• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1555-1562
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• 2017

A loose part monitoring system is used to identify unexpected loose parts in a nuclear reactor vessel or steam generator. It is still necessary for the mass estimation of loose parts, one function of a loose part monitoring system, to develop a new method due to the high estimation error of conventional methods such as Hertz's impact theory and the frequency ratio method. The purpose of this study is to propose a mass estimation method using a Markov decision process and compare its performance with a method using an artificial neural network model proposed in a previous study. First, how to extract feature vectors using discrete cosine transform was explained. Second, Markov chains were designed with codebooks obtained from the feature vector. A 1/8-scaled mockup of the reactor vessel for OPR1000 was employed, and all used signals were obtained by impacting its surface with several solid spherical masses. Next, the performance of mass estimation by the proposed Markov model was compared with that of the artificial neural network model. Finally, it was investigated that the proposed Markov model had matching error below 20% in mass estimation. That was a similar performance to the method using an artificial neural network model and considerably improved in comparison with the conventional methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.149-159
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• 2001

The conventional block-based motion prediction suffers, especially in low bit-rate video application, from shortcomings such as blocking artifacts of motion field and unstable motion estimation. To overcome the deficiency, this paper proposes one method of adopting a new motion compensation scheme based on the irregular triangular mesh structure while keeping the current block-based DCT coding structure of H.263 as much as possible. To represent the reconstructed previous frame using minimal number of control points, the proposed method designs content-adaptive irregular triangular meshes, and then, estimate the motion vector of each control point using the affine transformation-based matching. The predicted current frame is obtained by applying the affine transformation to each triangular mesh. Experiment with the several real video sequences shows improvement both in objective and subjective picture quality over the conventional block-based H.263 method.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.226-231
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• 2013

In The matching algorithm for automatic packaging of drugs is essential to determine whether the canister can exactly refill the suitable medicine. In this paper, we propose a hierarchical neural network with the upper and lower layers which can perform real-time processing and classification of many types of medicine bottles to prevent accidental medicine disaster. A few number of low-dimensional feature vector are extracted from the label images presenting medicine-bottle information. By using the extracted feature vectors, the lower layer of MLP(Multi-layer Perceptron) neural networks is learned. Then, the output of the learned middle layer of the MLP is used as the input to the upper layer of the MLP learning. The proposed hierarchical neural network shows good classification performance and real- time operation in the test of up to 30 degrees rotated to the left and right images of 100 different medicine bottles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.1
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• pp.25-44
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• 2010

With the increasing popularity of mobile devices, it has become necessary to protect private information and content in these devices. Face recognition has been favored over conventional passwords or security keys, because it can be easily implemented using a built-in camera, while providing user convenience. However, because mobile devices can be used both indoors and outdoors, there can be many illumination changes, which can reduce the accuracy of face recognition. Therefore, we propose a new face recognition method on a mobile device robust to illumination variations. This research makes the following four original contributions. First, we compared the performance of face recognition with illumination variations on mobile devices for several illumination normalization procedures suitable for mobile devices with low processing power. These include the Retinex filter, histogram equalization and histogram stretching. Second, we compared the performance for global and local methods of face recognition such as PCA (Principal Component Analysis), LNMF (Local Non-negative Matrix Factorization) and LBP (Local Binary Pattern) using an integer-based kernel suitable for mobile devices having low processing power. Third, the characteristics of each method according to the illumination va iations are analyzed. Fourth, we use two matching scores for several methods of illumination normalization, Retinex and histogram stretching, which show the best and $2^{nd}$ best performances, respectively. These are used as the inputs of an SVM (Support Vector Machine) classifier, which can increase the accuracy of face recognition. Experimental results with two databases (data collected by a mobile device and the AR database) showed that the accuracy of face recognition achieved by the proposed method was superior to that of other methods.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.739-747
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• 2018

Integration analysis of multi-sensor satellite images is becoming increasingly important. The first step in integration analysis is image registration between multi-sensor. SIFT (Scale Invariant Feature Transform) is a representative image registration method. However, optical image and SAR (Synthetic Aperture Radar) images are different from sensor attitude and radiation characteristics during acquisition, making it difficult to apply the conventional method, such as SIFT, because the radiometric characteristics between images are nonlinear. To overcome this limitation, we proposed a modified method that combines the SAR-SIFT method and shape descriptor vector DLSS(Dense Local Self-Similarity). We conducted an experiment using two pairs of Cosmo-SkyMed and KOMPSAT-2 images collected over Daejeon, Korea, an area with a high density of buildings. The proposed method extracted the correct matching points when compared to conventional methods, such as SIFT and SAR-SIFT. The method also gave quantitatively reasonable results for RMSE of 1.66m and 2.45m over the two pairs of images.

• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.765-774
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• 2002

The purpose of this paper is a design and implementation for korean character and pen-gesture recognition system in multimedia terminal, PDA and etc, which demand both a fast process and a high recognition rate. To recognize writing-types which are written by various users, the korean character recognition system uses a database which is based on the characteristic information of korean and the stroke information Which composes a phoneme, etc. In addition. it has a fast speed by the phoneme segmentation which uses the successive process or the backtracking process. The pen-gesture recognition system is performed by a matching process between the classification features extracted from an input pen-gesture and the classification features of 15 pen-gestures types defined in the gesture model. The classification feature is using the insensitive stroke information. i.e., the positional relation between two strokes. the crossing number, the direction transition, the direction vector, the number of direction code. and the distance ratio between starting and ending point in each stroke. In the experiment, we acquired a high recognition rate and a fart speed.

• Journal of Korea Multimedia Society
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• v.10 no.4
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• pp.548-558
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• 2007

This paper presents a method of location sensing of mobile objects using RF devices. By analyzing signal strengths between a certain number of fixed RF devices and a moving RF device, we can recognize the location of a moving object in real time. Firstly, signal strength values between RF devices are gathered, and then the values are normalized and constructed as a model feature vector for specific location. A number of model patterns are acquired and registered for all of the location which we want to recognize. For location sensing, signal strength information for an arbitrary moving RF device is acquired and compared with model feature vectors registered previously. In this case, distance value is calculated and the moving RF device is classified as one of the known model patterns. Experimental results show that our methods have performed the location sensing successfully with 100% rate of recognition when the number of fixed RF devices is 10 or more than 12. In terms of cost and applicability, experimental results seem to be very encouraging.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2192-2200
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• 2015

In this paper, we propose an efficient vehicle image compensation algorithm based on Histogram Equalization. The proposed a vehicle image compensation algorithm was elimination to the vehicle image shake using motion compensation and motion estimation. And, algorithm was calculated the histogram of pixel values from each sub-image by dividing the image as the constant size areas in order to image enhancement. Also, it had enhancement to the image by adjusting the gradient. The proposed algorithm was evaluate the difference between of performance and time, image by applied to the IP, and were confirmed the image enhancement with removing of vehicle camera image shake. In this paper, the proposed vehicle image enhancement algorithm was demonstrated effectiveness when compared to existing vehicle image stabilization, because the elimination of shake for the vehicle images used real-time processing without using a memory. And it was obtained the reduction effect of the computation time by the calculated through block matching, and obtained the better restoration result for naturalness of the image with the lowest noise.

• 한국가시화정보학회:학술대회논문집
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• 2003.11a
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• pp.39-42
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• 2003

Leading edge extension(LEX) in a highly swept shape applied to a delta wing features the modern air-fighters. The LEX vortices generated upon the upper surface of the wing at high angle of attack enhance the lift force of the delta wing by way of increased negative suction pressure over the surfaces. The present 3-D stereo PIV includes the Identification of 2-D cross-correlation equation, stereo matching of 2-D velocity vectors of two cameras, accurate calculation of 3-D velocity vectors by homogeneous coordinate system, removal of error vectors by a statistical method followed by a continuity equation criterion and so on. A delta wing model with or without LEX was immersed in a circulating water channel. Two high-resolution, high-speed digital cameras$(1280pixel\times1024pixel)$ were used to allow the time-resolved animation work. The present dynamic stereo PIV represents the complicated vortex behavior, especially, in terms of time-dependent characteristics of the vortices at given measuring sections. Quantities such as three velocity vector components, vorticity and other flow information can be easily visualized via the 3D time-resolved post-processing to make the easy understanding of the LEX effect or vortex emerging and collapse which are important phenomena occurring in the field of delta wing aerodynamics.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.116-122
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• 2010

As the importance of HCI(Human-Computer Interface) caused by dramatically developed computer technology is getting high, the requirement for the design of human friendly systems is also getting high. First of all, the personality and Emotional factor should be considered for implementing more human friendly systems. Many studies on Knowledge, Emotion and personality have been made, but the combined methods connecting these three factors is not so many investigated yet. It is known that memorizing process includes not only knowledge but also the emotion and the emotion state has much effects on the process of reasoning and decision making step. Accordingly, for implementing more human friendly efficient sophisticated intelligent system, the system considering these three factors should be modeled and designed. In this paper, knowledge-emotion reaction model was designed. Five types are defined for representing the personality and emotion reaction mechanism calculating emotion vector based on the extracted Thought threads by Type matching selection was proposed. This system is applied to the virtual memory and its emotional reactions are simulated.