• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.54-61
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• 2008

This paper proposes a new algorithm for detecting and recognizing overlapped objects among a stack of arbitrarily located objects using a signature representation scheme. The proposed algorithm consists of two processes of detecting overlap of objects and of determining the boundary between overlapping objects. To determine overlap of objects, in the first step, the edge image of object region is extracted and those areas in the object region are considered as the object areas if an area is surrounded by a closed edge. For each object, its signature image is constructed by measuring the distances of those edge points from the center of the object, along the angle axis, which are located at every angle with reference to the center of the object. When an object is not overlapped, its features which consist of the positions and angles of outstanding points in the signature are searched in the database to find its corresponding model. When an object is overlapped, its features are partially matched with those object models among which the best matching model is selected as the corresponding model. The boundary among the overlapping objects is determined by projecting the signature to the original image. The performance of the proposed algorithm has been tested with the task of picking the top or non-overlapped object from a stack of arbitrarily located objects. In the experiment, a recognition rate of 98% has been achieved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11B
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• pp.1320-1327
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• 2009

In stereoscopy using stereo camera system, the representative factors inducing stereoscopic depth distortions have been reported such as the inter camera distance, the convergence angle and the depth resolution. The image distance is just known to us as a factor related in optical system. In a point of view of depth distortion, it will be a factor inducing a stereoscopic depth distortion. In this paper, we focused on the proof of our opinion that the image distance is one of the weighted factors inducing depth distortion under orthostereoscopic condition.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.709-712
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• 2009

대부분의 고속도로 안개경고시스템은 시정측정을 위해 고가의 광학센서를 사용하고 있으나 운전자의 시정감각과 유사하면서도 비교적 저가인 CCTV를 이용한 시정측정에 관한 연구가 활발히 이루어지고 있다. 그러나 대부분의 CCTV를 이용한 시정측정 방법은 ROI를 기반으로 하고 있어 설치가 까다롭고 기존 CCTV를 활용하기 어렵다는 문제점을 가지고 있다. 본 논문에서는 고속도로상의 안개경고는 약 1~2Km이내의 시정일 때 발생되며, 눈으로 물체를 식별할 수 있는 최대거리가 시정이라는 기초적인 개념에 근거하여 고속도로 안개경고시스템에 사용될 수 있는 Non-ROI 기반의 실시간 CCTV 시정측정 방법을 제안한다. 이를 위해 본 논문에서는 고속도로상에 주행중인 차량의 실시간 이동영역과 가시선을 검출하고 카메라와 도로간의 상관관계를 나타내는 도로모델을 이용하여 시정측정을 수행하는 방법을 제시한다. 제안된 방법은 1~2Km 이내의 시정측정을 위한 방법으로 ROI가 필요없고 직관적이고 현실적인 주야간 시정측정이 가능하며 기존의 고속도로 CCTV에 바로 적용할 수 있다는 장점이 있다.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1263-1264
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• 2006

자기누설탐상법은 비파괴검사 방법의 하나로 대상물체를 외부에서 착자시켜 결함이 발생할 경우에 결함부위에서 자기누설이 발생하도록 하여, 누설된 자기장을 측정하여 결함의 유무와 크기 등을 판정하는 시스템이다. 본 논문에서는 MFL 방식의 범용 NDT 검사기의 개발을 위해 영구자석을 이용하여 소형 비파괴 검사기를 설계하고, 3차원 유한요소법을 이용하여 해석하고 실제 데이터를 측정하여 그 결과를 비교 분석하였다.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.18-24
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• 2004

SPECT technology is used for the reconstructed image in the field of industry noncontact measurement system. One of the distortion problems in reconstructed image quality is a collimator characterictic. The image distortion is caused by a geometrical structure of the collimator. This paper indicated a correction method to remove the image distortion by the structure of the collimator, and compared with the existing correction method. The correction. method removed the image distortion to use deconvolution of projection data with the shift-variant blurring function in the frequency domain. In this pater, I simulated with the collimator angle and distance between the detector and the center of object. and verified with expeimental data. The validity and limitation of correction method is studied for actual industrial applications.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.269-276
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• 2010

In this paper, we present the detection method of moving objects based on two background models. These background models support to understand multi layered environment belonged in images taken by shaking camera and each model is MBM(Multiple Background Model) and TMBM (Temporal Median Background Model). Because two background models are Pixel-based model, it must have noise by camera movement. Therefore correlation coefficient calculates the similarity between consecutive images and measures camera motion vector which indicates camera movement. For the calculation of correlation coefficient, we choose the selected region and searching area in the current and previous image respectively then we have a displacement vector by the correlation process. Every selected region must have its own displacement vector therefore the global maximum of a histogram of displacement vectors is the camera motion vector between consecutive images. The MBM classifies the intensity distribution of each pixel continuously related by camera motion vector to the multi clusters. However, MBM has weak sensitivity for temporal intensity variation thus we use TMBM to support the weakness of system. In the video-based experiment, we verify the presented algorithm needs around 49(ms) to generate two background models and detect moving objects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1135-1141
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• 2004

In this study, this system makes use of the analog infrared rays sensor and converts the feature of fish outline when sensor is operating with CPU(80C196KC). Then, after signal processing, this feature is classified a special feature and a outline of fish by using the neural network, one of the artificial intelligence scheme. This neural network classifies fish pattern of very simple and short calculation. This has linear activation function and the error back propagation is used as a teaming algorithm. And the neural network is learned in off-line process. Because an adaptation period of neural network is too long when random initial weights are used, off-line teaming is induced to decrease the progress time.

• Convergence Security Journal
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• v.8 no.4
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• pp.161-166
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• 2008

This paper proposes a new approach to align 3D data sets by using curvatures of feature surface. We use the Gaussian curvatures and the covariance matrix which imply the physical characteristics of the model to achieve registration of unaligned 3D data sets. First, the physical characteristics of local area are obtained by the Gaussian curvature. And the camera position of 3D range finder system is calculated from by using the projection matrix between 3D data set and 2D image. Then, the physical characteristics of whole area are obtained by the covariance matrix of the model. The corresponding points can be found in the overlapping region with the cross-projection method and it concentrates by removed points of self-occlusion. By the repeatedly the process discussed above, we finally find corrected points of overlapping region and get the optimized registration result.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.69-74
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• 2009

Abandoned objects should be treated as possibly dangerous things for public areas until they turn out to be safe because explosive material or chemical substance is intentionally contained in them for public terrors. For large public areas such as airports or train stations, there are limits in man-power for security staffs to check all the monitors for covering the entire area under surveillance. This is the basic motivation of developing the automatic detection system for dangerous abandoned objects based on vision technology. In this research, well-known DBE is applied to stably extract background images and the HOG algorithm is adapted to discriminate between human and stuff for object classification. To show the effectiveness of the proposed system, experiments are carried out in detecting intrusion for a forbidden area and alarming for abandoned objects in a room under surveillance.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.215.2-215.2
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• 2012

우주물체 전자광학 감시체계(OWL: Optical Wide-field Patrol)는 전세계에 5개의 50cm급 자동 망원경과 1개의 2m급 망원경을 설치하여 인공위성의 궤도 정보를 얻는 시스템이다. 이 시스템을 운영하게 될 소프트웨어는 크게 두 부분으로 나누어지는데, 해외 원격지에 설치되는 관측소의 50cm급 망원경의 마운트와 검출기, 돔, 기상 측기, 전원 제어 장치를 통합하여 무인으로 관측을 수행하고 그 결과를 본부에 보고하며, 각 시스템을 안전하게 보호하는 기능을 갖는 SOS(Site Operating System)와, 스케줄러에 의하여 각 관측소에 필요한 관측 일정을 작성하여 전달하고 관측소의 운영 현황을 모니터링 하는 NOS(Network Operating System)로 구성된다. OWL OS를 위하여, 시스템을 전반적으로 운영하는 운영 시나리오를 설계하였으며, 이 시나리오에는 기상조건 악화와 장비 오류 등의 경우에 시스템을 보호하고 상황을 즉시 보고하는 비상사태 대처 방안을 포함하였다. 이러한 운영의 모든 단계에서 주기적 또는 필요시 로그 기록이 남도록 하였으며, 이 로그 기록을 바탕으로 사용자가 원할 때에 본부에서 운영상황을 요약하여 보여주는 각종 통계 자료를 작성하여 확인할 수 있도록 하였다.