• Title/Summary/Keyword: Automatic Recognition

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Simulation of Ladar Range Images based on Linear FM Signal Analysis (Linear FM 신호분석을 통한 Ladar Range 영상의 시뮬레이션)

  • Min, Seong-Hong;Kim, Seong-Joon;Lee, Im-Pyeong
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.2
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    • pp.87-95
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    • 2008
  • Ladar (Laser Detection And Ranging, Lidar) is a sensor to acquire precise distances to the surfaces of target region using laser signals, which can be suitably applied to ATD (Automatic Target Detection) for guided missiles or aerial vehicles recently. It provides a range image in which each measured distance is expressed as the brightness of the corresponding pixel. Since the precise 3D models can be generated from the Ladar range image, more robust identification and recognition of the targets can be possible. If we simulate the data of Ladar sensor, we can efficiently use this simulator to design and develop Ladar sensors and systems and to develop the data processing algorithm. The purposes of this study are thus to simulate the signals of a Ladar sensor based on linear frequency modulation and to create range images from the simulated Ladar signals. We first simulated the laser signals of a Ladar using FM chirp modulator and then computed the distances from the sensor to a target using the FFT process of the simulated signals. Finally, we created the range image using the distances set.

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Feature Vector Extraction Method for Transient Sonar Signals Using PR-QMF Wavelet Transform (PR-QMF Wavelet Transform을 이용한 천이 수중 신호의 특징벡타 추출 기법)

  • Jung, Yong-Min;Choi, Jong-Ho;Cho, Yong-Soo;Oh, Won-Tcheon
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.1
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    • pp.87-92
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    • 1996
  • Transient signals in underwater show several characterisrics, that is, short duration, strong nonstationarity, various types of transient sources, which make it difficult to analyze and classify transient signals. In this paper, the feature vector extraction method for transient SOMAR signals is discussed by applying digital signal processing methods to the analysis of transient signals. A feature vector extraction methods using wavelet transform, which enable us to obtain better recognition rate than automatic classification using the classical method, are proposed. It is confirmed by simulation that the proposed method using wavelet transform performs better than the classical method even with smaller number of feature vectors. Especially, the feature vector extraction method using PR-QMF wavelet transform with the Daubechies coefficients is shown to perform well in noisy environment with easy implementation.

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An Object Tracking Method using Stereo Images (스테레오 영상을 이용한 물체 추적 방법)

  • Lee, Hak-Chan;Park, Chang-Han;Namkung, Yun;Namkyung, Jae-Chan
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.5
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    • pp.522-534
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    • 2002
  • In this paper, we propose a new object tracking system using stereo images to improve the performance of the automatic object tracking system. The existing object tracking system has optimum characteristics, but it requires a lot of computation. In the case of the image with a single eye, the system is difficult to estimate and track for the various transformation of the object. Because the stereo image by both eyes is difficult to estimate the translation and the rotation, this paper deals with the tracking method, which has the ability to track the image for translation for real time, with block matching algorithm in order to decrease the calculation. The experimental results demonstrate the usefulness of proposed system with the recognition rate of 88% in the rotation, 89% in the translation, 88% in various image, and with the mean rate of 88.3%.

Automatic Response and Conceptual Browsing of Internet FAQs Using Self-Organizing Maps (자기구성 지도를 이용한 인터넷 FAQ의 자동응답 및 개념적 브라우징)

  • Ahn, Joon-Hyun;Ryu, Jung-Won;Cho, Sung-Bae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.5
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    • pp.432-441
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    • 2002
  • Though many services offer useful information on internet, computer users are not so familiar with such services that they need an assistant system to use the services easily In the case of web sites, for example, the operators answer the users e-mail questions, but the increasing number of users makes it hard to answer the questions efficiently. In this paper, we propose an assistant system which responds to the users questions automatically and helps them browse the Hanmail Net FAQ (Frequently Asked Question) conceptually. This system uses two-level self-organizing map (SOM): the keyword clustering SOM and document classification SOM. The keyword clustering SOM reduces a variable length question to a normalized vector and the document classification SOM classifies the question into an answer class. Experiments on the 2,206 e-mail question data collected for a month from the Hanmail net show that this system is able to find the correct answers with the recognition rate of 95% and also the browsing based on the map is conceptual and efficient.

A Parallel Processing System for Visual Media Applications (시각매체를 위한 병렬처리 시스템)

  • Lee, Hyung;Pakr, Jong-Won
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.1A
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    • pp.80-88
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    • 2002
  • Visual media(image, graphic, and video) processing poses challenge from several perpectives, specifically from the point of view of real-time implementation and scalability. There have been several approaches to obtain speedups to meet the computing demands in multimedia processing ranging from media processors to special purpose implementations. A variety of parallel processing strategies are adopted in these implementations in order to achieve the required speedups. We have investigated a parallel processing system for improving the processing speed o f visual media related applications. The parallel processing system we proposed is similar to a pipelined memory stystem(MAMS). The multi-access memory system is made up of m memory modules and a memory controller to perform parallel memory access with a variety of combinations of 1${\times}$pq, pq${\times}$1, and p${\times}$q subarray, which improves both cost and complexity of control. Facial recognition, Phong shading, and automatic segmentation of moving object in image sequences are some that have been applied to the parallel processing system and resulted in faithful processing speed. This paper describes the parallel processing systems for the speedup and its utilization to three time-consuming applications.

The Cucumber Cognizance for Back Propagation of Nerual Network (신경회로망의 오류역전파 알고리즘을 이용한 오이 인식)

  • Min, Byeong-Ro;Lee, Dae-Weon
    • Journal of Bio-Environment Control
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    • v.20 no.4
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    • pp.277-282
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    • 2011
  • We carried out shape recognition. We found out cucumber's feature shape by means of neural network and back propagation algorithm. We developed an algorithm which finds object position and shape in real image and we gained following conclusion as a result. It was processed for feature shape extraction of cucumber to detect automatic. The output pattern rates of the miss-detected objects was 0.1~4.2% in the output pattern which was recognized as cucumber. We were gained output pattern according to image resolution $445{\times}363$, $501{\times}391$, $450{\times}271$, $297{\times}421$. It was appeared that no change was detected. When learning pattern was increased to 25, miss-detection ratio was 16.02%, and when learning pattern had 2 pattern, it didn't detect 8 cucumber in 40 images.

The Performance Improvement of Backpropagation Algorithm using the Gain Variable of Activation Function (활성화 함수의 이득 가변화를 이용한 역전파 알고리즘의 성능개선)

  • Chung, Sung-Boo;Lee, Hyun-Kwan;Eom, Ki-Hwan
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.38 no.6
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    • pp.26-37
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    • 2001
  • In order to improve the several problems of the general backpropagation, we propose a method using a fuzzy logic system for automatic tuning of the activation function gain in the backpropagation. First, we researched that the changing of the gain of sigmoid function is equivalent to changing the learning rate, the weights, and the biases. The inputs of the fuzzy logic system were the sensitivity of error respect to the last layer and the mean sensitivity of error respect to the hidden layer, and the output was the gain of the sigmoid function. In order to verify the effectiveness of the proposed method, we performed simulations on the parity problem, function approximation, and pattern recognition. The results show that the proposed method has considerably improved the performance compared to the general backpropagation.

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Development of Automatic Inspection System for ALC Block Using Distortion Correction Technique (왜곡 보정 기법을 이용한 ALC 블럭의 자동 검사 시스템 개발)

  • Han, Kwang-Hee;Huh, Kyung-Moo
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.47 no.1
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    • pp.1-6
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    • 2010
  • The lens distortion in the machine vision system is inevitable phenomenon. Distortion is getting worse, due to the selection of lens in the trend of reducing prices and size of the system. In this trend, the distortion correction becomes more important. But, the traditional correction methods has problems, such as complexity and requiring more operations. Effective distorted digital image correction is the precondition of target detection and recognition based on vision inspection. To overcome the disadvantage of traditional distortion correction algorithms, such as complex modeling, massive computation and marginal information loss, an image distortion correction algorithm based on photogrammetry method is proposed in this paper. In our method, we use the lattice image as the measurement target. Through the experimental results, we could find that we can reduce the processing time by 4ms. And also the inspection failure rate of our method was reduced by 2.3% than human-eyes inspection method.

Pronunciation Variation Patterns of Loanwords Produced by Korean and Grapheme-to-Phoneme Conversion Using Syllable-based Segmentation and Phonological Knowledge (한국인 화자의 외래어 발음 변이 양상과 음절 기반 외래어 자소-음소 변환)

  • Ryu, Hyuksu;Na, Minsu;Chung, Minhwa
    • Phonetics and Speech Sciences
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    • v.7 no.3
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    • pp.139-149
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    • 2015
  • This paper aims to analyze pronunciation variations of loanwords produced by Korean and improve the performance of pronunciation modeling of loanwords in Korean by using syllable-based segmentation and phonological knowledge. The loanword text corpus used for our experiment consists of 14.5k words extracted from the frequently used words in set-top box, music, and point-of-interest (POI) domains. At first, pronunciations of loanwords in Korean are obtained by manual transcriptions, which are used as target pronunciations. The target pronunciations are compared with the standard pronunciation using confusion matrices for analysis of pronunciation variation patterns of loanwords. Based on the confusion matrices, three salient pronunciation variations of loanwords are identified such as tensification of fricative [s] and derounding of rounded vowel [ɥi] and [$w{\varepsilon}$]. In addition, a syllable-based segmentation method considering phonological knowledge is proposed for loanword pronunciation modeling. Performance of the baseline and the proposed method is measured using phone error rate (PER)/word error rate (WER) and F-score at various context spans. Experimental results show that the proposed method outperforms the baseline. We also observe that performance degrades when training and test sets come from different domains, which implies that loanword pronunciations are influenced by data domains. It is noteworthy that pronunciation modeling for loanwords is enhanced by reflecting phonological knowledge. The loanword pronunciation modeling in Korean proposed in this paper can be used for automatic speech recognition of application interface such as navigation systems and set-top boxes and for computer-assisted pronunciation training for Korean learners of English.

Displacement Measurement of Structure using Multi-View Camera & Photogrammetry (사진측량법과 다시점 카메라를 이용한 구조물의 변위계측)

  • Yeo, Jeong-Hyeon;Yoon, In-Mo;Jeong, Young-Kee
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.1
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    • pp.1141-1144
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    • 2005
  • In this paper, we propose an automatic displacement system for testing stability of structure. Photogrammetry is a method which can measure accurate 3D data from 2D images taken from different locations and which is suitable for analyzing and measuring the displacement of structure. This paper consists of camera calibration, feature extraction using coded target & retro-reflective circle, 3D reconstruction and analyzing accuracy. Multi-view camera which is used for measuring displacement of structure is placed with different location respectively. Camera calibration calculates trifocal tensor from corresponding points in images, from which Euclidean camera is calculated. Especially, in a step of feature extraction, we utilize sub-pixel method and pattern recognition in order to measure the accurate 3D locations. Scale bar is used as reference to measure. the accurate value of world coordinate..

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