• 제목/요약/키워드: Pattern recognition algorithm

검색결과 766건 처리시간 0.027초

Iris Pattern Recognition Using the DFT Coefficients (DFT계수를 이용한 홍채 인식)

  • 고현주;전명근
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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    • pp.237-240
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    • 2001
  • In this work, we will present an iris pattern recognition method as a biometrically based technology for personal identification and authentication. For this, we propose a new algorithm for extraction unique feature from images of the iris of the human eye and representing these feature using the discrete fourier transform. From the computational simplicity of the adopted transform, we can obtain more fast and efficient results than previous ones.

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Neural-Network and Log-Polar Sampling Based Associative Pattern Recognizer for Aircraft Images (신경 회로망과 Log-Polar Sampling 기법을 사용한 항공기 영상의 연상 연식)

  • 김종오;김인철;진성일
    • Journal of the Korean Institute of Telematics and Electronics B
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    • 제28B권12호
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    • pp.59-67
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    • 1991
  • In this paper, we aimed to develop associative pattern recognizer based on neural network for aircraft identification. For obtaining invariant feature space description of an object regardless of its scale change and rotation, Log-polar sampling technique recently developed partly due to its similarity to the human visual system was introduced with Fourier transform post-processing. In addition to the recognition results, image recall was associatively performed and also used for the visualization of the recognition reliability. The multilayer perceptron model was learned by backpropagation algorithm.

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Pattern Classification Algorithm for Wrist Movements based on EMG (근전도 신호 기반 손목 움직임 패턴 분류 알고리즘에 대한 연구)

  • Cui, H.D.;Kim, Y.H.;Shim, H.M.;Yoon, K.S.;Lee, S.M.
    • Journal of rehabilitation welfare engineering & assistive technology
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    • 제7권2호
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    • pp.69-74
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    • 2013
  • In this paper, we propose the pattern classification algorithm of recognizing wrist movements based on electromyogram(EMG) to raise the recognition rate. We consider 30 characteristics of EMG signals wirh the root mean square(RMS) and the difference absolute standard deviation value(DASDV) for the extraction of precise features from EMG signals. To get the groups of each wrist movement, we estimated 2-dimension features. On this basis, we divide each group into two parts with mean to compare and promote the recognition rate of pattern classification effectively. For the motion classification based on EMG, the k-nearest neighbor(k-NN) is used. In this paper, the recognition rate is 92.59% and 0.84% higher than the study before.

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Optimized Multi-Output Fuzzy Neural Networks Based on Interval Type-2 Fuzzy Set for Pattern Recognition (패턴 인식을 위한 Interval Type-2 퍼지 집합 기반의 최적 다중출력 퍼지 뉴럴 네트워크)

  • Park, Keon-Jun;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • 제62권5호
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    • pp.705-711
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    • 2013
  • In this paper, we introduce an design of multi-output fuzzy neural networks based on Interval Type-2 fuzzy set. The proposed Interval Type-2 fuzzy set-based fuzzy neural networks with multi-output (IT2FS-based FNNm) comprise the network structure generated by dividing the input space individually. The premise part of the fuzzy rules of the network reflects the individuality of the division space for the entire input space and the consequent part of the fuzzy rules expresses three types of polynomial functions with interval sets such as constant, linear, and modified quadratic inference for pattern recognition. The learning of fuzzy neural networks is realized by adjusting connections of the neurons in the consequent part of the fuzzy rules, and it follows a back-propagation algorithm. In addition, in order to optimize the network, the parameters of the network such as apexes of membership functions, uncertainty factor, learning rate and momentum coefficient were automatically optimized by using real-coded genetic algorithm. The proposed model is evaluated with the use of numerical experimentation.

Pattern Recognition using Feature Feedback : Performance Evaluation for Feature Mask (특징되먹임을 이용한 패턴인식 : 특징마스크 검증을 통한 특징되먹임 성능분석)

  • Kim, Su-Hyun;Choi, Sang-Il;Bae, Sung-Han;Lee, Young-Dae;Jeong, Gu-Min
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • 제10권5호
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    • pp.179-185
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    • 2010
  • In this paper, we present a performance evaluation for face recognition algorithm using feature feedback according to the Feature mask. In the face recognition method using feature feedback, important region is extracted from original data set by using the reverse mapping from the extracted features to the original space. In this paper, we evaluate the performance of feature feedback according to shape of Feature Mask for Yale data. Comparing the result using Important part and unimportant part, we show the validity and applicability of the pattern recognition method based on feature feedback.

An Application of a Parallel Algorithm on an Image Recognition

  • Baik, Ran
    • Journal of Multimedia Information System
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    • 제4권4호
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    • pp.219-224
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    • 2017
  • This paper is to introduce an application of face recognition algorithm in parallel. We have experiments of 25 images with different motions and simulated the image recognitions; grouping of the image vectors, image normalization, calculating average image vectors, etc. We also discuss an analysis of the related eigen-image vectors and a parallel algorithm. To develop the parallel algorithm, we propose a new type of initial matrices for eigenvalue problem. If A is a symmetric matrix, initial matrices for eigen value problem are investigated: the "optimal" one, which minimize ${\parallel}C-A{\parallel}_F$ and the "super optimal", which minimize ${\parallel}I-C^{-1}A{\parallel}_F$. In this paper, we present a general new approach to the design of an initial matrices to solving eigenvalue problem based on the new optimal investigating C with preserving the characteristic of the given matrix A. Fast all resulting can be inverted via fast transform algorithms with O(N log N) operations.

Proposal of Image Detection Algorithm to Implement Hand Gestures

  • Woo, Eun-Ju;Moon, Yu-Sung;Choi, Ung-Se;Kim, Jung-Won
    • Journal of IKEEE
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    • 제22권4호
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    • pp.1222-1225
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    • 2018
  • This paper proposes an image detection algorithm to implement gesture. By using a camera sensor, the performance of the extracted image algorithm based on the gesture pattern was verified through experiments. In addition, through the experiments, we confirmed the proposed method's possibility of the implementation. For efficient image detection, we applied a segmentation technique based on image transition which divides into small units. To improve gesture recognition, the proposed method not only has high recognition rate and low false acceptance rate in real gesture environment, but also designed an algorithm that efficiently finds optimal thresholds that can be applied.

A Study on Face Recognition Method based on Binary Pattern Image under Varying Lighting Condition (조명 변화 환경에서 이진패턴 영상을 이용한 얼굴인식 방법에 관한 연구)

  • Kim, Dong-Ju;Sohn, Myoung-Kyu;Lee, Sang-Heon
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • 제49권2호
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    • pp.61-74
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    • 2012
  • In this paper, we propose a illumination-robust face recognition system using MCS-LBP and 2D-PCA algorithm. A binary pattern transform which has been used in the field of the face recognition and facial expression, has a characteristic of robust to illumination. Thus, this paper propose MCS-LBP which is more robust to illumination than previous LBP, and face recognition system fusing 2D-PCA algorithm. The performance evaluation of proposed system was performed by using various binary pattern images and well-known face recognition features such as PCA, LDA, 2D-PCA and ULBP histogram of gabor images. In the process of performance evaluation, we used a YaleB face database, an extended YaleB face database, and a CMU-PIE face database that are constructed under varying lighting condition, and the proposed system which consists of MCS-LBP image and 2D-PCA feature show the best recognition accuracy.

A Novel Algorithm for Dot Pattern Recognition with Reading Pen (펜학습기의 도트 패턴 인식을 위한 새로운 알고리즘)

  • Park, Hye-bin;Joung, Jinoo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • 제17권5호
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    • pp.165-171
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    • 2017
  • Reading Pen is used mostly in educational purpose, yet its possibility is great as an input device for various IT devices. Reading Pen recognizes tiny dot patterns printed in papers, converts the patterns to corresponding codes, and plays audio contents that match the codes. Recognizing dot patterns and converting to the codes are the main function of Reading Pens, on which we focus and propose a novel algorithm. Such technology is never open to public and this paper is the first open attempt in this area. We test the algorithm and obtain 85% recognition ratio.

Review on Genetic Algorithms for Pattern Recognition (패턴 인식을 위한 유전 알고리즘의 개관)

  • Oh, Il-Seok
    • The Journal of the Korea Contents Association
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    • 제7권1호
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    • pp.58-64
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    • 2007
  • In pattern recognition field, there are many optimization problems having exponential search spaces. To solve of sequential search algorithms seeking sub-optimal solutions have been used. The algorithms have limitations of stopping at local optimums. Recently lots of researches attempt to solve the problems using genetic algorithms. This paper explains the huge search spaces of typical problems such as feature selection, classifier ensemble selection, neural network pruning, and clustering, and it reviews the genetic algorithms for solving them. Additionally we present several subjects worthy of noting as future researches.