• Journal of the Korean Society for Nondestructive Testing
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• v.15 no.2
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• pp.386-394
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• 1995

The fringes developed by misalignment, an application of Moire method measuring small deformation of specimen, was transformed to frequency function. After that, theory of normalization was applied to derive the equations explaining the relation of the deformation and Moire fringes. Above all, the equations were produced to explain the rotation and increasing of fringes. In addition to that, the relation of fringe number and strain was illustated with the equations deduced from frequency function and geometrical method respectively. These two expressions were more effective than the used ones owing to the one can accommodate the other.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1278-1290
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• 2008

This paper proposes a preprocessing method and a neural network based character recognizer to enhance the overall performance of the license plate recognition system. First, plate outlines are extracted by virtual line matching, and then the 4 vertexes are obtained by calculating intersecting points of extracted lines. By these vertexes, plate image is reconstructed as rectangle-shaped image by bilinear transform. Finally, the license plate is recognized by the neural network based classifier which had been trained using delta-bar-delta algorithm. Various license plate images were used in the experiments, and the proposed plate normalization enhanced the recognition performance up to 16 percent.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4B
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• pp.319-328
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• 2009

This study quantified the data by applying the EDA techniques considering the data structure, and the results were then used for the frequency analysis. Although traditional methods based on the method of moments provide very sensitive statistics to the extreme values, the EDA techniques have an advantage of providing very stable statistics with their small variation. For the application of the EDA techniques to the frequency analysis, it is necessary to normalization transform and inverse-transform to conserve the skewness of the raw data. That is, it is necessary to transform the raw data to make the data follow the normal distribution, to estimate the statistics by applying the EDA techniques, and then finally to inverse-transform the statistics of transformed data. These statistics decided are then applied for the frequency analysis with a given probability density function. This study analyzed the annual maxima one hour rainfall data at Seoul and Pohang stations. As a result, it was found that more stable rainfall quantiles, which were also less sensitive to extreme values, could be estimated by applying the EDA techniques. This methodology may be effectively used for the frequency analysis of rainfall at stations with especially high annual variations of rainfall due to climate change, etc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8C
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• pp.711-720
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• 2012

In this paper, we introduce the implementation of driver fatigue monitering system and its result. Input video device is selected commercially available web-cam camera. Haar transform is used to face detection and adopted illumination normalization is used for arbitrary illumination conditions. Facial image through illumination normalization is extracted using Haar face features easily. Eye candidate area through illumination normalization can be reduced by anthropometric measurement and eye detection is performed by PCA and Circle Mask mixture model. This methods achieve robust eye detection on arbitrary illumination changing conditions. Drowsiness state is determined by the level on illumination normalize eye images by a simple calculation. Our system alarms and operates seatbelt on vibration through controller area network(CAN) when the driver's doze level is detected. Our algorithm is implemented with low computation complexity and high recognition rate. We achieve 97% of correct detection rate through in-car environment experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.2
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• pp.164-173
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• 2013

In this paper, we propose multi-frame based super resolution algorithm by using motion vector normalization and edge pattern analysis. Existing algorithms have constraints of sub-pixel motion and global translation between frames. Thus, applying of algorithms is limited. And single-frame based super resolution algorithm by using discrete wavelet transform which robust to these problems is proposed but it has another problem that quantity of information for interpolation is limited. To solve these problems, we propose motion vector normalization and edge pattern analysis for 2*2 block motion estimation. The experimental results show that the proposed algorithm has better performance than other conventional algorithms.

• Journal of Korea Multimedia Society
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• v.14 no.4
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• pp.538-545
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• 2011

Today, there is a wide variety of digital contents on the Internet. Especially, comic images are one of popular digital contents. Most of them are scanned from comic books by digital scanners, but they were not normalized in sense of their size, skew and boundary margin. The normalization is very important step in comic image analysis. It can be achieved by finding out-boundary rectangles in comic images. In this paper, we propose a method for detecting the out-boundary rectangle using the gradient Radon transform in comic images. We applied the Radon transform using image gradients to extract line segments which are the out-boundary rectangle sides' candidates in comic images. The final out-boundary rectangle can be detected by local histogram and the candidate line segments. Experimental results show that our proposed method effectively detect the out-boundary rectangle in comic images.

• Journal of the Korean earth science society
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• v.28 no.1
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• pp.87-104
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• 2007

As part of the SPVS (Short-Period Variability Survey) which is a wide-field $(90'{\times}60')$ photometric monitering program at Bohyunsan Optical Astronomy (BOAO), we performed V band time-series CCD photometric observations ofthe young open cluster NGC 129 for 11 nights between October 12, 2004 and November 3, 2005 using the 155mm refractor equipped with $3K{\times}2K$ CCD camera. From the observation we obtained 2400 V band CCD frames and color-magnitude diagram of the cluster. To transform instrumental magnitude to standard magnitude, we applied ensemble normalization technique to all observed time-series data. After the photometric reduction process, we examined variations of 9537 stars. As a result, sixty six of the new variable stars were discovered. To determine the periods of the sevariables, we used DFT(Discrete Fourier Transform) and phase-matching technique. According to light curve shape, period, amplitude and the position on a C-M diagram, we classified these variables as 9 SPB type, 9 ${\delta}$ Scuti type, 29 eclipsing, 17 long term variables. However, two of them were not classified. From this study, we learned that small telescopes could be a very useful tool to observe variable stars in the open cluster in survey program.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.244-247
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• 1999

in this paper, we propose the recognition system of face using polynomial coefficients to recognize fact images using neural network. The system consists of following steps. First step, the sizes of fare images is reduced sizes of input images to 1/4 using wavelet transform. Second step, the polynomial coefficients is obtained from low frequency coefficient matrix after 3 level wavelet transform. Third step, polynomial coefficients is normalized. The of range of normalization is from -1 to 1. Last, Face images is trained and recognized using neural network with error back propagation algorithm.

• The KIPS Transactions:PartB
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• v.18B no.4
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• pp.221-230
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• 2011

Digital comic images are one of popular contents on the Internet. Usually, they are scanned from comic books by digital scanners. Without post-processing, they may have different sizes, skews and margins other than contents at the boundary. To normalize the size of their contents without the skews and margins is an important step in comic image analysis and application such as content-based comic image retrieval system. In this paper, we propose a method to detect a box frame in comic images by extracting of line segments using the gradient Radon transform. The box frame in comic images is the maximum rectangle which consists of contents without margins. We use the detected box frame to normalize the size of comic images and to make them no skew. In addition, the proposed method is implemented by OpenCL to speed up the detection of the line segments. Experimental results show that our proposed method effectively detects the box frame in comic images.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.48-54
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• 2013

Purpose: This study evaluated the feasibility of using a discrete wavelet transform (DWT) method as a preprocessing tool for visible/near-infrared spectroscopy (VIS/NIRS) with a spectroscopic transmittance dataset for predicting the internal quality of cherry tomatoes. Methods: VIS/NIRS was used to acquire transmittance spectrum data, to which a DWT was applied to generate new variables in the wavelet domain, which replaced the original spectral signal for subsequent partial least squares (PLS) regression analysis and prediction modeling. The DWT concept and its importance are described with emphasis on the properties that make the DWT a suitable transform for analyzing spectroscopic data. Results: The $R^2$ values and root mean squared errors (RMSEs) of calibration and prediction models for the firmness, sugar content, and titratable acidity of cherry tomatoes obtained by applying the DWT to a PLS regression with a set of spectra showed more enhanced results than those of each model obtained from raw data and mean normalization preprocessing through PLS regression. Conclusions: The developed DWT-incorporated PLS models using the db5 wavelet base and selected approximation coefficients indicate their feasibility as good preprocessing tools by improving the prediction of firmness and titratable acidity for cherry tomatoes with respect to $R^2$ values and RMSEs.