• Title/Summary/Keyword: preprocessing technique

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Study on non-destructive sorting technique for lettuce(Lactuca sativa L) seed using fourier transform near-Infrared spectrometer (FT-NIR을 이용한 상추(Lactuca sativa L) 종자의 비파괴 선별 기술에 관한 연구)

  • Ahn, Chi-Kook;Cho, Byoung-Kwan;Kang, Jum-Soon;Lee, Kang-Jin
    • Korean Journal of Agricultural Science
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    • v.39 no.1
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    • pp.111-116
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    • 2012
  • Nondestructive evaluation of seed viability is one of the highly demanding technologies for seed production industry. Conventional seed sorting technologies, such as tetrazolium and standard germination test are destructive, time consuming, and labor intensive methods. Near infrared spectroscopy technique has shown good potential for nondestructive quality measurements for food and agricultural products. In this study, FT-NIR spectroscopy was used to classify normal and artificially aged lettuce seeds. The spectra with the range of 1100~2500 nm were scanned for lettuce seeds and analyzed using the principal component analysis(PCA) method. To classify viable seeds from nonviable seeds, a calibration modeling set was developed with a partial least square(PLS) method. The calibration model developed from PLS resulted in 98% classification accuracy with the Savitzky-Golay $1^{st}$ derivative preprocessing method. The prediction accuracy for the test data set was 93% with the MSC(Multiplicative Scatter Correction) preprocessing method. The results show that FT-NIR has good potential for discriminating non-viable lettuce seeds from viable ones.

A Preprocessing Technique of Gray Scale Image for Efficient Entropy Coding (효율적인 엔트로피부호화를 위한 명암도 등급 이미지의 전처리 기법)

  • Kim, Sun-Ja;Han, Deuk-Su;Park, Jung-Man;You, Kang-Soo;Lee, Jong-Ha;Kwak, Hoon-Sung
    • Annual Conference of KIPS
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    • 2005.05a
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    • pp.805-808
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    • 2005
  • 엔트로피부호화(entropy coding)는 텍스트와 같은 일반적인 데이터들을 효율적으로 압축하는 반면에, 이미지 데이터들에 대해서는 그 성능이 다소 저하된다. 본 논문에서는 이러한 단점을 개선시키기 위한 효율적인 전처리기법(preprocessing technique)을 소개한다. 제안한 전처리기법은 입력된 명암도 등급 이미지를 무손실 압축하기 이전에, 이미지 내에서 인접한 명암도 값들의 발생빈도(occurrence frequency)를 조사한다. 다음으로 각 픽셀 쌍들의 명암도 값들을 발생빈도에 기반한 순서화된 값(ordered number)들로 대체시킨 후, 최종적으로 엔트로피부호화에 의한 압축을 수행한다. 이와 같은 단계들을 거치면서 이미지 데이터의 통계적인 특성(statistical feature)이 보다 강화되기 때문에, 엔트로피부호화에서의 무손실 압축 성능을 효율적으로 개선시킬 수 있다. 실험을 통하여 256 명암도 등급 이미지들을 산술부호화와 허프만부호화를 사용하여 압축한 결과, 제안한 전처리기법이 압축 후 비트율(bit rate)을 최대 37.49%까지 감소시켰음을 확인하였다.

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An Efficient Preprocessing Technique for Improving the Performance of the Crease Detection (지문 영상의 주름선 검출을 위한 효율적인 전처리 기법)

  • Park, Sung-Wook;Park, Jong-Wook
    • Journal of Korea Society of Industrial Information Systems
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    • v.14 no.4
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    • pp.57-64
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    • 2009
  • In this paper, We propose an highly efficient preprocessing technique for improving the performance of the crease extraction method, which can improve the accuracy of feature extraction within the fingerprint image. The proposed method applies the 1-dimensional directional slit for each pixel in fingerprint image. Once the direction of every pixel in crease candidate area is estimated, it is decomposed into different images depending on their direction. From the directional images, the crease clusters are estimated by utilizing the property of crease area. The proposed method finally extracts the crease from the crease clusters estimated from directional images.

Development of Prediction Model for Moisture and Protein Content of Single Kernel Rice using Spectroscopy (분광분석법을 이용한 단립 쌀의 함수율 및 단백질 함량 예측모델 개발)

  • 김재민;최창현;민봉기;김종훈
    • Journal of Biosystems Engineering
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    • v.23 no.1
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    • pp.49-56
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    • 1998
  • The objectives of this study were to develop models to predict the contents of moisture and protein of single kernel of brown rice based on visible/NIR (near-infrared) spectroscopic technique. The reflectance spectra of rice were obtained in the range of the wavelength 400 to 2,500 nm with 2 nm intervals. Multiple linear regression(MLR) and partial least squares (PLS) were used to develop the models. The MLR model using the first derivative spectra(10 nm of gap) with Standard Normal Variate and Detrending (SNV and Drt.) preprocessing showed the best results to predict moisture content of the sin린e kernel brown rice. To predict the protein content of a single kernel of brown ricer the PLS model used the raw spectra with multiplicative scatter correction(MSC) preprocessing over the wavelength of 1,100~1,500 nm.

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A Fuzzy Time-Series Prediction with Preprocessing (전처리과정을 갖는 시계열데이터의 퍼지예측)

  • Yoon, Sang-Hun;Lee, Chul-Hee
    • Proceedings of the KIEE Conference
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    • 2000.11d
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    • pp.666-668
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    • 2000
  • In this paper, a fuzzy prediction method is proposed for time series data having uncertainty and non-stationary characteristics. Conventional methods, which use past data directly in prediction procedure, cannot properly handle non-stationary data whose long-term mean is floating. To cope with this problem, a data preprocessing technique utilizing the differences of original time series data is suggested. The difference sets are established from data. And the optimal difference set is selected for input of fuzzy predictor. The proposed method based the Takigi-Sugeno-Kang(TSK or TS) fuzzy rule. Computer simulations show improved results for various time series.

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Adjusted Direct Orthogonal Signal Correction For High-Dimensional Spectral Data (고차원 스펙트라 데이터 분석을 위한 Adjusted Direct Orthogonal Signal Correction 기법)

  • Kim, Sin-Young;Kim, Seoung-Bum
    • Journal of Korean Institute of Industrial Engineers
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    • v.37 no.4
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    • pp.400-407
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    • 2011
  • Modeling and analysis of high-dimensional spectral data provide an opportunity to uncover inherent patterns in various information-rich data. Orthogonal signal correction (OSC) a preprocessing technique has been widely used to remove unwanted variations of spectral data that do not contribute to prediction or classification. In the present study we propose a novel OSC algorithm called adjusted direct OSC to improve visualization and the ability of classification. Experimental results with real mass spectral data from condom lubricants demonstrate the effectiveness of the proposed approach.

Regularized Channel Inversion for Multiple-Antenna Users in Multiuser MIMO Downlink (다중 안테나 다중 사용자 하향 링크 환경에서 Regularized Channel Inversion 기법)

  • Lee, Heun-Chul;Lee, Kwang-Won;Lee, In-Kyu
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.3A
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    • pp.260-268
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    • 2010
  • Channel inversion is one of the simplest techniques for multiuser downlink systems with single-antenna users. In this paper, we extend the regularized channel inversion technique developed for the single-antenna user case to multiuser multiple-input multiple-output (MIMO) channels with multiple-antenna users. We first employ the multiuser preprocessing to project the multiuser signals near the null space of the unintended users based on the MMSE criterion, and then the single-user preprocessing is applied to the decomposed MIMO interference channels. In order to reduce the complexity, we focus on non-iterative solutions for the multiuser transmit beamforming and use a linear receiver based on an MMSE criterion. Simulation results show that the proposed scheme outperforms existing joint iterative algorithms in most multiuser configurations.

The research of preprocessing technique of Data Compaction customized to network packet data (네트워크 패킷 데이터 마이닝을 위한 데이터 압축 전처리 기법에 관한 연구)

  • Na, Sang-Hyuck;Lee, Won-Suk
    • 한국IT서비스학회:학술대회논문집
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    • 2009.05a
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    • pp.341-344
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    • 2009
  • 네트워크(Network) 라우터(Router)와 스위치(Switch) 장치에서 수많은 패킷(Packet)이 통과된다. 네트워크에 연결된 컴퓨터가 20대일 경우에 일일 평균 패킷 전송양은 약 400GB 정도에 이른다. 이러한 패킷 데이터를 분석하기 위해서는 수집된 데이터를 디스크 장치에 저장할 수 있는 대규모의 저장공간과 주기적인 백업이 필요하다. 수집된 데이터 원형에는 사용자가 원하는 정보뿐만 아니라 불필요한 정보가 산재해있다. 따라서 수집된 데이터를 원형 그대로 저장하는 것이 아니라 원하는 정보(Information)와 지식(Knowledge)이 유지되고 쉽게 식별될 수 있도록 데이터를 가공해서 요약된 정보를 유지하는 것이 효과적이다. 전 세계적으로 네트워크를 통과하는 패킷 데이터의 양이 헤아릴 수 없을 만큼 증가하고, 인터넷 보급률이 증가함에 따라서 인터넷 사용자 및 소비자의 정보 분석의 필요성이 부각되고 있다. 본 논문에서는 네트워크에서 수집된 패킷 데이터에 적합한 데이터 전처리 기법(preprocessing)을 제안한다.

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A Study of the Use of step by preprocessing and Graph Cut for the exact depth map (깊이맵 향상을 위한 전처리 과정과 그래프 컷에 관한 연구)

  • Kim, Young-Seop;Song, Eung-Yeol
    • Journal of the Semiconductor & Display Technology
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    • v.10 no.3
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    • pp.99-103
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    • 2011
  • The stereoscopic vision system is the algorithm to obtain the depth of target object of stereo vision image. This paper presents an efficient disparity matching method using blue edge filter and graph cut algorithm. We do recommend the use of the simple sobel edge operator. The application of B band sobel edge operator over image demonstrates result with somewhat noisy (distinct border). The basic technique is to construct a specialized graph for the energy function to be minimized such that the minimum cut on the graph also minimizes the energy (either globally or locally). This method has the advantage of saving a lot of data. We propose a preprocessing effective stereo matching method based on sobel algorithm which uses blue edge information and the graph cut, we could obtain effective depth map.

Estimating Directly Damage on External Surface of Container from Parameters of Capsize-Gaussian-Function

  • Son TRAN Ngoc Hoang;KIM Hwan-Seong
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2005.10a
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    • pp.297-302
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    • 2005
  • In this paper, an estimating damage on external surface of container using Capsize-Gaussian-Function (be called CGF) is presented. The estimation of the damage size can be get directly from two parameters of CGF, these are the depth and the flexure, also the direction of damage. The performance of the present method has been illustrated using an image of damage container, which had been taken from Hanjin Busan Port, after using image processing techniques to do preprocessing of the image, especially, the main used technique is Canny edge detecting that is widely used in computer vision to locate sharp intensity and to find object boundaries in the image, then correlation between the edge image from the preprocessing step and the CGF with three parameters (direction, depth, flexure), as a result, we get an image that perform damage information, and these parameters is an estimator directly to the damage.

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