• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.7
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• pp.9-15
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• 2019

The purpose of present study is to assess the maximum width of the surface cracks using the histogram analysis of image processing techniques in concrete structures. For this purpose, the concrete crack image is acquired by the camera. The image is Grayscale coded and Binary coded. After Binary coded image is Dilate and Erode coded, the image is then recognized as separated objects by applying Labeling techniques. Over time, dust and stains may occur naturally on the surface of concrete. The crack image of concrete may include shadows and reflections by lighting depending on a surrounding conditions. In general, concrete cracks occur in a continuous pattern and noise of image appears in the form of shot noises. Bilateral Blurring and Adaptive Threshold apply to the Grayscale image to eliminate these effects. The remaining noises are removed by the object area ratio to the Labeled area. The maximum numbers of pixels and its positions in the crack objects without noises are calculated in x-direction and y-direction by Histogram analysis. The widths of the crack are estimated by trigonometric ratio at the positions of the pixels maximum numbers for the Labeled objects. Finally, the maximum crack width estimated by the proposed method is compared to the crack width measured with the crack gauge. The proposed method by the present study may increase the reliability for the estimation of maximum crack width using image processing techniques in concrete surface images.

• Journal of the Korean Society for Railway
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• v.20 no.1
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• pp.11-19
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• 2017

Since operation of railway trains is a major source of particle pollution in tunnel air, a particle removal device can be an effective measure to remove wear particles. To obtain design conditions of the particle removal device that will be installed underneath the railway trains, the wind speed and particle concentration underneath the trains were investigated using a three-dimensional ultrasonic anemometer and a DustTrak aerosol monitor, respectively. The measurements were made for the trains running on Seoul Metropolitan Subway Line 5 on February 10, 2015. The data were analyzed according to the track geometry (straight, curved) and train speed pattern (acceleration, cruising, and deceleration) between stations. Train speed was also analyzed. The average wind speed and $PM_{10}$ concentration underneath the trains were ~30% of the train speed and ${\sim}200{\mu}g/m^3$ for both straight and curved sections. Average $PM_{10}$ concentration for deceleration sections was higher than that for acceleration sections.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.20-38
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• 2014

Vegetation phenology is the most important indicator of ecosystem response to climate change. Therefore it is necessary to continuously monitor forest phenology. This paper analyzes the phenological characteristics of forests in South Korea using the MODIS vegetation index with error from clouds or other sources removed using the HANTS algorithm. After using the HANTS algorithm to reduce the noise of the satellite-based vegetation index data, we were able to confirm that phenological transition dates varied strongly with altitudinal gradients. The dates of the start of the growing season, end of the growing season and the length of the growing season were estimated to vary by +0.71day/100m, -1.33day/100m and -2.04day/100m in needleleaf forests, +1.50day/100m, -1.54day/100m and -3.04day/100m in broadleaf forests, +1.39day/100m, -2.04day/100m and -3.43day/100m in mixed forests. We found a linear pattern of variation in response to altitudinal gradients that was related to air temperature. We also found that broadleaf forests are more sensitive to temperature changes compared to needleleaf forests.

• Journal of Astronomy and Space Sciences
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• v.24 no.4
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• pp.349-366
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• 2007

We designed and developed a multi-purpose CCD camera system for three kinds of CCDs; KAF-0401E($768{\times}512$), KAF-1602E($1536{\times}1024$), KAF-3200E($2184{\times}1472$) made by KODAK Co.. The system supports fast USB port as well as parallel port for data I/O and control signal. The packing is based on two stage circuit boards for size reduction and contains built-in filter wheel. Basic hardware components include clock pattern circuit, A/D conversion circuit, CCD data flow control circuit, and CCD temperature control unit. The CCD temperature can be controlled with accuracy of approximately $0.4^{\circ}C$ in the max. range of temperature, ${\Delta}33^{\circ}C$. This CCD camera system has with readout noise $6\;e^-$, and system gain $5\;e^-/ADU$. A total of 10 CCD camera systems were produced and our tests show that all of them show passable performance.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.421-430
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• 2018

Many voice recognition systems use methods such as MFCC, HMM to acknowledge human voice. This recognition method is designed to analyze only a targeted sound which normally appears between a human and a device one. However, the recognition capability is limited when there is a group sound formed with diversity in wider frequency range such as dog barking and indoor sounds. The frequency of overlapped sound resides in a wide range, up to 20KHz, which is higher than a voice. This paper proposes the new recognition method which provides wider frequency range by conjugating the Wideband Sound Spectrogram and the Keras Sequential Model based on DNN. The wideband sound spectrogram is adopted to analyze and verify diverse sounds from wide frequency range as it is designed to extract features and also classify as explained. The KSM is employed for the pattern recognition using extracted features from the WSS to improve sound recognition quality. The experiment verified that the proposed WSS and KSM excellently classified the targeted sound among noisy environment; overlapped sounds such as dog barking and indoor sounds. Furthermore, the paper shows a stage by stage analyzation and comparison of the factors' influences on the recognition and its characteristics according to various levels of noise.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.2
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• pp.93-101
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• 2015

This study was conducted to analyze the relationship between tree-ring growth of Quercus acutissima and climatic variables by dendroclimatological method. Annual tree-ring growth data of Quercus acutissima collected by the $5^{th}$ National Forest Inventory (NFI5) were organized to analyze the spatial distribution of the species growth pattern. To explain the relationship between tree-ring growth of Quercus acutissima and climatic variables, monthly temperature and precipitation data from 1950 to 2010 were compared with tree-ring growth data for each county. When tree-ring growth data were analyzed through cluster analysis based on similarity of climatic conditions, four clusters were identified. In addition, index chronology of Quercus acutissima for each cluster was produced through cross-dating and standardization procedures. The adequacy of index chronologies was tested using basic statistics such as mean sensitivity, auto correlation, signal to noise ratio, and expressed population signal of annual tree-ring growth. Response function analysis was conducted to reveal the relationship between tree-ring growth and climatic variables for each cluster. The results of this study are expected to provide valuable information necessary for estimating local growth characteristics of Quercus acutissima and for predicting changes in tree growth patterns caused by climate change.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.289-307
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• 2010

The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model selection for the general case of arbitrary (random or deterministic) design matrices and arbitrary nonzero entries of the signal. In this regard, it generalizes the notion of incoherence in the existing literature on model selection and introduces two fundamental measures of coherence-termed as the worst-case coherence and the average coherence-among the columns of a design matrix. It utilizes these two measures of coherence to provide an in-depth analysis of a simple, model-order agnostic one-step thresholding (OST) algorithm for model selection and proves that OST is feasible for exact as well as partial model selection as long as the design matrix obeys an easily verifiable property, which is termed as the coherence property. One of the key insights offered by the ensuing analysis in this regard is that OST can successfully carry out model selection even when methods based on convex optimization such as the lasso fail due to the rank deficiency of the submatrices of the design matrix. In addition, the paper establishes that if the design matrix has reasonably small worst-case and average coherence then OST performs near-optimally when either (i) the energy of any nonzero entry of the signal is close to the average signal energy per nonzero entry or (ii) the signal-to-noise ratio in the measurement system is not too high. Finally, two other key contributions of the paper are that (i) it provides bounds on the average coherence of Gaussian matrices and Gabor frames, and (ii) it extends the results on model selection using OST to low-complexity, model-order agnostic recovery of sparse signals with arbitrary nonzero entries. In particular, this part of the analysis in the paper implies that an Alltop Gabor frame together with OST can successfully carry out model selection and recovery of sparse signals irrespective of the phases of the nonzero entries even if the number of nonzero entries scales almost linearly with the number of rows of the Alltop Gabor frame.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.3
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• pp.12-26
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• 2000

In this paper, we propose a post-processing algorithm to remove false minutiae which decrease the overall performance of an automatic fingerprint identification system by increasing computational complexity, FAR(False Acceptance Rate), and FRR(False Rejection Rate) in matching process. The proposed algorithm extracts candidate minutiae from thinned fingerprint image. Considering characteristics of the thinned fingerprint image, the algorithm selects the minutiae that may be false and located in recoverable area. If the area where the selected minutiae reside is thinned incorrectly due to noise and loss of information, the algorithm recovers the area and the selected minutiae are removed from the candidate minutiae list. By examining the ridge pattern of the block where the candidate minutiae are found, true minutiae are recovered and in contrast, false minutiae are filtered out. In an experiment, Fingerprint images from NIST special database 14 are tested and the result shows that the proposed algorithm reduces the false minutiae extraction rate remarkably and increases the overall performance of an automatic fingerprint identification system.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.23 no.1
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• pp.48-58
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• 2001

After performing mandibular setback surgery, we found some changes in patterns and organs of speech. This investigation was undertaken to investigate the aspect and degree of speech patterns according to the amount of surgical setback in mandibular prognathic patients. Thirteen patients with skeletal Class III malocclusion were studied preoperative and postoperative over 6 months. They had undergone the mandible setback operation via bilateral sagittal split ramus osteotomy(BSSRO). We split the patients into two groups. Group 1 included patients whose degree of mandibular setback was 6mm or less, and Group 2 above 6mm. Control group was two adults wish normal speech patterns. A phonetician performed narrow phonetic transcriptions of tape-recorded words and sentences produced by each of the patients and the acoustic characteristics of the plosives, fricatives, and flaps were analyzed with a phonetic computer program (Computerized Speech Lab(CSL) Model 4300B(USA)). The results are as follows: 1. Generally, Patients showed longer closure duration of plosives, shorter VOT(voice onset time) and higher ratio of closure duration against VOT. 2. Patients showed more frequent diffuse distribution than the control group in frication noise energy of fricatives. 3. In fricatives, frequency of compact from were higher in group 1 than in group 2. 4. Generally, a short duration of closure for /ㄹ/ was not realized in the patient's flaps. Instead, it was realized as fricatives, sonorant with a vowel-like formant structure, or trill type consonant. 5. Abnormality of the patient's articulation was reduced, but adaptation of their articulation after surgery was not perfect and the degree of adaptation was different according to the degree of surgical setback.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.519-527
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• 2003

Speech is much influenced by the existence of outliers which are introduced by such an unexpected happenings as additive background noise, change of speaker's utterance pattern and voice detection errors. These kinds of outliers may result in severe degradation of speaker recognition performance. In this paper, we proposed the GMM based on robust principal component analysis (RPCA-GMM) using M-estimation to solve the problems of both ouliers and high dimensionality of training feature vectors in speaker identification. Firstly, a new feature vector with reduced dimension is obtained by robust PCA obtained from M-estimation. The robust PCA transforms the original dimensional feature vector onto the reduced dimensional linear subspace that is spanned by the leading eigenvectors of the covariance matrix of feature vector. Secondly, the GMM with diagonal covariance matrix is obtained from these transformed feature vectors. We peformed speaker identification experiments to show the effectiveness of the proposed method. We compared the proposed method (RPCA-GMM) with transformed feature vectors to the PCA and the conventional GMM with diagonal matrix. Whenever the portion of outliers increases by every 2%, the proposed method maintains almost same speaker identification rate with 0.03% of little degradation, while the conventional GMM and the PCA shows much degradation of that by 0.65% and 0.55%, respectively This means that our method is more robust to the existence of outlier.