• Journal of Broadcast Engineering
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• v.22 no.5
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• pp.643-651
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• 2017

Steganography is one of information hiding technologies and discriminated from cryptography in that it focuses on avoiding the existence the hidden information from being detected by third parties, rather than protecting it from being decoded. In this paper, as an image steganography method which uses images as media, we propose a new block matching method that embeds information into the discrete wavelet transform (DWT) domain. The proposed method, based on a statistical analysis, reduces loss of embedding capacity due to inequable use of candidate blocks. It works in such a way that computes the variance of each candidate block, preserves candidate blocks with high frequency components while reducing candidate blocks with low frequency components by compressing them exploiting the k-means clustering algorithm. Compared with the previous block matching method, the proposed method can reconstruct secret images with similar PSNRs while embedding higher-capacity information.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.968-974
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• 2010

We assessed the feasibility of discrete wavelet transform (DWT) applied for the spectral processing to enhance the estimation performance quality of soil organic matters using visible-near infrared spectra and mapped their distribution via block Kriging model. Continuum-removal and $1^{st}$ derivative transform as well as Haar and Daubechies DWT were used to enhance spectral variation in terms of soil organic matter contents and those spectra were put into the PLSR (Partial Least Squares Regression) model. Estimation results using raw reflectance and transformed spectra showed similar quality with $R^2$ > 0.6 and RPD> 1.5. These values mean the approximation prediction on soil organic matter contents. The poor performance of estimation using DWT spectra might be caused by coarser approximation of DWT which not enough to express spectral variation based on soil organic matter contents. The distribution maps of soil organic matter were drawn via a spatial information model, Kriging. Organic contents of soil samples made Gaussian distribution centered at around 20 g $kg^{-1}$ and the values in the map were distributed with similar patterns. The estimated organic matter contents had similar distribution to the measured values even though some parts of estimated value map showed slightly higher. If the estimation quality is improved more, estimation model and mapping using spectroscopy may be applied in global soil mapping, soil classification, and remote sensing data analysis as a rapid and cost-effective method.

• Journal of KIISE:Software and Applications
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• v.28 no.7
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• pp.501-510
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• 2001

Generally, it is essential to estimate exact disparity for the 3D modeling from stereo images. Because existing methods calculate disparities from a whole image, they require too much cimputational time and bring about the mismatching problem. In this article, using the characteristic that the disparity vectors in stereo images are distributed not equally in a whole image but only exist about the background and obhect, we do a wavelet transformation on stereo images and estimate coarse disparity fields from the reduced lowpass field using area-based method at first-step. From these coarse disparity vectors, we generate disparity histogram and then separate object from background area using it. Afterwards, we restore only object area to the original image and estimate dense and accurate disparity by our two-step pixel-based method which does not use pixel brightness but use second gradient. We also extract feature points from the separated object area and estimate depth information by applying disparity vectors and camera parameters. Finally, we generate 3D model using both feature points and their z coordinates. By using our proposed, we can considerably reduce the computation time and estimate the precise disparity through the additional pixel-based method using LOG filter. Furthermore, our proposed foreground/background method can solve the mismatching problem of existing Delaunay triangulation and generate accurate 3D model.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.341-348
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• 2011

ECG(Electrocardiogram), a field of Bio-signal, is generally experimented with classification algorithms most of which are SVM(Support Vector Machine), MLP(Multilayer Perceptron). But this study modified the Random Forest Algorithm along the basis of signal characteristics and comparatively analyzed the accuracies of modified algorithm with those of SVM and MLP to prove the ability of modified algorithm. The R-R interval extracted from ECG is used in this study and the results of established researches which experimented co-equal data are also comparatively analyzed. As a result, modified RF Classifier showed better consequences than SVM classifier, MLP classifier and other researches' results in accuracy category. The Band-pass filter is used to extract R-R interval in pre-processing stage. However, the Wavelet transform, median filter, and finite impulse response filter in addition to Band-pass filter are often used in experiment of ECG. After this study, selection of the filters efficiently deleting the baseline wandering in pre-processing stage and study of the methods correctly extracting the R-R interval are needed.

• Journal of the Korea Concrete Institute
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• v.23 no.2
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• pp.219-224
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• 2011

In this study, a piezoelectric smart sensor that can be embedded inside of concrete structures is developed to investigate the early stage of concrete curing. A waterproof coating is used to protect the piezoelectric sensor from moistures of concrete mixture. Also, a mortar case is utilized to encapsulate the sensor to protect it from impact loads. To estimate the strength of concrete, a self-sense guided-wave actuated sensing technique is applied. In the guided wave, its velocity is varied according to the mechanical properties of concrete such as modulus of elasticity. Because modulus of elasticity directly affects the strength of concrete, the guidedwave's velocity also affects the concrete strength development. To verify the feasibility of using the proposed approach, the smart sensor was embedded into a 100MPa concrete cylinder and the self-sense guided wave is continuously measured throughout the curing process. The measurements showed that the propagation time (TOF) of the measured guided waves gradually decreased as the curing age increased. Especially, at the early age of the curing process, the variation of the TOF was very significant. Furthermore, the results showed that there is a linear relationship between the TOF of the self-sense guided waves and the strength of concrete existed. It is safe to conclude that the proposed approach can be used very effectively in monitoring of the strength development of high strength concrete structures.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.2
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• pp.105-114
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• 2007

Two-dimensional imaging of $V_s$ profile becomes more important in Korea because of the large horizontal variation of soil stiffness. To obtain a shear-wave velocity profile in geotechnical practice, various seismic nondestructive investigation methods are being frequently used. In this study, harmonic wavelet analysis of wave (HWAW) method is applied to the determination of $V_s$ profile to overcome some of weaknesses in the existing surface wave methods. HWAW method which is based on time-frequency analysis using harmonic wavelet transform has been developed to determine phase and group velocities of waves. Field testing of this method is relatively simple and fast because one experimental setup which consists of one pair of receivers is needed to determine $V_s$ profile of site. The proposed method uses the signal portion of the maximum local signal/noise ratio to evaluate the phase velocity to minimize the effects of noise, and uses single array inversion which considers receiver locations. Field tests were performed in 2 sites in order to evaluate accuracy of test method and estimate the applicability of 2-D imaging by HWAW method. Through field applications and comparison with other test results, the good accuracy and applicability of the proposed method were verified.

• Journal of KIISE:Software and Applications
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• v.34 no.9
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• pp.869-879
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• 2007

This paper proposes a neural network based approach for automatic human emotion recognition in textile images. To investigate the correlation between the emotion and the pattern, the survey is conducted on 20 peoples, which shows that a emotion is deeply affected by a pattern. Accordingly, a neural network based classifier is used for recognizing the pattern included in textiles. In our system, two schemes are used for describing the pattern; raw-pixel data extraction scheme using auto-regressive method (RDES) and wavelet transformed data extraction scheme (WTDES). To assess the validity of the proposed method, it was applied to recognize the human emotions in 100 textiles, and the results shows that using WTDES guarantees better performance than using RDES. The former produced the accuracy of 71%, while the latter produced the accuracy of 90%. Although there are some differences according to the data extraction scheme, the proposed method shows the accuracy of 80% on average. This result confirmed that our system has the potential to be applied for various application such as textile industry and e-business.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9C
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• pp.939-948
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• 2005

In EBCOT, the context extraction process takes excessive calculation time and this paper proposed a method to reduce this calculation time. That is, if a coefficient is less than a pre-defined threshold value the coefficient and its descendents skip the context extraction process. There is a trade-off relationship between the calculation time and the image quality or the amount of output data such that as this threshold value increases, the calculation time and the amount of output data decreases, but the image degradation increases. Therefore, by deciding this threshold value according to the network environments or conditions, it is possible to establish a network-adaptive context extraction method. The experimental results showed that the range of the threshold values for acceptable image quality(better than 30dB) is from 0 to 4. The experimental results showed that in this range the Resulting reduction rate in calculation time was from $3\%\;to\;64\%$ in average, the reduction rate in output data was from $32\%$ to $73\%$ in average, which means that large reduction in calculation time and output data can be obtained with a cost of an acceptable image quality degradation. Therefore, the proposed method is expected to be used efficiently in the application area such as the real-time image/video data communication in wireless environments, etc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.618-627
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• 2002

In processing images using 2 dimensional Discrete Wavelet Transform(2D-DWT), the method to process the pixels around the image boundary may affect the quality of image and the cost to implement in hardware and software. This paper proposed an effective method to treat the boundary pixels, which is apt to implement in hardware and software without losing the quality of the image costly. This method processes the 2-D image as 1-D array so that 2-D DWT is performed by considering the image with the serial-sequential data structure (Serial-Sequential Processing). To show the performance and easiness in implementation of the proposed method, an image compression codec which compresses image and reconstructs it has been implemented and experimented. It included log-scale fried quantizer, but the entropy coder was not implemented. From the experimental results, the proposed method showed the SNR of almost the same SNR(Signal to Noise Ratio) to the Periodic Expansion(PE) method when the compression ratio(excluding entropy coding) of 2:1, 15.3% higher than Symmetric Expansion(SE) method, and 9.3% higher than 0-pixel Padding Expansion(ZPE) method. Also PE method needed 12.99% more memory space than the proposed method. By considering only the compression process, SE and ZPE methods needed additional operations than the proposed one. In hardware implementation, the proposed method in this paper had 5.92% of overall circuit as the control circuit, while SE, PE, and ZPE method has 22%, 21,2%, and 11.9% as the control circuit, respectively. Consequently, the proposed method can be thought more effective in implementing software and hardware without losing any image quality in the usual image processing applications.

• Composites Research
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• v.24 no.1
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• pp.24-30
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• 2011

Low-velocity impact can cause various damages which are mostly hidden inside the laminates or occur in the opposite side. Thus, these damages cannot be easily detected by visual inspection or conventional NDT systems. And if they occurred between the scheduled NDT periods, the possibilities of extensive damages or structural failure can be higher. Due to these reasons, the built-in NDT systems such as real-time impact monitoring system are required in the near future. In this paper, we studied the impact monitoring system consist of impact location detection and damage assessment techniques for composite flat and stiffened panel. In order to acquire the impact-induced acoustic signals, four multiplexed FBG sensors and high-speed FBG interrogator were used. And for development of the impact and damage occurrence detections, the neural networks and wavelet transforms were adopted. Finally, these algorithms were embodied using MATLAB and LabVIEW software for the user-friendly interface.