time is decreased.

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Mongolian Traditional Stamp Recognition using Scalable kNN

  • Gantuya., P;Mungunshagai., B;Suvdaa., B
    • International journal of advanced smart convergence
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    • v.4 no.2
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    • pp.170-176
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    • 2015
  • The stamp is one of the crucial information of traditional historical and cultural for nations. In this paper, we purpose to detect official stamps from scanned document and recognize the Mongolian traditional, historical stamps. Therefore we performed following steps: first, we detect official stamps from scanned document based on red-color segmentation and document standard. Then we collected 234 traditional stamp images with 6 classes and 100 official stamp images from scanned document images. Also we implemented the processing algorithms for noise removing, resize and reshape etc. Finally, we proposed a new scale invariant classification algorithm based on KNN (k-nearest neighbor). In the experimental result, our proposed a method had shown proper recognition rate.

The Learning of the Neural Network Using Hadamard Transform

  • Katayama, Hiromu;Tsuruta, Shinchi;Nakao, Tomohiro;Harada, Hisamochi;Konishi, Ryosuke
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1125-1128
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    • 1993
  • We propose the new method about the neural-based pattern recognition by using Hadamard transform for the improvement of learning speed, stability and flexibility of network. We can obtain the spatial feature of pattern by Hadamard transformed pattern. We carried out an experiment to estimate the effect of Hadamard transform. We tried the learning of numeric patterns, and tried the pattern recognition with noisy pattern. As a result, the learning times of the network for the 'Hadamard' case is smaller than that of usual case. And the recognition rate of the network for the 'Hadamard' case is higher than that of usual case, too.

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