• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.10
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• pp.1957-1964
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• 1994

In this thesis, a Synthetic Aperture Rarar Processor that is possible real-time handling is implemented using CW(Continuose Wave) laser as a light source, CCD(charge Coupled Device) as a time integrator, and AOD(Acousto-Optic Device) as the space integrator. One of the advantages of the proposed system is that it does not require driving circuits of the light source. To implement the system, the linear frequency modulation(chirp) technique has been used for radar signal. The received data for the unit target was processed using 7.80 board and accompanying electronic circuits. In order to reduce the smear effect of the focused chirp signal which occurs Bragg diffrection angle of the AOD has been utilized to make sharp pulses of the laser source, and the pulse made synchronized with the chirp signal. Experiment and analysis results of the data and images detected from CCD of the proposed SAR system demonstrated that detection effect is degrated as the unit target distance increases, and the resolving power is improved as the bandwidth of the chirp signal increases. Also, as the pulse width of the light source decreases, the smear effect has been reduced. The experimental results assured that the proposed system in this papre can be used as a real time SAR processor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.33-40
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• 2012

This paper proposes a method to implement biological early warning systems(BEWS). This system generates periodically data event using a monitoring daemon and it extracts the feature parameters from this data sets. The feature parameters are derived with 6 variables, x/y coordinates, distance, absolute distance, angle, and fractal dimension. Specially by using the fractal dimension theory, the proposed algorithm define the input features represent the organism characteristics in non-toxic or toxic environment. And to find a moderate algorithm for learning the extracted feature data, the system uses an extended learning algorithm(UChoo) popularly used in machine learning. And this algorithm includes a learning method with the extended data expression to overcome the BEWS environment which the feature sets added periodically by a monitoring daemon. In this algorithm, decision tree classifier define class distribution information using the weight parameter in the extended data expression. Experimental results show that the proposed BEWS is available for environmental toxicity detection.

• Journal of Cadastre & Land InformatiX
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• v.45 no.2
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• pp.117-130
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• 2015

A least squares method for adjusting the horizontal network satisfies the conditions which is minimizing the sum of the squares of errors based on probability theory. This research compared accuracy of 3rd cadastral control points adjusted by traditional and least square method with respect to the result of Network-RTK. Test results showed the least square method more evenly distribute closure error than traditional method. Mean errors of least square and traditional adjusting method are 2.7cm, 2.2cm respectively. In addition, blunder in angle observations can be detected by comparing position errors which calculated by forward and backward initial coordinates. However, distance blunder cannot offer specific observation line occurred mistake because distance error propagates several observation lines which have similar directions.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.8
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• pp.26-32
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• 2002

In this paper, we propose a suboptimal receiver combining adaptive array antenna and orthogonal decision-feedback detector in DS/CDMA system. Adaptive way antenna can cancel out undesired signal using beamforming scheme. However, if there are interfering signals from undesired users with the same incident angle as that of a desired user, an adaptive array antenna cannot suppress them. The proposed receiver can cancel out remaining interference from users having nearly the same beam pattern. And we employ Orthogonal Decision-Feedback Detector (ODFD) as Multiuser detection. The ODFD performs as good as the decorrelating decision -feedback detector (DDFD) with much less complexity. Simulation results show that the proposed system provides a significantly enhanced performance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.1-11
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• 2006

In this paper, we propose the novel video retrieval algorithm using non-parametric based motion classification in the shot-based video indexing structure. The proposed system firstly gets the key frame and motion information from each shot segmented by scene change detection method, and then extracts visual features and non-parametric based motion information from them. Finally, we construct real-time retrieval system supporting similarity comparison of these spatio-temporal features. After the normalized motion vector fields is created from MPEG compressed stream, the extraction of non-parametric based motion feature is effectively achieved by discretizing each normalized motion vectors into various angle bins, and considering a mean, a variance, and a direction of these bins. We use the edge-based spatial descriptor to extract the visual feature in key frames. Experimental evidence shows that our algorithm outperforms other video retrieval methods for image indexing and retrieval. To index the feature vectors, we use R*-tree structures.

• Journal of the korean academy of Pediatric Dentistry
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• v.30 no.3
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• pp.510-514
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• 2003

The Axenfeld-Rieger syndrome is a rare autosomal dominant disorder characterized by dental and ocular abnormalities. The essential ocular features include partial or complete bilateral hypoplasia of the iris stroma, abnormalities of the angle structures with congenital iris adhesions, and anterior displacement of Schwalbe's corpuscles. Common oral findings are hypodontia(especially in anterior maxillary segment), microdontia, misshaped teeth, delayed eruption of the teeth. Additionally, other systemic symptoms can be seen and early detection by the pedodontist through dental diagnosis should prevent visual impairment.

• 한국생물공학회:학술대회논문집
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• 2003.04a
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• pp.74-78
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• 2003

Multi-channel images of 11-MUA and 11-MUOH self-assembled monolayers were obtained by using two-dimensional surface plasmon resonance (SPR) absorption. Patterning process was simplified by exploiting direct photo-oxidation of thiol bonding (photolysis) instead of conventional photolithography. Sharper images were resolved by using a white light source in combination with a narrow bandpass filter in the visible region, minimizing the diffraction patterns on the images. The line profile calibration of the image contrast caused by different resonance conditions at each points on the sensor surface (at a fixed incident angle) enables us to discriminate the monolayer thickness in sub-nanometer scale. Furthermore, there is no signal degradation such as photo bleaching or quenching which are common in the detection methods based on the fluorescence.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1546-1551
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• 2004

The laser Doppler technique is well-established as a velocity measurement technique of high precision for flow velocity. Recently, the laser Doppler technique has also been used to measure acceleration of fluid particles. Acceleration is interesting from a fluid mechanics point of view, since the Navier Stokes equations, specifically the left-hand-side, are formulated in terms of fluid acceleration. Further, there are several avenues to estimating the dissipation rate using the acceleration. However such measurements place additional demands on the design of the optical system; in particular fringe non-uniformity must be held below about 0.0001 to avoid systematic errors. Relations expressing fringe divergence as a function of the optical parameters of the system have been given in the literature; however, direct use of these formulae to minimize fringe divergence lead either to very large measurement volumes or to extremely high intersection angles. This dilemma can be resolved by using an off-axis receiving arrangement, in which the measurement volume is truncated by a pinhole in front of the detection plane. In the present study an optical design study is performed for optimizing laser Doppler systems for fluid acceleration measurements. This is followed by laboratory validation using a round free jet and a stagnation flow, two flows in which either fluid acceleration has been previously measured or in which the acceleration is known analytically. A 90 degree off-axis receiving angle is used with a pinhole or a slit.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.1
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• pp.48-55
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• 2012

Pressure vessels in vehicle industries, power plants, and chemical industries are often affected by flaw and defect generated inside the pressure vessels due to production processes or being used. It is very important to detect such internal defects of pressure vessel because they sometimes bring out serious problems. In this paper, an optical defect detection method using digital shearography is used. This method has advantages that the inspection can be performed at a real time measurement and is less sensitive to environmental noise. Shearography is a laser-based technique for full-field, non-contacting measurement of surface deformation (displacement or strain). The ultimate goal of this paper is to detect flaws in pressure vessels and to measure the lengths of the flaws by using unwrapping, phase images which are only obtained by Phase map. Through this method, we could decrease post-processing (next processing). Real length of a pixel can be calculated by comparing minimum and maximum unwrapping images with shearing angle. Through measuring several specimen defects which have different lengths and depths of defect, it can be possible to interpret quantitatively by calculating gray level.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.327-336
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• 2002

Texture analysis is an important technique in many image understanding areas, such as perception of surface, object, shape and depth. But the previous works are intend to the issue of only texture segment, that is not capable of acquiring recognition information. No unsupervised method is basased on the recognition of texture in image. we propose a novel approach for efficient texture image analysis that uses unsupervised learning schemes for the texture recognition. The self-organization neural network for multiple texture image identification is based on block-based clustering and merging. The texture features used are the angle and magnitude in orientation-field that might be different from the sample textures. In order to show the performance of the proposed system, After we have attempted to build a various texture images. The final segmentation is achieved by using efficient edge detection algorithm applying to block-based dilation. The experimental results show that the performance of the system Is very successful.