• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.462-482
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• 2014

This paper proposes a new resampling detection method for images that detects whether an image has been resampled and recovers the corresponding resampling rate. The proposed method uses a given set of zeroing masks for various resampling factors to evaluate the convolution values of the input image with the zeroing masks. Improving upon our previous work, the proposed method detects more resampling factors by checking for some periodicity with an approximate detection mechanism. The experimental results demonstrate that the proposed method is effective and efficient.

• Journal of Industrial Technology
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• v.24 no.A
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• pp.67-73
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• 2004

The purpose of this study is to analyze the vibration signal of the revolution machine using the STFT(Short Time Fourier Transform). It is common to analyze the frequency of signal through FFT algorithm with the fixed sampling rate. However, in this situation the order spectrum information useful rather than the general frequency information with the fixed sampling rate. In this paper, the resampling technique was used for getting the information of order spectrum. In resampling process, the arithmetic amount and MSE(Mean Square Error) for various kinds of the signal interpolation was compared and presented the propriety of the interpolation method while developing analysis equipment. Order tracking was implemented using signal interpolation method which it has selected. Then the analyzed results were obtained through simulation using the STFT technique.

• Journal of Broadcast Engineering
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• v.8 no.1
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• pp.37-44
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• 2003

The standard approach to signal resampling is to fit the original image to a continuous model and resample the function at a desired rate. We used the compact B-spline function as the continuous model which produces less oscillatory behavior than other tails functions. In the case of nonuniform resampling based on a B-spline model, the digital signal is fitted to a spline model, and then the fitted signal is resampled at a space varying rate determined by the transformation function. It is simple to implement but may suffer from artifacts due to data loss. The main purpose of this paper is the derivation of optimal nonuniform resampling algorithm. For the optimal nonuniform formulation, the resampled signal is represented by a combination of shift varying splines determined by the transformation function. This optimal nonuniform resampling algorithm can be verified from the experiments that It produces less errors.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.50-55
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• 2002

The standard approach of image resampling is to fit the original image with continuous model and resample the function at a desired rate. We used the B-spline function as the continuous model because it oscillates less than the others. The main purpose of this paper is the derivation of a nonuniform optimal resampling algorithm. To derive it, needing approximation can be computed in three steps: 1) determining the I-spline coefficients by matrix inverse process, 2) obtaining the transformed-spline coefficients by the optimal resampling algorithm derived from the orthogonal projection theorem, 3) converting of the result back into the signal domain by indirect B-spline transformation. With these methods, we can use B-spline in the non-uniform resampling, which is proved to be a good kernel in uniform resampling, and can also verify the applicability from our experiments.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.357-371
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• 2014

There are many studies related to imbalanced data in which the class distribution is highly skewed. To address the problem of imbalanced data, previous studies deal with resampling techniques which correct the skewness of the class distribution in each sampled subset by using under-sampling, over-sampling or hybrid-sampling such as SMOTE. Ensemble methods have also alleviated the problem of class imbalanced data. In this paper, we compare around a dozen algorithms that combine the ensemble methods and resampling techniques based on simulated data sets generated by the Backbone model, which can handle the imbalance rate. The results on various real imbalanced data sets are also presented to compare the effectiveness of algorithms. As a result, we highly recommend the resampling technique combining ensemble methods for imbalanced data in which the proportion of the minority class is less than 10%. We also find that each ensemble method has a well-matched sampling technique. The algorithms which combine bagging or random forest ensembles with random undersampling tend to perform well; however, the boosting ensemble appears to perform better with over-sampling. All ensemble methods combined with SMOTE outperform in most situations.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.331-343
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• 2014

We propose two estimating procedures to analyze clustered interval-censored data with an informative cluster size based on a marginal model and investigate their asymptotic properties. One is an extension of Cong et al. (2007) to interval-censored data and the other uses the within-cluster resampling method proposed by Hoffman et al. (2001). Simulation results imply that the proposed estimators have a better performance in terms of bias and coverage rate of true value than an estimator with no adjustment of informative cluster size when the cluster size is related with survival time. Finally, they are applied to lymphatic filariasis data adopted from Williamson et al. (2008).

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.1
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• pp.37-43
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• 2003

A faster autofocusing method is proposed. The searching speed of microscope camera is limited by the long focusing time due to too much sampled digital image data. The improvement of autofocusing speed based on the down sampling is discussed analytically and is proved by experiments. The anticipated aliasing is found negligible in shilling rate of focus measure.

• Journal of Wetlands Research
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• v.20 no.2
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• pp.105-115
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• 2018

The frequency analysis of hydrometeorological data is one of the most important factors in response to natural disaster damage, and design standards for a disaster prevention facilities. In case of frequency analysis of hydrometeorological data, it assumes that observation data have statistical stationarity, and a parametric method considering the parameter of probability distribution is applied. For a parametric method, it is necessary to sufficiently collect reliable data; however, snowfall observations are needed to compensate for insufficient data in Korea, because of reducing the number of days for snowfall observations and mean maximum daily snowfall depth due to climate change. In this study, we conducted the frequency analysis for snowfall using the Bootstrap method and SIR algorithm which are the resampling methods that can overcome the problems of insufficient data. For the 58 meteorological stations distributed evenly in Korea, the probability of snowfall depth was estimated by non-parametric frequency analysis using the maximum daily snowfall depth data. The results of frequency based snowfall depth show that most stations representing the rate of change were found to be consistent in both parametric and non-parametric frequency analysis. According to the results, observed data and Bootstrap method showed a difference of -19.2% to 3.9%, and the Bootstrap method and SIR(Sampling Importance Resampling) algorithm showed a difference of -7.7 to 137.8%. This study shows that the resampling methods can do the frequency analysis of the snowfall depth that has insufficient observed samples, which can be applied to interpretation of other natural disasters such as summer typhoons with seasonal characteristics.

• Journal of Platform Technology
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• v.11 no.2
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• pp.26-38
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• 2023

This paper is a study on a transport robot capable of autonomously driving to a destination using a QR code in an indoor environment. The transport robot was designed and manufactured by attaching a lidar sensor so that the robot can maintain a certain distance during movement by detecting the distance between the camera for recognizing the QR code and the left and right walls. For the location information of the delivery robot, the QR code image was enlarged with Lanczos resampling interpolation, then binarized with Otsu Algorithm, and detection and analysis were performed using the Zbar library. The QR code recognition experiment was performed while changing the size of the QR code and the traveling speed of the transport robot while the camera position of the transport robot and the height of the QR code were fixed at 192cm. When the QR code size was 9cm × 9cm The recognition rate was 99.7% and almost 100% when the traveling speed of the transport robot was less than about 0.5m/s. Based on the QR code recognition rate, an experiment was conducted on the case where the destination is only going straight and the destination is going straight and turning in the absence of obstacles for autonomous driving to the destination. When the destination was only going straight, it was possible to reach the destination quickly because there was little need for position correction. However, when the destination included a turn, the time to arrive at the destination was relatively delayed due to the need for position correction. As a result of the experiment, it was found that the delivery robot arrived at the destination relatively accurately, although a slight positional error occurred while driving, and the applicability of the QR code-based destination self-driving delivery robot was confirmed.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.27-30
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• 1998

본 연구에서는 청각계의 시간 및 주파수 특성을 고려한 과도음의 시간-주파수 신호해석 기법인 VFT-STFT (STFT with Variable Frequency Resollution)을 제안하고자 한다. VFT-STFT은 downsampling와 FFT를 반복적으로 수행하여 주파수 대역에 따라 주파수 및 시간 분해능이 청각계의 특성과 유사한 기존의 VFR-FFT에 그 뿌리를 두고 있다. 그러나, 본 연구에서는 기존의 VFT-FFT 알고리즘에 overlap인자를 도입하여 시간-주파수 해석 결과를 구하고, 2/3-rate resampling에 의해 추가로 구성된 시간-주파수 해석 결과의 일부를 기존의 시간-주파수 해석 결과에 이식시킴으로서 기존의 VFT-FFT가 갖는 overlap과 spectral loss 등의 문제점을 최소화하고자 한다.