• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.1
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• pp.91-99
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• 2012

The main objective of this study is to examine the feasibility of using lead zirconate titanate (PZT)'s direct piezoelectric response as vibrational feature for damage monitoring in beam structures. For the purpose, modal strain energy (MSE)-based damage monitoring in beam structures using dynamic strain response based on the direct piezoelectric effect of PZT sensor is proposed in this paper. The following approaches are used to achieve the objective. First, the theoretical background of PZT's direct piezoelectric effect for dynamic strain response is presented. Next, the damage monitoring method that utilizes the change in MSE to locate of damage in beam structures is outlined. For validation, forced vibration tests are carried out on lab-scale cantilever beam. For several damage scenarios, dynamic responses are measured by three different sensor types (accelerometer, PZT sensor and electrical strain gage) and damage monitoring tasks are performed thereafter. The performance of PZT's direct piezoelectric response for MSE-based damage monitoring is evaluated by comparing the damage localization results from the three sensor types.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.5 s.311
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• pp.38-47
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• 2006

Conventional classification method uses a single classifier based on shape or motion feature. However this method exhibits a weakness if naively used since the classification performance is highly sensitive to the accuracy of moving region to be detected. The detection accuracy, in turn, depends on the condition of the image background. In this paper, we propose to resolve the drawback and thus strengthen the classification reliability by employing a Bayesian decision fusion and by optimally combining the decisions of three classifiers. The first classifier is based on shape information obtained from Fourier descriptors while the second is based on the shape information obtained from image gradients. The third classifier uses motion information. Our experimental results on the classification Performance of human and vehicle with a static camera in various directions confirm a significant improvement and indicate the superiority of the proposed decision fusion method compared to the conventional Majority Voting and Weight Average Score approaches.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.19-26
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• 2006

In these days, multimedia data is transmitted and processed in compressed format. Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor (EHD) is time consuming as well as computationally expensive. To improve efficiency of compressed image retrieval, we propose a new edge histogram generation algorithm in DCT domain in this paper. Using the edge information provided by the only two AC coefficients of DCT coefficients, we can get edge directions and strengths directly in DCT domain. The experimental results demonstrate that our system has good performance in terms of retrieval efficiency and effectiveness.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.63.2-63.2
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• 2014

As a part of the "Dust, Ice, and Gas In Time" (DIGIT) key program on Herschel, we observed GSS30-IRS1, a Class I protostar located in Ophiuchus (d =125 pc), with Herschel/Photodetector Array Camera and Spectrometer (PACS). More than 70 lines were detected within a wavelength range from 50 ${\mu}m$ to 200 ${\mu}m$: CO lines from J = 14-13 to 41-40, several $H_2O$ lines of Eup = 100 K to 1500 K, 16 transitions of OH rotational lines, and two atomic [O I] lines at 63 and 145 ${\mu}m$. The [C II] line, known as a tracer of externally heated gas by the interstellar radiation field, is also detected at 158 ${\mu}m$. All lines, except [O I] and [C II], are detected only at the central spaxel of $9^{\prime\prime}.4{\times}9^{\prime\prime}.4$. The [O I] emission is extended along a NE-SW orientation, which is consistent with the known outflow direction, while the [C II] line is detected over all spaxels. One possible explanation of the detection of the [C II] line and no correlation of its spatial distribution with any other molecular emission is the existence of the enhanced ISRF nearby GSS30-IRS1. One interesting feature of GSS30-IRS1 is that the continuum emission is extended beyond the point-spread function (PSF), unlike the molecular line emission, indicative of significant external heating. The best-fit continuum model of GSS30-IRS1 with the physical structure including flared disk, envelope, and outflow shows that the internal luminosity is 11 $L_{\odot}$, and the region is also externally heated by a radiation field enhanced by a factor of 25 compared to the local standard interstellar field.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.83-86
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• 2013

In this paper, by using the Morphing, if the size of the eyes of both sides are not the same, we propose a method to correct the size of eyes area. First, by using the Haar-like feature from a input image that is input, to detect the shape of the eyes and face. After inverting the left and right eye region of one of the shape of the eyes detected sets the correspondence between the second with a line to control the shape of the eyes detected using eyes that is detected with canny edge, in the previous step. To the Warping to match the correspondence was then set in the previous step, an area of each eye. Then, I merge the image which merged in the eye area is detected from the original image. As a result, a system result of the experiment in the test image and face image seen from the front, the proposed, prove to be more efficient than a method of keying the size of the eye only.

• Journal of Digital Contents Society
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• v.11 no.4
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• pp.597-606
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• 2010

This paper describes a real-time camera tracking framework specifically designed to track a monocular camera in an AR workspace. Typically, the Kalman filter is often employed for the camera tracking. In general, however, tracking performances of conventional methods are seriously affected by unpredictable situations such as ambiguity in feature detection, occlusion of features and rapid camera shake. In this paper, a recursive Bayesian sampling framework which is also known as the particle filter is adopted for the camera pose estimation. In our system, the camera state is estimated on the basis of the Gaussian distribution without employing additional uncertainty model and sample weight computation. In addition, the camera state is directly computed based on new sample particles which are distributed according to the true posterior of system state. In order to verify the proposed system, we conduct several experiments for unstable situations in the desktop AR environments.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.313-319
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• 2007

In this paper, we propose a novel method to extract an area of car licence plate and codes of vehicle number from a photographed car image using features on vertical edges and a new Fuzzy neural network algorithm to recognize extracted codes. Prewitt mask is used in searching for vertical edges for detection of an area of vehicle number plate and feature information of vehicle number palate is used to eliminate image noises and extract the plate area and individual codes of vehicle number. Finally, for recognition of extracted codes, we use the proposed Fuzzy neural network algorithm, in which FCM is used as the learning structure between input and middle layers and Max_Min neural network is used as the learning structure within inhibition and output layers. Through a variety of experiments using real 150 images of vehicle, we showed that the proposed method is more efficient than others.

• Journal of Digital Contents Society
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• v.18 no.2
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• pp.267-274
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• 2017

Recently, there is a new trend about internet of things (IoT) such as shops with smart mirror around the fashion and beauty industry. Since smart mirror can display a content through a monitor which is attached to back of mirror system while looking through a mirror, it can be applied to various industries such as fashion, beauty and health care. This paper proposes an efficient learning system requiring no assistance from others for the hearing deaf who atrophy verbal skill and are inaccurate in pronunciation by using features of smart mirror. Also, this system proposes an efficient and simple lip reading method which can be applied to an embedded system and improves a learning efficiency by employing previously verified pronunciation training data.

• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.1-13
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• 2002

In this paper, we propose an object tracking system which can be convinced of moving area shaped on objects through color sequential images, decided moving directions of foot messengers or vehicles of image sequences. In static camera, we suggests a new evaluating method extracting co-occurrence matrix with feature vectors of RGB after analyzing and blocking difference images, which is accessed to field of camera view for motion. They are energy, entropy, contrast, maximum probability, inverse difference moment, and correlation of RGB color vectors. we describe how to analyze and compute corresponding relations of objects between adjacent frames. In the clustering, we apply an algorithm of FCM(fuzzy c means) to analyze matching and clustering problems of adjacent frames of the featured vectors, energy and entropy, gotten from previous phase. In the matching phase, we also propose a method to know correspondence relation that can track motion each objects by clustering with similar area, compute object centers and cluster around them in case of same objects based on membership function of motion area of adjacent frames.

• The KIPS Transactions:PartB
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• v.16B no.1
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• pp.47-54
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• 2009

Automatic object recognition in 3D measuring data is of great interest in many application fields e.g. computer vision, reverse engineering and digital factory. In this paper we present a software tool for a fully automatic object detection and parameter estimation in unordered and noisy point clouds with a large number of data points. The software consists of three interactive modules each for model selection, point segmentation and model fitting, in which the orthogonal distance fitting (ODF) plays an important role. The ODF algorithms estimate model parameters by minimizing the square sum of the shortest distances between model feature and measurement points. The local quadric surface fitted through ODF to a randomly touched small initial patch of the point cloud provides the necessary initial information for the overall procedures of model selection, point segmentation and model fitting. The performance of the presented software tool will be demonstrated by applying to point clouds.