• 제목/요약/키워드: feature measurement

검색결과 523건 처리시간 0.032초

레이저 비전을 이용한 3차원 측정 시스템 구현 (Development of a 3-Dimensional Measurement System using Laser Vision)

  • 권효근;천영석;서영수;노영식
    • 전기학회논문지
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    • 제56권5호
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    • pp.973-979
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    • 2007
  • A laser vision system is developed to measure the three-dimensional feature of an object. This system consists of two low cost cameras and a cross laser. One camera and a cross laser are used to measure a plane equation of an object. Using this information, the other camera measures a hole size of an object. The proposed system provides 0.05 mm accuracy measurement systems with relatively low cost.

한대의 카메라에 기반한 직육면체의 부피 계측 방법 (A Single Camera based Method for Cubing Rectangular Parallelepiped Objects)

  • 원종운;정윤수;김우섭;유광훈;이용준;박길흠
    • 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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    • 제8권5호
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    • pp.562-573
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    • 2002
  • 본 논문에서는 소포 및 택배와 같은 패키지(package)의 효과적인 취급(handling)을 위한 직육면체의 부피 계측 방법을 제안한다. 제안된 방법은 한대의 카메라와 직육면체의 특성을 이용하여 실시간으로 부피 계측을 수행한다. 부피 계측을 위한 전처리 과정에서, 제안된 방법은 직육면체의 외곽 선분 정보를 검출하고, 이러한 선분들의 교차점을 3D 물체의 꼭지점으로 추출/인식하여, 물체의 부피를 계산한다. 제안된 방법은 선분 정보를 이용하여 꼭지점을 추출함으로써, 꼭지점을 직접 추출하는 경우에 비하여 카메라의 블러링 효과에 비교적 강인한 특성을 나타내며, 물체의 방향을 고려함으로써 견실한 부피계측 결과를 나타낸다. 실험의 결과를 통하여 제안된 방법이 직육면체 물체의 실시간 부피 계산에 효과적으로 사용될 수 있음이 보여진다.

뉴로-퍼지 신경망 기반 최적의 HRV특징을 이용한 우울증진단 알고리즘 (Neuro-Fuzzy Network-based Depression Diagnosis Algorithm Using Optimal Features of HRV)

  • 장진흥;전설위;임준식
    • 한국콘텐츠학회논문지
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    • 제12권2호
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    • pp.1-9
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    • 2012
  • 본 논문은 가중 퍼지소속함수 기반 신경망 (Neural Network with Weighted Fuzzy Membership functions, NEWFM)과 심박수 변이도(Heart Rate Variability, HRV)를 이용하여 우울증 진단알고리즘을 제안하고 있다. 본 알고리즘에서 사용할 NEWFM의 입력특징을 추출하기 위해서 주파수도메인 특징추출, 시간도메인 특징추출, 웨이블릿변환 특징추출, 포인케어변환 특징추출 방법을 이용하여 22개의 초기 HRV 특징들을 추출하였다. 또한 NEWFM에서 제공하는 비중복면적 분산측정법 (Non-overlap Area Distribution Measurement, NADM)에 의해 입력특징의 중요도를 평가하여 22개의 초기특징으로부터 중요도가 가장 높은 6개 최적입력특징을 선택하였다. 이 6개 특징을 이용하여 우울증을 진단한 결과는 95.8% 의 정확도를 나타내었다.

Hardware Accelerated Design on Bag of Words Classification Algorithm

  • Lee, Chang-yong;Lee, Ji-yong;Lee, Yong-hwan
    • Journal of Platform Technology
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    • 제6권4호
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    • pp.26-33
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    • 2018
  • In this paper, we propose an image retrieval algorithm for real-time processing and design it as hardware. The proposed method is based on the classification of BoWs(Bag of Words) algorithm and proposes an image search algorithm using bit stream. K-fold cross validation is used for the verification of the algorithm. Data is classified into seven classes, each class has seven images and a total of 49 images are tested. The test has two kinds of accuracy measurement and speed measurement. The accuracy of the image classification was 86.2% for the BoWs algorithm and 83.7% the proposed hardware-accelerated software implementation algorithm, and the BoWs algorithm was 2.5% higher. The image retrieval processing speed of BoWs is 7.89s and our algorithm is 1.55s. Our algorithm is 5.09 times faster than BoWs algorithm. The algorithm is largely divided into software and hardware parts. In the software structure, C-language is used. The Scale Invariant Feature Transform algorithm is used to extract feature points that are invariant to size and rotation from the image. Bit streams are generated from the extracted feature point. In the hardware architecture, the proposed image retrieval algorithm is written in Verilog HDL and designed and verified by FPGA and Design Compiler. The generated bit streams are stored, the clustering step is performed, and a searcher image databases or an input image databases are generated and matched. Using the proposed algorithm, we can improve convenience and satisfaction of the user in terms of speed if we search using database matching method which represents each object.

고압전동기 고정자권선의 절연결함에 대한 특징추출기법 (Feature Extraction Technique for Insulation Fault of High Voltage Motor Stator Winding)

  • 박재준;이성룡;문대철
    • 한국전기전자재료학회논문지
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    • 제19권10호
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    • pp.976-983
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    • 2006
  • Multi-resolution Signal Decomposition (MSD) Technique of Wavelet Transform has interesting properties of capturing the embedded horizontal, vertical and diagonal variations within an image in a separable form. This feature was exploited to identify individual partial discharge sources present in multi-source PD pattern, usually encountered during practical PD measurement. Employing the Daubechies wavelet, feature were extracted from the third level decomposed and reconstructed horizontal and vertical component images. These features were found to contain the necessary discriminating information corresponding to the individual PD sources and multi-PD soruces.

Region Division for Large-scale Image Retrieval

  • Rao, Yunbo;Liu, Wei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권10호
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    • pp.5197-5218
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    • 2019
  • Large-scale retrieval algorithm is problem for visual analyses applications, along its research track. In this paper, we propose a high-efficiency region division-based image retrieve approaches, which fuse low-level local color histogram feature and texture feature. A novel image region division is proposed to roughly mimic the location distribution of image color and deal with the color histogram failing to describe spatial information. Furthermore, for optimizing our region division retrieval method, an image descriptor combining local color histogram and Gabor texture features with reduced feature dimensions are developed. Moreover, we propose an extended Canberra distance method for images similarity measure to increase the fault-tolerant ability of the whole large-scale image retrieval. Extensive experimental results on several benchmark image retrieval databases validate the superiority of the proposed approaches over many recently proposed color-histogram-based and texture-feature-based algorithms.

웨이블렛 변환을 이용한 부분 방전 신호 분석 (An Analysis of Partial Discharge signal Using Wavelet Transforms)

  • 박재준;장진강;임윤석;심종탁;김재환
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 1999년도 춘계학술대회 논문집
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    • pp.169-172
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    • 1999
  • Recently, the wavelet transform has been a new and powerful tool for signal processing. It is more suitable specially for the feature extraction and detection of non-stationary signals than traditional methods such as, the Fourier Transform(FT), the Fast Fourier Transform(FFT) and the Least Square Method etc. because of the characteristic of the multi-scale analysis and time-frequency domain localization. The wavelet transform has been developed for the analysis of PD pulse signal to raise in the progress of insulation degradation. In this paper, the wavelet transform was applied to one foundational method for feature extraction. For the obtain experimental data, a computer-aided partial discharge measurement system with a single acoustic sensor was used. If we are applying to the neural network method the accumulated data through the extracted feature, it is expected that we can detect the PD pulse signal in the insulation materials on the on-line.

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Use of Crown Feature Analysis to Separate the Two Pine Species in QuickBird Imagery

  • Kim, Cheon
    • 대한원격탐사학회지
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    • 제24권3호
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    • pp.267-272
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    • 2008
  • Tree species-specific estimates with spacebome high-resolution imagery improve estimation of forest biomass which is needed to predict the long term planning for the sustainable forest management(SFM). This paper is a contribution to develop crown distinguishing coniferous species, Pinus densiflora and Pinus koraiensis, from QuickBird imagery. The proposed feature analysis derived from shape parameters and first and second-order statistical texture features of the same test area were compared for the two species separation and delineation. As expected, initial studies have shown that both formfactor and compactness shape parameters provided the successful differentiating method between the pine species within the compartment for single crown identification from spaceborne high resolution imagery. Another result revealed that the selected texture parameters - the mean, variance, angular second moment(ASM) - in the infrared band image could produce good subset combination of texture features for representing detailed tree crown outline.

Visual Feature Extraction Technique for Content-Based Image Retrieval

  • Park, Won-Bae;Song, Young-Jun;Kwon, Heak-Bong;Ahn, Jae-Hyeong
    • 한국멀티미디어학회논문지
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    • 제7권12호
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    • pp.1671-1679
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    • 2004
  • This study has proposed visual-feature extraction methods for each band in wavelet domain with both spatial frequency features and multi resolution features. In addition, it has brought forward similarity measurement method using fuzzy theory and new color feature expression method taking advantage of the frequency of the same color after color quantization for reducing quantization error, a disadvantage of the existing color histogram intersection method. Experiments are performed on a database containing 1,000 color images. The proposed method gives better performance than the conventional method in both objective and subjective performance evaluation.

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표적의 형상정보를 활용한 다중표적 추적 기법 (Multiple Target Tracking using Target Feature Information)

  • 김수진;정영헌;강재웅;윤주홍
    • 한국멀티미디어학회논문지
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    • 제19권5호
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    • pp.890-900
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    • 2016
  • This paper presents a multiple target tracking system using target feature information. In the proposed system, the state of target is defined as its kinematic as well as feature : the kinematic includes a location and a velocity; the feature contains the image correlation between a prior target and a current measurement. The feature information is used for generating the validation matrix and association probability of joint probabilistic data association (JPDA) algorithm. Through the Kalman filter, the target kinematic is updated. Then the tracking information is cycled by the track management algorithm. The system has been evaluated using the images obtained from Electro-Optics/ InfraRed (EO/IR) sensor. It is verified that the proposed system can reduce the complexity burden of JPDA process and can enhance the track maintenance rate.