• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.67-73
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• 2015

In a distribution of digital image, there is a serious problem that is the image alteration by a forger. For the problem solution, this paper proposes the forensic decision algorithm of a median filtering (MF) image using the feature vector based on a coefficient of variation (c.v.) of Fourier transform. In the proposed algorithm, we compute Fourier transform (FT) coefficients of row and column line respectively of an image first, then c.v. between neighboring lines is computed. Subsquently, 10 Dim. feature vector is defined for the MF detection. On the experiment of MF detection, the proposed scheme is compared to MFR (Median Filter Residual) and Rhee's MF detection schemes that have the same 10 Dim. feature vector both. As a result, the performance is excellent at Unaltered, JPEG (QF=90), Down scaling (0.9) and Up scaling (1.1) images, and it showed good performance at Gaussian filtering ($3{\times}3$) image. However, in the performance evaluation of all measured items of the proposed scheme, AUC (Area Under ROC (Receiver Operating Characteristic) Curve) by the sensitivity and 1-specificity approached to 1 thus, it is confirmed that the grade of the performance evaluation is rated as 'Excellent (A)'.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.58-66
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• 2003

In this paper. an image compression of embedded zerotree structure using multiwavelet filter banks is proposed. Multiwavelet is used DGHM(Donovan, Geronimo, Hardin, and Massopust) scaling functions and wavelet functions of a new method with two channel fillet banks. The important properties of the DGHM multiwavelet are orthogonality and approximation order. The DCHM muitiwavelet using the this paper preserves the approximation order=2 for better energy compaction and perfect reconstruction. Image compression using the preposed DGHM multiwavelet is better PSNR for compression ratio than single Daubechies wavelet(D4), Biorthogoanl wavelet, and GHM(Geronimo, Hardin, and Massopust) multi wavelet.

• Earthquakes and Structures
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• v.3 no.6
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• pp.839-852
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• 2012

Earthquake records are often analyzed in various earthquake engineering problems, making time-frequency analysis for such records of primary concern. The best tool for such analysis appears to be based on wavelet functions; selection of which is not an easy task and is commonly carried through trial and error process. Furthermore, often a particular wavelet is adopted for analysis of various earthquakes irrespective of record's prime characteristics, e.g. wave's magnitude. A wavelet constructed based on records' characteristics may yield a more accurate solution and more efficient solution procedure in time-frequency analysis. In this study, a low-pass reconstruction filter is obtained for each earthquake record based on multi-resolution decomposition technique; the filter is then assigned to be the normalized version of the last approximation component with respect to its magnitude. The scaling and wavelet functions are computed using two-scale relations. The calculated wavelets are highly efficient in decomposing the original records as compared to other commonly used wavelets such as Daubechies2 wavelet. The method is further advantageous since it enables one to decompose the original record in such a way that a clear time-frequency resolution is obtained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5624-5638
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• 2016

A novel method based on Surf points is proposed to detect and lock-track single ground target in aerial videos. Videos captured by moving cameras contain complex motions, which bring difficulty in moving object detection. Our approach contains three parts: moving target template detection, search area estimation and target tracking. Global motion estimation and compensation are first made by grids-sampling Surf points selecting and matching. And then, the single ground target is detected by joint spatial-temporal information processing. The temporal process is made by calculating difference between compensated reference and current image and the spatial process is implementing morphological operations and adaptive binarization. The second part improves KALMAN filter with surf points scale information to predict target position and search area adaptively. Lastly, the local Surf points of target template are matched in this search region to realize target tracking. The long-term tracking is updated following target scaling, occlusion and large deformation. Experimental results show that the algorithm can correctly detect small moving target in dynamic scenes with complex motions. It is robust to vehicle dithering and target scale changing, rotation, especially partial occlusion or temporal complete occlusion. Comparing with traditional algorithms, our method enables real time operation, processing $520{\times}390$ frames at around 15fps.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.163-170
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• 2007

In this paper, we propose that the polyphase scaler whose performance to that of the bicubic method, has less complexity in hardware structure. In order to get the new information, proposed system is based on the group delay which is one of the digital filter characteristics. The performance of this system is superior to that of bicubic algorithm which is well known. Because the hardware structure is simpler than other image scalers, we can adopt this system for mobile devices easily. The previous polyphase filters make blurring noise which is generated by up-scaling. We replace polyphase filters by boost-up filter to get vivid image. The proposed scaler is verified by Xilinx Virtex2 FPGA and is used as digital Boom in mobile camera phone.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.52-62
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• 2008

In this paper, we develop a method that changes the resolutions of images in an arbitrary block transform domain by using a filter that suits to the characteristics of the underlying images. To accomplish this, we represent each procedure resizing images in an arbitrary transform domain as matrix multiplications and we derive the matrix that scales the image resolutions from the matrix multiplications. The resolution scaling matrix is also designed to be able to select the up/down-sampling filter that suits the characteristics of the image. Experiments show that the proposed method produces the reliable performances when it is applied to various transforms and to images that are mixed with predicted and non-predicted blocks which are generated during video coding.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2879-2899
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• 2021

The tone reservation (TR) scheme is an attractive method to reduce peak-to-average power ratio (PAPR) in the filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) systems. However, the high PAPR of FBMC signal will severely degrades system performance. To address this issue, a cyclic shift based TR (CS-TR) scheme with embedding side information (SI) is proposed to reduce the PAPR of FBMC signals. At the transmitter, four candidate signals are first generated based on cyclic shift of the output of inverse discrete Fourier transform (IDFT), and the SI of the selected signal with minimum peak power among the four candidate signals is embedded in sparse symbols with quadrature phase-shift keying constellation. Then, the TR weighted by optimal scaling factor is employed to further reduce PAPR of the selected signal. At the receiver, a reliable SI detector is presented by determining the phase rotation of SI embedding symbols, and the transmitted data blocks can be correctly demodulated according to the detected SI. Simulation results show that the proposed scheme significantly outperforms the existing TR schemes in both PAPR reduction and bit error rate (BER) performances. In addition, the proposed scheme with detected SI can achieve the same BER performance compared to the one with perfect SI.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.1
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• pp.63-73
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• 1999

This paper presents new pipeline architecure for low power and high speed digital FIR filters. The proposed architecture based on retiming technique achieves enhancement on speed by sharing the input delay stage with multiplication of input data and on power combined with supply voltage scaling down technique. An 8-tap digital FIR filter for PRML disk-drive read channels adopting the proposed pipeline architecture has been designed and fabricated with 0.8${\mu}m$ CMOS double metal process technology. Measured results show that the designed FIR filter operates to 192 MHz in average and dissipates 1.22 mW/MHz at 3.3.V power supply. As a result, the proposed architecture improves speed by about 16% and reduces power dissipation by about 23% when operating at the same throughput.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.13-21
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• 2010

The Optimal results of Kalman Filtering on the Inverted Pendulum System requires an effective factor such as the noise covariance matrix Q, the measurement noise covariance matrix R and the initial error covariance matrix $P_0$. We present a special case where the optimality of the filter is not destroyed and not sensitive to scaling of these covariance matrix because these factors are unknown or are known only approximately in the practical situation. Moreover, the error covariance matrices issued by this method predict errors in the state estimate consistent with the scaled covariance matrices and not the issued state estimates. Various results using the scalar gain $\delta$ are derived to described the relations among the three covariance matrices, Kalman Gain and the error covariance matrices. This paper is described as follows: Section III a brief overview of the Inverted Pendulum system. Section IV deals with the mathematical dynamic model of the system used for the computer simulation. Section V presents a various simulation results using the scalar gain.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.522-527
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• 2022

Object tracking is a field of signal processing that sequentially tracks the location of an object based on the previous-time location estimations and the present-time observation data. In this paper, we propose an adaptive scaling neural network that can track and adjust the scale of the input data with three recursive neural network (RNN) submodules. To evaluate object tracking performance, we compare the proposed system with the Kalman filter and the maximum likelihood object tracking scheme under an one-dimensional object movement model in which the object moves with piecewise constant acceleration. We show that the proposed scheme is generally better, in terms of root mean square error (RMSE) performance, than maximum likelihood scheme and Kalman filter and that the performance gaps grow with increased observation noise.