• Applied Microscopy
• /
• v.38 no.3
• /
• pp.275-278
• /
• 2008

Electron tomography (ET) is an electron microscopic technique for obtaining a 3-D image from any electron microscopy specimen and its application in biomedical science has been increased thanks to development of electron microscopy and related technologies during the last decade. There are few researches on ET in Korea during this period. Although the importance of ET has been recognized recently by many researchers, initial approach to electron tomographic research is not easy for beginners. The 4th International Congress on Electron Tomography (4 ICET) was held on Nov $5{\sim}8$, 2006, at San Diego. The program dealt instrumentation, reconstruction algorithm, visualization/quantitative analysis and electron tomographic presentation of biological specimen and nano particles. 1 have summarized oral presentations and analyzed the posters presented on the meeting. Cryo-electron microscopic system was popular system for ET and followed conventional transmission electron microscopic system. Cultured cell line and tissue were most popular specimens analyzed and microorganisms including bacteria and virus also constituted important specimens. This analysis provides a current state of art in ET research and a guide line for practical application of ET and further research strategies.

• Journal of Mechanical Science and Technology
• /
• v.18 no.12
• /
• pp.2265-2272
• /
• 2004

The aquaculture tank is used for breeding fish in sea water which was pumped up to land. The flow characteristics in the aquaculture were investigated with varying the tank geometry and flow rate. The numerical analysis has been employed for calculating the velocity and temperature distributions in a water tank of rectangular type. The finite volume method and SIMPLE algorithm with 3-dimensional standard $\kappa$-$\varepsilon$ turbulence model were used for the numerical analysis. For comparison with experimental results, the PIV system was applied to visualize the flow patterns quantitatively. The numerical results showed good agreements with the experimental results. The mean velocity and temperature versus aquarium depth were represented for various circulating flow rates. Especially, the aquaculture environment is recommended that the aquarium depth has to be d=0.5 m, and this case is the condition of higher velocity and temperature in winter season.

• Korean Journal of Remote Sensing
• /
• v.28 no.6
• /
• pp.623-632
• /
• 2012

In this paper, we analyzed the effect of wavelet decomposition levels in feature extraction for anomaly detection from hyperspectral imagery. After wavelet analysis, anomaly detection was experimentally performed using the RX detector algorithm to analyze the detecting capabilities. From the experiment for anomaly detection using CASI imagery, the characteristics of extracted features and the changes of their patterns showed that radiance curves were simplified as wavelet transform progresses and H bands did not show significant differences between target anomaly and background in the previous levels. The results of anomaly detection and their ROC curves showed the best performance when using the appropriate sub-band decided from the visual interpretation of wavelet analysis which was L band at the decomposition level where the overall shape of profile was preserved. The results of this study would be used as fundamental information or guidelines when applying wavelet transform to feature extraction and selection from hyperspectral imagery. However, further researches for various anomaly targets and the quantitative selection of optimal decomposition levels are needed for generalization.

• Journal of Korea Society of Industrial Information Systems
• /
• v.12 no.4
• /
• pp.164-168
• /
• 2007

In this paper, we propose the eye detection algorithms which can apply to the Real-Time Embedded systems. To detect the eye region, the feature vectors are obtained at the first step and then, PCA(Principal Component Analysis) and amplitude projection method is applied to composite the feature vectors. In the decision state, the estimated probability density functions (PDFs) are applied by the proposed Bayesian method to detect eye region in an image from the CCD camera. The simulation results show that our proposed method has a good detection rate on the frontal face and this can be applied to the embedded system because of its small amount of the mathematical complexity.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.6
• /
• pp.813-819
• /
• 2014

The purpose of this study was to extract accurate parameters of facial movement features using 3-D motion capture system in speech recognition technology through lip-reading. Instead of using the features obtained through traditional camera image, the 3-D motion system was used to obtain quantitative data for actual facial movements, and to analyze 11 variables that exhibit particular patterns such as nose, lip, jaw and cheek movements in monosyllable vocalizations. Fourteen subjects, all in 20s of age, were asked to vocalize 11 types of Korean vowel monosyllables for three times with 36 reflective markers on their faces. The obtained facial movement data were then calculated into 11 parameters and presented as patterns for each monosyllable vocalization. The parameter patterns were performed through learning and recognizing process for each monosyllable with speech recognition algorithms with Hidden Markov Model (HMM) and Viterbi algorithm. The accuracy rate of 11 monosyllables recognition was 97.2%, which suggests the possibility of voice recognition of Korean language through quantitative facial movement analysis.

• Journal of Digital Contents Society
• /
• v.10 no.2
• /
• pp.319-326
• /
• 2009

In this paper, we present an algorithm which recognize hand shape in real time using only image without adhering separate sensor. Hand recognizes using edge orientation histogram, which comes under a constant quantity of 2D appearances because hand shape is intricate. This method suit hand pose recognition in real time because it extracts hand space accurately, has little computation quantity, and is less sensitive to lighting change using color information in complicated background. Method which reduces recognition error using principal component analysis(PCA) method to can recognize through hand shape presentation direction change is explained. A case that hand shape changes by turning 3D also by using this method is possible to recognize. Human interface system manufacture technique, which controls a home electric appliance or game using, suggested method at experience could be applied.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.12 no.1
• /
• pp.39-47
• /
• 2004

The objective of this study is to analyse the spray characteristics according to the injection duration under ambient pressure condition and to investigate the relationship between vorticity and entropy for controlling diffusion process that is the most important thing during the intake stroke injection process. Therefore, the spray velocity was obtained by using the PIV method that has been an useful optical diagnostics technology, and vorticity calculated from spray velocity component with vorticity algorithm. In addition, the homogeneous diffusion rate of spray was quantified by using the entropy analysis based on the Boltzmann's statistical thermodynamics. From these method, we found that as injection duration increases, spray velocity increases and the location of vortex is moved to the downstream of spray. In the same condition, as the entropy decrease, mean vorticity increases. This means that the concentration of spray droplets caused by the increase of injection duration is more effective than the increase of momentum dissipation.

• Journal of KIISE
• /
• v.42 no.7
• /
• pp.868-877
• /
• 2015

The barcode area extraction from images has been extensively studied, and existing methods exploit frequency characteristics or depend on the Hough transform (HT). However, the slantedness of the images and noise affects the performance of these approaches. Moreover, it is difficult to deal with the case where an image contains multiple barcodes. We therefore propose a barcode detection algorithm that is robust under such unfavorable conditions. The pre-processing step implements a probabilistic Hough transform to determine the areas that contain barcodes with a high probability, regardless of the slantedness, noise, and the number of instances. Then, a frequency component analysis extracts the barcodes. We successfully implemented the proposed system and performed a series of barcode extraction tests.

• Biomedical Engineering Letters
• /
• v.8 no.4
• /
• pp.373-382
• /
• 2018

Since epileptic seizure is unpredictable and paroxysmal, an automatic system for seizure detecting could be of great significance and assistance to patients and medical staff. In this paper, a novel method is proposed for multichannel patient-specific seizure detection applying the earth mover's distance (EMD) in scalp EEG. Firstly, the wavelet decomposition is executed to the original EEGs with five scales, the scale 3, 4 and 5 are selected and transformed into histograms and afterwards the distances between histograms in pairs are computed applying the earth mover's distance as effective features. Then, the EMD features are sent to the classifier based on the Bayesian linear discriminant analysis (BLDA) for classification, and an efficient postprocessing procedure is applied to improve the detection system precision, finally. To evaluate the performance of the proposed method, the CHB-MIT scalp EEG database with 958 h EEG recordings from 23 epileptic patients is used and a relatively satisfactory detection rate is achieved with the average sensitivity of 95.65% and false detection rate of 0.68/h. The good performance of this algorithm indicates the potential application for seizure monitoring in clinical practice.

• Journal of Broadcast Engineering
• /
• v.26 no.1
• /
• pp.79-87
• /
• 2021

In this paper, we analysis the semi-supervised learning (SSL), which is adopted in order to train a deep learning-based classification model using the small number of labeled data. The conventional SSL techniques can be categorized into consistency regularization, entropy-based, and pseudo labeling. First, we describe the algorithm of each SSL technique. In the experimental results, we evaluate the classification accuracy of each SSL technique varying the number of labeled data. Finally, based on the experimental results, we describe the limitations of SSL technique, and suggest the research direction to improve the classification performance of SSL.