• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권11호
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• pp.5299-5320
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• 2019

Interest in self-driving vehicle research has been rapidly increasing, and related research has been continuously conducted. In such a fast-paced self-driving vehicle research area, the development of advanced technology for better convenience safety, and efficiency in road and transportation systems is expected. Here, we investigate research in self-driving vehicles and analyze the main technologies of driverless car software, including: technical aspects of autonomous vehicles, traffic infrastructure and its communications, research techniques with vision recognition, deep leaning algorithms, localization methods, existing problems, and future development directions. First, we introduce intelligent self-driving car and road infrastructure algorithms such as machine learning, image processing methods, and localizations. Second, we examine the intelligent technologies used in self-driving car projects, autonomous vehicles equipped with multiple sensors, and interactions with transport infrastructure. Finally, we highlight the future direction and challenges of self-driving vehicle transportation systems.

• 한국정보통신학회논문지
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• 제17권6호
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• pp.1281-1285
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• 2013

본 논문에서는 충수 영역을 추출하는 방법을 제안한다. 충수 영역을 추출하는 과정은 복부 초음파 영상에서 앤드인 탐색 스트레칭 기법, 블록 이진화, Grassfire, 팽창 연산을 이용하여 복부 근육의 최하단 근막 부분을 추출하여 제거한 후, 퍼지 시그마 이진화 기법을 적용하여 영상의 객체화 및 객체 제거를 통해 충수 영역을 추출한다. 제안된 방법을 복부 초음파 영상에 적용한 결과, 객관적이고 효율적으로 충수 영역이 추출됨을 확인할 수 있었다.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2002년도 하계학술대회 논문집 Vol.3 No.2
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• pp.1097-1102
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• 2002

For detecting of Faulty Insulator, a new Lateral Information Propagation Networks (LIPN) has been proposed. Energized insulator is reduced the rate of insulation extremely, and taken the results dirty and injured. It is necessary to be actions that detect the faulty insulator and exchange the new one. And thus, we have designed the LIPN to be detected that insulators by the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. Information propagates among neighbor nodes laterally and inter-node interpolation is achieved. Through several simulation experiments,real time reconstruction of the nonlinear image information is processed.

• 센서학회지
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• 제27권4호
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• pp.216-220
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• 2018

In this paper, we present visual sensing techniques that can be used to teach a robot using a laser pointer. The light spot of an off-the-shelf laser pointer is detected and its movement is tracked on consecutive images of a camera. The three-dimensional position of the spot is calculated using stereo cameras. The light spot on the image is detected based on its color, brightness, and shape. The detection results in a binary image, and morphological processing steps are performed on the image to refine the detection. The movement of the laser spot is measured using two methods. The first is a simple method of specifying the region of interest (ROI) centered at the current location of the light spot and finding the spot within the ROI on the next image. It is assumed that the movement of the spot is not large on two consecutive images. The second method is using a Kalman filter, which has been widely employed in trajectory estimation problems. In our simulation study of various cases, Kalman filtering shows better results mostly. However, there is a problem of fitting the system model of the filter to the pattern of the spot movement.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2002년도 전력전자학술대회 논문집
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• pp.455-458
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• 2002

A control of the body posture and movement is maintained by the vestibular system, vision, and proprioceptors. Especially, vestibular system has a very important function that controls the eye movement through vestibuloocular reflex and contraction of skeletal muscles through vestibulospinal reflex. However, postural disturbance caused by loss of vestibular function results in nausea, vomiting, vertigo and loss of craving for life. Lose of vestibular function leads to abnormal reflex of eye movements named nystagmus. Analysis of the nystagmus is needed to diagnose the vertigo, which is performed by means of electronystagmography (ENG). The purpose of this study is to develop a computerized system for data processing and an algorithm for the automatic evaluation of the slow component velocity (SCV) of nystagmus Induced by optokinetic(OKN) stimulation system. A new algorithm using recursive least square method (RLSM) to detect SCV of nystagmus is suggested in this paper. This method allows a fast and precise evaluation of the nystagmus, through artifact rejection techniques. The results are depicted in this paper.

• 대한기계학회논문집
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• 제17권12호
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• pp.3115-3123
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• 1993

This paper presents a real-time correction method of the movemont errors of a translatory precision machine axis. This method is a null-balances technique in which two plane mirrors are used to generate an interferometric fringe pattern utilizing the optical principles of TwymanGreen interferometry. One mirror is fixed on a reference frame, while the other is placed on the machine axis being supported by three piezoelectric actuators. From the fringe pattern, one translatory and two rotational error components of the machine axis are simultaneously detected by using CCD camera vision and image processing techniques. These errors are then independently suppressed by activating the peizoelectric actuators by real-time feedback control while the machine axis is moving. Experimental results demonstrate that a machine axis can be controlled with movement errors less than 10 nm in vertical straightness, 0.1 arcsec in pitch, and 0.06 arcsec in roll for 50mm travel by adopting the real-time correction method.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제4권12호
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• pp.571-576
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• 2015

다양한 안개 제거 기술이 개발되어왔으나 이들의 성능을 정량 정성적으로 평가하는 방식에 대한 연구는 다소 부족하다. 본 논문에서는 안개 제거 기술의 성능을 평가하기 위하여 사용할 수 있는 다양한 척도를 살펴본다. 성능 척도의 신뢰도 검증을 위하여, 고화질 칼라 깊이 영상을 이용하여 안개 영상을 합성하고 안개 제거 영상과 원 영상을 비교하는 방식을 택한다. 한편 안개 제거 기술을 화질을 기준으로 평가하는 방식이 아닌, 안개 제거 전 후 영상에 대한 컴퓨터 비전 기법의 성능을 비교하는 방식을 검토한다. 다양한 안개 제거 기술 성능 척도에 대한 비교 분석 및 문제점에 대한 해결 방안을 토의한다.

• JSTS:Journal of Semiconductor Technology and Science
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• 제13권2호
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• pp.157-169
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• 2013

Scale Invariant Feature Transform (SIFT) generates image features widely used to match objects in different images. Previous work on hardware-based SIFT implementation requires excessive internal memory and hardware logic [1]. In this paper, a new hardware organization is proposed to implement SIFT with less memory and hardware cost than the previous work. To this end, a parallel Gaussian filter bank is adopted to eliminate the buffers that store intermediate results because parallel operations allow all intermediate results available at the same time. Furthermore, the processing order is changed from the raster-scan order to the block-by-block order so that the line buffer size storing the source image is also reduced. These techniques trade the reduction of memory size with a slight increase of the execution time and external memory bandwidth. As a result, the memory size is reduced by 94.4%. The proposed hardware for SIFT implementation includes the Descriptor generation block, which is omitted in the previous work [1]. The addition of the hardwired descriptor generation improves the computation speed by about 30 times when compared with the previous work.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권2호
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• pp.118-123
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• 2011

Video based object tracking normally deals with non-stationary image streams that change over time. Robust and real time moving object tracking is considered to be a problematic issue in computer vision. Multiple object tracking has many practical applications in scene analysis for automated surveillance. In this paper, we introduce a specified object tracking based particle filter used in an environment of multiple moving objects. A differential image region based tracking method for the detection of multiple moving objects is used. In order to ensure accurate object detection in an unconstrained environment, a background image update method is used. In addition, there exist problems in tracking a particular object through a video sequence, which cannot rely only on image processing techniques. For this, a probabilistic framework is used. Our proposed particle filter has been proved to be robust in dealing with nonlinear and non-Gaussian problems. The particle filter provides a robust object tracking framework under ambiguity conditions and greatly improves the estimation accuracy for complicated tracking problems.

• 소성∙가공
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• 제31권4호
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• pp.229-239
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• 2022

Convolution Neural Network(CNN) is a class of deep learning algorithms and can be used for image analysis. In particular, it has excellent performance in finding the pattern of images. Therefore, CNN is commonly applied for recognizing, learning and classifying images. In this study, the surface defect classification performance of Al 6061 extruded material using CNN-based algorithms were compared and evaluated. First, the data collection criteria were suggested and a total of 2,024 datasets were prepared. And they were randomly classified into 1,417 learning data and 607 evaluation data. After that, the size and quality of the training data set were improved using data augmentation techniques to increase the performance of deep learning. The CNN-based algorithms used in this study were VGGNet-16, VGGNet-19, ResNet-50 and DenseNet-121. The evaluation of the defect classification performance was made by comparing the accuracy, loss, and learning speed using verification data. The DenseNet-121 algorithm showed better performance than other algorithms with an accuracy of 99.13% and a loss value of 0.037. This was due to the structural characteristics of the DenseNet model, and the information loss was reduced by acquiring information from all previous layers for image identification in this algorithm. Based on the above results, the possibility of machine vision application of CNN-based model for the surface defect classification of Al extruded materials was also discussed.