• 제목/요약/키워드: features extraction

검색결과 1,473건 처리시간 0.033초

Clinical and panoramic radiographic features of osteomyelitis of the jaw: A comparison between antiresorptive medication-related and medication-unrelated conditions

  • Shin, Jeong Won;Kim, Jo-Eun;Huh, Kyung-Hoe;Yi, Won-Jin;Heo, Min-Suk;Lee, Sam-Sun;Choi, Soon-Chul
    • Imaging Science in Dentistry
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    • 제49권4호
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    • pp.287-294
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    • 2019
  • Purpose: This study was performed to analyze the clinical and imaging features of contemporary osteomyelitis(OM) and to investigate differences in these features on panoramic radiography according to patients' history of use of medication affecting bone metabolism. Materials and Methods: The records of 364 patients(241 female and 123 male, average age 66.8±14.9 years) with OM were retrospectively reviewed. Panoramic imaging features were analyzed and compared between patients with medication-related OM(m-OM) and those with conventional, medication-unrelated OM(c-OM). Results: The age of onset of OM tended to be high, with the largest number of patients experiencing onset in their 70s. The 2 most frequent presumed causes were antiresorptive medication use (44.2%) and odontogenic origin (34.6%). On panoramic radiographs, a mix of osteolysis and sclerosis was the most common lesion pattern observed (68.6%). Sequestrum, extraction socket, and periosteal new bone formation were found in 143(42.1%), 79 (23.2%), and 24 (7.1%) cases, respectively. The m-OM group exhibited sequestrum and extraction socket more frequently and displayed significantly higher mandibular cortical index values than the c-OM group. Conclusion: We observed some differences in imaging features as shown on panoramic radiography according to the history of antiresorptive medication use. This study may help elucidate the predictive imaging features of medication-related osteonecrosis of the jaw.

An Algorithm for a pose estimation of a robot using Scale-Invariant feature Transform

  • 이재광;허욱열;김학일
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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    • pp.517-519
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    • 2004
  • This paper describes an approach to estimate a robot pose with an image. The algorithm of pose estimation with an image can be broken down into three stages : extracting scale-invariant features, matching these features and calculating affine invariant. In the first step, the robot mounted mono camera captures environment image. Then feature extraction is executed in a captured image. These extracted features are recorded in a database. In the matching stage, a Random Sample Consensus(RANSAC) method is employed to match these features. After matching these features, the robot pose is estimated with positions of features by calculating affine invariant. This algorithm is implemented and demonstrated by Matlab program.

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컴퓨터 시각에 의한 잎담배의 외형 및 색 특징 추출 (Extraction of Geometric and Color Features in the Tobacco-leaf by Computer Vision)

  • 조한근;송현갑
    • Journal of Biosystems Engineering
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    • 제19권4호
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    • pp.380-396
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    • 1994
  • A personal computer based color machine vision system with video camera and fluorescent lighting system was used to generate images of stationary tobacco leaves. Image processing algorithms were developed to extract both the geometric and the color features of tobacco leaves. Geometric features include area, perimeter, centroid, roundness and complex ratio. Color calibration scheme was developed to convert measured pixel values to the standard color unit using both statistics and artificial neural network algorithm. Improved back propagation algorithm showed less sum of square errors than multiple linear regression. Color features provide not only quality evaluation quantities but the accurate color measurement. Those quality features would be useful in grading tobacco automatically. This system would also be useful in measuring visual features of other agricultural products.

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열악한 환경에 강인한 화자인증을 위한 위상 기반 특징 추출 기법 (A Phase-related Feature Extraction Method for Robust Speaker Verification)

  • 권철홍
    • 한국정보통신학회논문지
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    • 제14권3호
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    • pp.613-620
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    • 2010
  • 화자인증 시스템은 훈련 환경과 인식 환경이 다른 경우 인식 성능이 크게 저하된다. 이러한 훈련과 인식 환경의 불일치는 다양한 잡음과 상이한 채널 환경 때문이다. 본 논문은 화자인증 시스템의 강인성 개선을 위하여 음성신호의 위상에 기반한 특정 추출 기법을 제안한다. 이 방법은 음성신호의 위상으로부터 순시 주파수를 계산하여 대역별로 순시 주파수를 모두 모아 구한 히스토그램으로부터 특징 계수를 추출한다. 이 특징 파라미터를 적용한 결과 조 용한 환경뿐만 아니라 잡음환경 그리고 채널 왜곡 환경에서도 화자인증 시스템의 성능이 개선됨을 알 수 있다.

Matrix Factorization을 이용한 음성 특징 파라미터 추출 및 인식 (Feature Parameter Extraction and Speech Recognition Using Matrix Factorization)

  • 이광석;허강인
    • 한국정보통신학회논문지
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    • 제10권7호
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    • pp.1307-1311
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    • 2006
  • 본 연구에서는 행렬 분해 (Matrix Factorization)를 이용하여 음성 스펙트럼의 부분적 특정을 나타낼 수 있는 새로운 음성 파라마터를 제안한다. 제안된 파라미터는 행렬내의 모든 원소가 음수가 아니라는 조건에서 행렬분해 과정을 거치게 되고 고차원의 데이터가 효과적으로 축소되어 나타남을 알 수 있다. 차원 축소된 데이터는 입력 데이터의 부분적인 특성을 표현한다. 음성 특징 추출 과정에서 일반적으로 사용되는 멜 필터뱅크 (Mel-Filter Bank)의 출력 을 Non-Negative 행렬 분해(NMF:Non-Negative Matrix Factorization) 알고리즘의 입 력으로 사용하고, 알고리즘을 통해 차원 축소된 데이터를 음성인식기의 입력으로 사용하여 멜 주파수 캡스트럼 계수 (MFCC: Mel Frequency Cepstral Coefficient)의 인식결과와 비교해 보았다. 인식결과를 통하여 일반적으로 음성인식기의 성능평가를 위해 사용되는 MFCC에 비하여 제안된 특정 파라미터가 인식 성능이 뛰어남을 알 수 있었다.

A SHAPE FEATURE EXTRACTION FOR COMPLEX TOPOGRAPHICAL IMAGES

  • Kwon Yong-Il;Park Ho-Hyun;Lee Seok-Lyong;Chung Chin-Wan
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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    • pp.575-578
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    • 2005
  • Topographical images, in case of aerial or satellite images, are usually similar in colors and textures, and complex in shapes. Thus we have to use shape features of images for efficiently retrieving a query image from topographical image databases. In this paper, we propose a shape feature extraction method which is suitable for topographical images. This method, which improves the existing projection in the Cartesian coordinates, performs the projection operation in the polar coordinates. This method extracts three attributes, namely the number of region pixels, the boundary pixel length of the region from the centroid, the number of alternations between region and background, along each angular direction of the polar coordinates. It extracts the features of complex shape objects which may have holes and disconnected regions. An advantage of our method is that it is invariant to rotation/scale/translation of images. Finally we show the advantages of our method through experiments by comparing it with CSS which is one of the most successful methods in the area of shape feature extraction

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오스테나이트계 스테인리스강 304 용접부의 초음파 형상 인식 평가를 위한 카오스 시뮬레이터의 구축 (Construction fo chaos simulator for ultrasonic pattern recognition evaluation of weld zone in austenitic stainless steel 304)

  • 이원;윤인식;장영권
    • Journal of Welding and Joining
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    • 제16권5호
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    • pp.108-118
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    • 1998
  • This study proposes th analysis and evaluation method of time series ultrasonic signal using the chaos feature extraction for ultrasonic pattern recognition. Features extracted from time series data using the chaos time series signal analyze quantitatively weld defects. For this purpose, analysis objective in this study is fractal dimension and Lyapunov exponent. Trajectory changes in the strange attractor indicated that even same type of defects carried substantial difference in chaosity resulting from distance shifts such as 0.5 and 1.0 skip distance. Such differences in chaosity enables the evaluation of unique features of defects in the weld zone. In quantitative chaos feature extraction, feature values of 4.511 and 0.091 in the case of side hole and 4.539 and 0.115 in the case of vertical hole were proposed on the basis of fractal dimension and Lyapunov exponent. Proposed chaos feature extraction in this study can enhances ultrasonic pattern recognition results from defect signals of weld zone such as side hole and vertical hole.

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6dB Drop법에 의한 용접 결함 초음파 신호의 카오스성 평가 (Chaoticity Evaluation of Ultrasonic Signals in Welding Defects by 6dB Drop Method)

  • 이원;윤인식
    • 대한기계학회논문집A
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    • 제23권7호
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    • pp.1065-1074
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    • 1999
  • This study proposes the analysis and evaluation method of time series ultrasonic signal using the chaotic feature extraction for ultrasonic pattern recognition. Features extracted from time series data using the chaotic time series signal analysis quantitatively welding defects. For this purpose analysis objective in this study is fractal dimension and Lyapunov exponent. Trajectory changes in the strange attractor indicated that even same type of defects carried substantial difference in chaoticity resulting from distance shills such as 0.5 and 1.0 skip distance. Such differences in chaoticity enables the evaluation of unique features of defects in the weld zone. In experiment fractal(correlation) dimension and Lyapunov exponent extracted from 6dB ultrasonic defect signals of weld zone showed chaoticity. In quantitative chaotic feature extraction, feature values(mean values) of 4.2690 and 0.0907 in the case of porosity and 4.2432 and 0.0888 in the case of incomplete penetration were proposed on the basis of fractal dimension and Lyapunov exponent. Proposed chaotic feature extraction in this study enhances ultrasonic pattern recognition results from defect signals of weld zone such as vertical hole.

Proposed Efficient Architectures and Design Choices in SoPC System for Speech Recognition

  • Trang, Hoang;Hoang, Tran Van
    • 전기전자학회논문지
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    • 제17권3호
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    • pp.241-247
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    • 2013
  • This paper presents the design of a System on Programmable Chip (SoPC) based on Field Programmable Gate Array (FPGA) for speech recognition in which Mel-Frequency Cepstral Coefficients (MFCC) for speech feature extraction and Vector Quantization for recognition are used. The implementing process of the speech recognition system undergoes the following steps: feature extraction, training codebook, recognition. In the first step of feature extraction, the input voice data will be transformed into spectral components and extracted to get the main features by using MFCC algorithm. In the recognition step, the obtained spectral features from the first step will be processed and compared with the trained components. The Vector Quantization (VQ) is applied in this step. In our experiment, Altera's DE2 board with Cyclone II FPGA is used to implement the recognition system which can recognize 64 words. The execution speed of the blocks in the speech recognition system is surveyed by calculating the number of clock cycles while executing each block. The recognition accuracies are also measured in different parameters of the system. These results in execution speed and recognition accuracy could help the designer to choose the best configurations in speech recognition on SoPC.

Extended pivot-based approach for bilingual lexicon extraction

  • Seo, Hyeong-Won;Kwon, Hong-Seok;Kim, Jae-Hoon
    • Journal of Advanced Marine Engineering and Technology
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    • 제38권5호
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    • pp.557-565
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    • 2014
  • This paper describes the extended pivot-based approach for bilingual lexicon extraction. The basic features of the approach can be described as follows: First, the approach builds context vectors between a source (or target) language and a pivot language like English, respectively. This is the same as the standard pivot-based approach which is useful for extracting bilingual lexicons between low-resource languages such as Korean-French. Second, unlike the standard pivot-based approach, the approach looks for similar context vectors in a source language. This is helpful to extract translation candidates for polysemous words as well as lets the translations be more confident. Third, the approach extracts translation candidates from target context vectors through the similarity between source and target context vectors. Based on these features, this paper describes the extended pivot-based approach and does various experiments in a language pair, Korean-French (KR-FR). We have observed that the approach is useful for extracting the most proper translation candidate as well as for a low-resource language pair.