• 소성∙가공
• /
• 제19권5호
• /
• pp.320-324
• /
• 2010

Multi-Layer Ceramic Circuit(MLCC) in the face of thousands of fine pitch multi hole is processed. However, the fine pitch multi hole has a size of only a few micrometers. Therefore, in order to curtail the measurement time and reduce error, the image processing measurement method is required. So, we proposed an image processing measurement algorithm which is required to accurately measure the fine pitch multi hole. The proposed algorithm gets image of the fine pitch multi hole, extracts object from the image by morphological process, and extracts the parameters of its position and feature by edge detecting process. In addition, we have used the sub-pixel algorithm to improve accuracy. As a result, the proposed algorithm shows 97% test-retest measurement reliability within 2 ${\mu}m$. We found that the algorithm was wellsuited for measuring the fine pitch multi hole.

• 디지털융복합연구
• /
• 제10권11호
• /
• pp.383-387
• /
• 2012

스캔된 인보이스에 특화된 서류 관리 자동화 시스템 구축에있어서 추출된 금전적 데이터의 정확도에대한 엄격한 요구는 인보이스 테이블을 위한 발생적 모델 설계에서 자체 인증 절차를 포함하는 것을 필요로 한다. 가격 = 단가 ${\times}$ 구매수량과 같은 내부적 관계식을 활용한 단순한 인증 절차를 사용하는 것이 전형적 방법론이다. 본 논문에서 는 영상내 테이블 헤더 부분의 탐색과 탐색된 헤더의 컬럼 구분자를 활용하는 개선된 자동 인증 절차를 갖춘 인보이스내 정보 추출 모델을 제안한다.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
• /
• pp.639-644
• /
• 2002

Password typing is the most wifely ued identity verification method in computer security domain. However, due to its simplicity, it is vulnerable to imposter attacks Keystroke dynamics adds a shield to password. Discriminating imposters from owners is a novelty detection problem. Auto-Associative Multilayer Perceptron (AaMLP) has teen proved to be a good novelty detector. However, the wifely used 2-layer AaMLP cannot identify nonlinear boundaries, which can result in serious problems in computer security. In this paper, a nonlinear model, i.e. 4-layer AaMLP, is proposed to serve as the novelty detector, which can remedy the limitations of 2-layer AaMLP.

• 한국산업융합학회 논문집
• /
• 제27권1호
• /
• pp.183-193
• /
• 2024

Recurrent Neural Network technology that learns past patterns and predicts future patterns using technology for recognizing and classifying objects is being applied to various industries, economies, and languages. And research for practical use is making a lot of progress. However, research on the application of Recurrent Neural Networks for evaluating and predicting the safety of mechanical structures is insufficient. Accurate detection of external load applied to the outside is required to evaluate the safety of mechanical structures. Learning of Recurrent Neural Networks for this requires a large amount of load data. This study applied the Gated Recurrent Unit technique to examine the possibility of load learning and investigated the possibility of applying a stacked Auto Encoder as a way to secure load data. In addition, the usefulness of learning mechanical loads was analyzed with the Gated Recurrent Unit technique, and the basic setting of related functions and parameters was proposed to secure accuracy in the recognition and prediction of loads.

• 융합신호처리학회 학술대회논문집
• /
• 한국신호처리시스템학회 2000년도 하계종합학술대회논문집
• /
• pp.269-272
• /
• 2000

It is need to develop and apply a human pulse diagnosis system providing a quantitative and automatic analysis in the the oriental medicine. In order to analyze quantitatively the characteristic of pulsation, each of points had to be recognized accurately notifying the existence and the position of feature point in the wave form. And getting the period of human pulse. Thus, in this paper, it is proposed the preprocessing method of human pulse and the detection method of period by Wavelet Transformation. The human pulse is seprated from each band through Wavelet Transformation and feature points can be recognized through over the fact, and then the parameter of proposed Mac-Jin parameter is measured. Commonly, Human pulse signal has often various noises which are baseline drift, high frequency noise and so on. So it is significant to remove that noises. Thus, in this paper, the one period of human pulse is deciede and the feature points are detected after doing the preprocessing by wavelet transformation. As a result, it could be confirmed that this method is effective as a real program for the auto-diagnosis of human pulse.

• 대한안전경영과학회지
• /
• 제23권3호
• /
• pp.83-88
• /
• 2021

Recently, due to the aging of workers and the weakening of the labor base in the automobile industry, research on quality inspection methods through ICT(Information and Communication Technology) convergence is being actively conducted. A lot of research has already been done on the development of an automated system for quality inspection in the manufacturing process using image processing. However, there is a limit to detecting defects occurring in the automotive sunroof sealer application process, which is the subject of this study, only by image processing using a general camera. To solve this problem, this paper proposes a system construction method that collects image information using a infrared thermal imaging camera for the sunroof sealer application process and detects possible product defects based on the SVM(Support Vector Machine) algorithm. The proposed system construction method was actually tested and applied to auto parts makers equipped with the sunroof sealer application process, and as a result, the superiority, reliability, and field applicability of the proposed method were proven.

• 방송공학회논문지
• /
• 제19권4호
• /
• pp.491-501
• /
• 2014

최근 전 세계적으로 지진, 쓰나미와 같이 막대한 인명과 재산 피해를 야기시키는 자연재난이 증가함에 따라 재난에 효과적으로 대응하기 위한 방송 시스템에 대한 요구가 증가하고 있다. 재난 방송시스템에서는 재난 발생 시 재난정보를 보다 빠르고 효과적으로 전달하기 위하여, 단말을 깨워 재난 방송 채널로 자동 변환 시켜주는 대기모드해제(wake-up) 신호가 사용된다. 본 논문에서는, 재난 방송시스템을 위한 대기모드해제 검출 방법을 제안한다. 재난방송용 대기모드 해제신호는 기존 디지털TV 시스템과의 간섭을 줄이기 위하여 저전력/협대역에서 고려되어야 하며, 좋은 자기 상관 특성을 가져야한다. 우선, 본 논문에서의 자기상관특성이 우수한 단일 m-시퀀스와 상보부호(complementary code)를 이용한 대기모드해제의 적합성을 분석하고, 신호 대 잡음비에 따른 성능을 검증한다. 다음으로 대기모드 해제신호의 검출 성능을 향상시키기 위하여, 의사잡음 계열의 Barker 부호 및 Walsh-Hadamard 부호를 이용한 직접확산 방식의 신호 전송 포맷을 제안한다. 제안된 직접확산방식에 의한 대기모드 해제신호 검출 방법은 확산 이득으로 인하여 단일 m-시퀀스와 Golay 부호(이진 상보부호)를 이용한 방법보다 뛰어난 검출 성능을 나타낸다.

• 한국해양공학회지
• /
• 제21권4호
• /
• pp.55-60
• /
• 2007

In contrast to the method in Part I, which is considered to be the general approach, Part II pursues a closed-form solution. However, this closed-form solution is available only in the 2D situation under the assumption that the moving object is restricted to a 2D space, and also requires the use of only two laser-slit sensors. Since the motion of the container loaded on top of an AGV is restricted to a plane parallel to the ground, it can be considered a 2D motion. As a simple method, but with a high cost, the use of a laser scanner is also discussed. Since the approach in Part I already uses three laser-slit sensors, it is desirable to use the schemes presented in Part II for supplementary purposes.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2000년도 추계학술대회 논문집
• /
• pp.687-690
• /
• 2000

Lately, many studies have been progressed for the protection human's lives and property as holding in check accidents happened by human's carelessness or mistakes. One part of these is the development of an autonomouse vehicle. General control method of vision-based autonomous vehicle system is to determine the navigation direction by analyzing lane images from a camera, and to navigate using proper control algorithm. In this paper, characteristic points are abstracted from lane images using lane recognition algorithm with sobel operator. And then the vehicle is controlled using two proposed auto-steering algorithms. Two steering control algorithms are introduced in this paper. First method is to use the geometric relation of a camera. After transforming from an image coordinate to a vehicle coordinate, a steering angle is calculated using Ackermann angle. Second one is using a neural network algorithm. It doesn't need to use the geometric relation of a camera and is easy to apply a steering algorithm. In addition, It is a nearest algorithm for the driving style of human driver. Proposed controller is a multilayer neural network using Levenberg-Marquardt backpropagation learning algorithm which was estimated much better than other methods, i.e. Conjugate Gradient or Gradient Decent ones.

• 응용통계연구
• /
• 제22권6호
• /
• pp.1191-1201
• /
• 2009

공정관리에서 작은 평균변화를 탐지하기 위하여 누적합 관리도를 사용하는 것이 일반적이다. 자기상관이 존재하는 공정의 경우 시계열 모형에 적합하여 구한 잔차를 관리도에 적용하는 모형기반 관리방법이 활용되고 있다. 그러나 공정에 일정한 크기의 지속적인 수준 변화가 발생하면 잔차에는 동적 평균변화의 패턴이 나타나게 되어 누적합 관리도의 탐지능력은 저하될 수 있다. 본 논문에서는 잔차에 등락을 반복하는 진동(oscillation) 특성의 동적 평균변화가 발생하는 ARMA(1,1) 모형을 대상으로, 그러한 변화를 효율적으로 탐지할 수 있는 새로운 OCUSUM 관리도를 제안하고 모의실험을 통해 최근에 소개된 기존의 CUSUM 관리도와 탐지능력을 비교하였다.