• The KIPS Transactions:PartC
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• v.8C no.6
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• pp.703-710
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• 2001

In this paper, we consider a multiple watermarking for image copyright protection. Multiple watermarking can be defined that two or more watermarks are inserted into the same content. Multiple watermarking using spread spectrum technique is able to extract the correct watermarks from the watermarked content when the orthogonality among keys should be guaranteed only. To keep the orthogonal property between keys, we perform the process of Gram-Schmidt on the random sequences. The orthogonalized sequences are used as keys to embed the watermarks. The proposed method can not only extract correctly the embedded watermarks but also show the robustness against various attacks such as Gaussian noise addition, histogram equalization, gamma correlation, sharpening and brightness/contrast adjustment.

• Journal of KIISE:Databases
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• v.35 no.1
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• pp.54-66
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• 2008

A spatio-temporal join is an expensive operation that is commonly used in spatio-temporal database systems. In order to generate an efficient query plan for the queries involving spatio-temporal join operations, it is crucial to estimate accurate selectivity for the join operations. Given two dataset $S_1,\;S_2$ of discrete data and a timestamp $t_q$, a spatio-temporal join retrieves all pairs of objects that are intersected each other at $t_q$. The selectivity of the join operation equals the number of retrieved pairs divided by the cardinality of the Cartesian product $S_1{\times}S_2$. In this paper, we propose aspatio-temporal histogram to estimate selectivity of spatio-temporal join by extending existing geometric histogram. By using a wide spectrum of both uniform dataset and skewed dataset, it is shown that our proposed method, called Spatio-Temporal Histogram, can accurately estimate the selectivity of spatio-temporal join. Our contributions can be summarized as follows: First, the selectivity estimation of spatio-temporal join for discrete data has been first attempted. Second, we propose an efficient maintenance method that reconstructs histograms using compression of spatial statistical information during the lifespan of discrete data.

• Current Optics and Photonics
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• v.5 no.3
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• pp.278-288
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• 2021

We propose a characterization method for the scattering property of microspheres using spectroscopic optical coherence tomography (OCT). To prove the effectiveness of the proposed method, we prepare solutions of different concentrations using microspheres ranging from 28 to 2300 nm in diameter. Time-frequency analysis is performed on the measured interference spectrum of each solution, and the resulting spectroscopic information is converted into histograms for centroid wavelengths. The histograms present a very sensitive response to changes in the concentration and size of microspheres. We classify them into three categories according to their characteristics. When the histogram of each category is replaced with the corresponding calculated value of the scattering coefficient, each category is mapped to a different scattering-coefficient region. It is expected that the proposed method could be used to investigate the optical characteristics of a biological sample from OCT images, which would be helpful for optical diagnostic and therapeutic applications.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.57-65
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• 2010

In this paper, we present a universal steganalysis scheme. The proposed method extract features of two types. First feature set is extracted from histogram characteristic of the wavelet subbands. Second feature set is determined by statistical moments of wavelet characteristic functions. 3-level wavelet decomposition is performed for stego image and cover image using the Haar wavelet basis. We extract one features from 9 high frequency subbands of 12 subbands. The number of second features is 39. We use total 48 features for steganalysis. Multi layer perceptron(MLP) is applied as classifier to distinguish between cover images and stego images. To evaluate the proposed steganalysis method, we use the CorelDraw image database. We test the performance of our proposed steganalysis method over LSB method, spread spectrum data hiding method, blind spread spectrum data hiding method and F5 data hiding method. The proposed method outperforms the previous methods in sensitivity, specificity, error rate and area under ROC curve, etc.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.55-63
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• 2010

In this paper, a new video watermarking algorithm using 3D wavelet transform and position encoding of spread spectrum correlation is proposed as a method for ensuring enough payload in order to protect copyright for video contents. This algorithm provides better robustness than other watermarking methods in bit error and rotation because it uses the position encoding and $4{\times}4$ sample space instead of $1{\times}1$ pixel to express a digit. The evaluation result over 6 video clips shows that the PSNR is over 31dB at strength 11 when histogram is narrow and it satisfies the transparency. Also, it shows the robustness of the proposed watermark algorithm that the BER is 0% to three codecs.

• Journal of Korea Multimedia Society
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• v.21 no.4
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• pp.450-463
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• 2018

Sound based machine fault diagnosis is the process consisting of detecting automatically the damages that affect the machines by analyzing the sounds they produce during their operating time. The collected sounds being inevitably corrupted by random disturbance, the most important part of the diagnosis consists of discovering the hidden elements inside the data that can reveal the faulty patterns. This paper presents a novel feature extraction methodology that combines various digital signal processing and pattern recognition methods for the analysis of the sounds produced by the drills. Using the Fourier analysis, the magnitude spectrum of the sounds are extracted, converted into two-dimensional vectors and uniformly normalized in such a way that they can be represented as 8-bit grayscale images. Histogram equalization is then performed over the obtained images in order to adjust their very poor contrast. The obtained contrast enhanced images will be used as the features of our diagnosis system. Finally, principal component analysis is performed over the image features for reducing their dimensions and a nonlinear classifier is adopted to produce the final response. Unlike the conventional features, the results demonstrate that the proposed feature extraction method manages to capture the hidden health patterns of the sound.

• Ocean and Polar Research
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• v.28 no.4
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• pp.459-465
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• 2006

Ambient noise as a background noise in the ocean has been well known for its the various and irregular signal characteristics. Generally, these signals we treated as noise and they are analyzed through stochastical level if they don't include definite sinusoidal signals. This study is to see how ocean ambient noise can be analyzed by the chaotic analysis technique. The chaotic analysis is carried out with underwater ambient noise obtained in areas near the Korean Peninsula. The calculated physical parameters of time series signal are as follows: histogram, self-correlation coefficient, delay time, frequency spectrum, sonogram, return map, embedding dimension, correlation dimension, Lyapunov exponent, etc. We investigate the chaotic pattern of noises from these parameters. From the embedding dimensions of underwater noises, the assesment of underwater noise by chaotic analysis shows similar results if they don't include a definite sinusoidal signal. However, the values of Lyapunov exponent (divergence exponent) are smaller than that of random noise signal. As a result we confirm the possibility of classification of underwater noise using Lyapunov analysis.

• Journal of KSNVE
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• v.3 no.4
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• pp.341-352
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• 1993

Although a frequency analysis by FFT algorithm has been widely used in the vibration community, this approach has somewhat limited features when an analysist want to see the details of frequency trends because FFT shows only energy contents along frequencies. So the concept of instantaneous frequency that represents the dominant frequency component at each time needs to be introduced. In this paper, to get the instantaneous frequency, two methods are used. Methods using Hilbert transform and evolutionary spectrum are those. One of the problems of estimating instantaneous frequency using Hilbert transform is that it is normally very sensitive to signal to noise ratio(SNR) because of the differentiation. Moving window is applied on the estimation of instantaneous frequency, and instantaneous frequency histogram are used to handle this problem and proved to be very effective. Computer simulations for various signals have been done to understand the characteristics of instantaneous frequency. The usefulness of signal analysis using instantaneous frequency was tested by three simple experiments, which were engine experiment, beam experiment, and car door experiment. The instantaneous frequency analysis is found to be a useful technique to analyze the signals that have time varying frequencies.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.5
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• pp.338-347
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• 2005

A computer-based low back muscle evaluation system was designed to simultaneously acquire, process, display, quantify, and correlate electromyographic(EMG) activity with muscle force, and range of motion(ROM) in the lumbar muscle of human. This integrated multi-channel system was designed around notebook PC. Each channel consisted of a time and frequency domain block, and T-F(time-frequency) domain block. The captured data in each channel was used to display and Quantify : raw EMG, histogram, zero crossing, turn, RMS(root mean square), variance, mean, power spectrum, median frequency, mean frequency, wavelet transform, Wigner-Ville distribution, Choi-Williams distribution, and Cohen-Posch distribution. To evaluate the performance of the designed system, the static and dynamic contraction experiments from lumbar(waist) level of human were done. The experiment performed in five subjects, and various parameters were tested and compared. This system could equally well be modified to allow acquisition, processing, and analysis of EMG signals in other studies and applications.

• Journal of IKEEE
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• v.13 no.4
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• pp.96-102
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• 2009

We investigate the characteristics of RJ (random jitter) in an analog fiber-optic link employing a MZM (Mach-Zehnder modulator) and an EDFA (Erbium-doped fiber amplifier). RJ has been measured using two methods, one of which derived from the noise spectrum of a RF spectrum analyzer and the other from the histogram data of a sampling oscilloscope. If the optical power and/or the RF power input to the MZM increase, RJ decreases due to the output signal power increase. For the optical link without EDFA, the minimum RJ is about 1 ps at an RF power of 10 dBm and an optical power of 8 dBm measured using the noise spectrum method. For the optical link with an EDFA, RJ decreases toward a jitter floor as the EDFA gain increases. If the gain increases further, it has been observed that RJ increases from the minimum. If the EDFA gain is fixed, RJ is smaller for the case of larger optical input power. As the EDFA gain increases, RJ reduction rate becomes greater for the case of lower optical input power.