• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.783-788
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• 2003

In this paper, we present a new approach to detect and recognize human face in the image from vision camera equipped on the mobile robot platform. Due to the mobility of camera platform, obtained facial image is small and pose-various. For this condition, new algorithm should cope with these constraints and can detect and recognize face in nearly real time. In detection step, ‘coarse to fine’ detection strategy is used. Firstly, region boundary including face is roughly located by dual ellipse templates of facial color and on this region, the locations of three main facial features- two eyes and mouth-are estimated. For this, simplified facial feature maps using characteristic chrominance are made out and candidate pixels are segmented as eye or mouth pixels group. These candidate facial features are verified whether the length and orientation of feature pairs are suitable for face geometry. In recognition step, pseudo-convex hull area of gray face image is defined which area includes feature triangle connecting two eyes and mouth. And random lattice line set are composed and laid on this convex hull area, and then 2D appearance of this area is represented. From these procedures, facial information of detected face is obtained and face DB images are similarly processed for each person class. Based on facial information of these areas, distance measure of match of lattice lines is calculated and face image is recognized using this measure as a classifier. This proposed detection and recognition algorithms overcome the constraints of previous approach [15], make real-time face detection and recognition possible, and guarantee the correct recognition irregardless of some pose variation of face. The usefulness at mobile robot application is demonstrated.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.3 s.309
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• pp.8-15
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• 2006

Obstacle detection is an important task for many mobile robot applications. The methods using stereo vision and optical flow are computationally expensive. Therefore, this paper presents a vision-based obstacle detection method using only two view images. The method uses a single passive camera and odometry, performs in real-time. The proposed method is an obstacle detection method using 3D reconstruction from taro views. Processing begins with feature extraction for each input image using Dr. Lowe's SIFT(Scale Invariant Feature Transform) and establish the correspondence of features across input images. Using extrinsic camera rotation and translation matrix which is provided by odometry, we could calculate the 3D position of these corresponding points by triangulation. The results of triangulation are partial 3D reconstruction for obstacles. The proposed method has been tested successfully on an indoor mobile robot and is able to detect obstacles at 75msec.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.7
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• pp.678-684
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• 2009

Many researches on the GNSS integer ambiguity resolution methods for precise positioning and attitude determination applications have been done. However, by the time invariant property of the integer ambiguity, the reuse of integer ambiguity without performing time consuming integer search procedure is possible. In this paper, a new efficient integer ambiguity propagation method is proposed. The initial integer ambiguity can be determined using the famous LAMBDA method and it is propagated with the propagation method. The proposed method can reconfigure the integer ambiguity using the previous epoch's integer ambiguity and new carrier phase measurements under environmental variations such as geometry changes, signal blockage and reacquisition. Experiments with real measurements show the proposed method can determine an integer ambiguity effectively.

• Journal of KIISE:Information Networking
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• v.28 no.3
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• pp.369-376
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• 2001

The firewall systems can be installed between the intemal network and the extemal network. The firewall systems has the least privilege, so its does not provide transparency to user. This problem of transparency can be solved by using the proxy. In this thesis, I have designed and verified the FTP-PSM(FTP-Proxy Security Mode]) which provides transparency for the firewall systems and has a strong security function. FTP-PSM doesn't finish its work after implementing a command. Instead, its does several security functions such as user authentication, MAC(MandatOlY Access Controll, DAC(Discretionary Access Controll and authentication of user group. Those data must not be lost under any circumstances in order to implement the above security functions. So, the security against such problems as falling into deadlock or unlimited loop during the implementation must be verified. Therefore, FTP-PSM suggested in thesis was verified its security through PHPlace Invariant) based on CPNlCo]oured Petri Net).

• Journal of Korea Multimedia Society
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• v.1 no.2
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• pp.173-182
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• 1998

As a result of remarkable developments in multimedia technology, the image database system that can efficiently retrieve image data becomes a core technology of information-oriented society. In this paper, we proposed the 2-phase Image Retrieval System considering both color and shape information as the method of image features extraction for content-based image data retrieval. At the first level, to get color information, with improving and extending the indexing method using color distribution characteristic suggested by Striker et al., i.e. the indexing method considering local color distribution characteristics, the system roughly classifies images through the improved method. At the second level, the system finally retrieves the most similar image from the image queried by the user using the shape information about the image groups classified at the first level. To extract the shape information, we use the Improved Moment Invariants (IMI) that manipulates only the pixels on the edges of objects in order to overcome two main problems of the existing Moment Invariant methods large amount of processing and rotation sensitiveness which can frequently be seen in the Directive Histogram Intersection technique suggested by Jain et al. Experiments have been conducted on 300 automobile images. And we could obtain the more improved results through the comparative test with other methods.

• Journal of Advanced Navigation Technology
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• v.15 no.1
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• pp.140-146
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• 2011

In this paper, we propose a fast object classification method based on texture and color information for video surveillance. We take the advantage of local patches by extracting SURF and color histogram from images. SURF gives intensity content information and color information strengthens distinctiveness by providing links to patch content. We achieve the advantages of fast computation of SURF as well as color cues of objects. We use Bag of Word models to generate global descriptors of a region of interest (ROI) or an image using the local features, and Na$\ddot{i}$ve Bayes model for classifying the global descriptor. In this paper, we also investigate discriminative descriptor named Scale Invariant Feature Transform (SIFT). Our experiment result for 4 classes of the objects shows 95.75% of classification rate.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.300-311
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• 2014

According to fast change of the environment, the structured study of the ecosystem by analyzing the plant leaves are needed. Expecially, the methodology that searches and classifies the leaves from captured from the smart device have received numerous concerns in the field of computer science and ecology. In this paper, we propose a plant leaf classification technique using shape descriptor by combining Scale Invarinat Feature Transform (SIFT) and Histogram of Oriented Gradient (HOG) from the image segmented from the background via Graphcut algorithm. The shape descriptor is coded in the field of Locality-constrained Linear Coding to optimize the meaningful features from a high degree of freedom. It is connected to Support Vector Machines (SVM) for efficient classification. The experimental results show that our proposed approach is very efficient to classify the leaves which have similar color, and shape.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.7
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• pp.166-175
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• 1989

In this paper, we present a method which is based on the concept of the rotation of subspaces. This method is highly related to the angle (or distance) between subspaces arising in many applications. An effective procedures is first derived for finding the optimal transformation matrix which rotates one subspace into another as closely as possible in the least squares sense , and then this algorithm is applied to the solution to general direction-of-arrival estimation problem of multiple broadband plane waves which may be a mixture of incoherent, partially coherent or coherent. In this typical application, the rotation of signal subspaces (ROSS) algorithm is effectively developed to achieve the high performance in the active systems for the case in which the noise field remains invariant with the measurement of the array spectral density matrix (or data matrix). It is not uncommon to observe this situation in sonar systems. The advantage of this techniques is not to require the preliminary processing and spatial prefiltering which is used in Wang-Kaveh's CSS focusing method. Furthermore, the array's geometry is not restricted. Simulation results are presented to illustrate the high performance achieved with this new approach relative to that obtained with Wang-Kaveh's CSS focusing method for incoherent sources and forward-backward spatial smoothed MUSIC for coherent sources including the signal eigenvector method (SEM).

• The Journal of the Acoustical Society of Korea
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• v.22 no.2
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• pp.104-112
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• 2003

The in-duct acoustical sources of fluid machines are often characterized by the source impedance and strength using the linear time-invariant model. However, negative resistances, which are physically unreasonable, have been found throughout various measurements of the source properties in IC-engines and compressors. In this paper, the effects of the time-varying nature of fluid machines on the source characteristics are studied analytically. For this purpose, the simple fluid machine consisting of a reciprocating piston and an exhaust is considered as representing a typical periodic, time-varying system and the equivalent circuits are analyzed. Simulated measurements using the analytic solutions show that the time-varying nature in the actual sources is one of the main causes of the negative source resistances. It is also found that, for the small magnitude of the time-varying component, the source radiates large acoustic power if the piston operates at twice the natural frequency of the static system. or integral submultiples of that rate.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.34-42
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• 1997

This paper deals with the recognition of closed planar shape using a three dimensional spectral feature vector which is derived from the FFT(Fast Fourier Transform) spectrum of contour sequence and fuzzy ARTMAP neural network classifier. Contour sequences obtained from 2-D planar images represent the Euclidean distance between the centroid and all boundary pixels of the shape, and are related to the overall shape of the images. The Fourier transform of contour sequence and spectrum analyzer are used as a means of feature selection and data reduction. The three dimensional spectral feature vectors are extracted by spectrum analyzer from the FFT spectrum. These spectral feature vectors are invariant to shape translation, rotation and scale transformation. The fuzzy ARTMAP neural network which is combined with two fuzzy ART modules is trained and tested with these feature vectors. The experiments including 4 aircrafts and 4 industrial parts recognition process are presented to illustrate the high performance of this proposed method in the recognition problems of noisy shapes.