• The Journal of the Acoustical Society of Korea
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• v.18 no.6
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• pp.57-64
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• 1999

In this paper, we investigated the robust endpoint detection algorithm in noisy environment. A new feature parameter based on a discrete wavelet transform is proposed for word boundary detection of isolated utterances. The sum of standard deviation of wavelet coefficients in the third coarse and weighted first detailed scale is defined as a new feature parameter for endpoint detection. We then developed a new and robust endpoint detection algorithm using the feature found in the wavelet domain. For the performance evaluation, we evaluated the detection accuracy and the average recognition error rate due to endpoint detection in an HMM-based recognition system across several signal-to-noise ratios and noise conditions.

• Journal of Ocean Engineering and Technology
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• v.20 no.2 s.69
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• pp.8-15
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• 2006

Guided-waves-based mortar-filled steel pipe inspection is carried out through using EMAT (Electro magnetic acoustic transducer) and wavelet transform. Possibly existing anomalies such as separation (or void) and inclusion are made in the fabricated mortar-fled steel pipes: these anomalies are infected. Since guided waves have the long range inspection capability, EMAT has its own advantages over the conventional PZT (Piezoelectric zirconate titanate), and wavelet transform gives the multi-resolution on time-frequency domain results, the suggested technique gives an alternative way for inspecting mortar-filled steel pipes, which are popularly used for supporting marine structures such as piers, wharfs, moles, and dolphins. Through this study, it is show that the suggested technique is promising for detecting the amounts of separations and inclusions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1469-1474
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• 2004

A wavelet-based image watermarking scheme is proposed, based on the insertion of pseudo-random codes in the frequency domain. The original image is required for the watermark detection. The 'strength' of the signature to be embedded depends on the image to be marked, thus fitting signal capacity. The experimental results prove that the method is more tamper resistant and less perceptible for any type of images than other well-known private methods in the frequency domains.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.221-222
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• 2007

This paper presents wavelet-based moving object segmentation using double change detection and background registration. Three successive frame differences for detection change were used in the wavelet domain. The background was constructed with the wavelet coefficients in the lowest frequency subband which are the approximated version of an image. Combining double change detection and background registration, we can obtain an efficient moving object segmentation algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.3B
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• pp.557-564
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• 2000

This paper presents a watermarking algorithm for embedding visually recognizable pattern (Mark, Logo, Symbol, stamping or signature) into the image. first, the color image(RGB model)is transformed in YCbCr model and then the Y component is transformed into 3-level wavelet transform. Next, the values are assembled with pattern watermark. PN(pseudo noise) code at spread spectrum communication method and mutilevel watermark weights. This values are inserted into discrete wavelet domain. In our scheme, new calculating method is designed to calculate wavelet transform with integer value in considering the quantization error. and we used the color conversion with fixed-point arithmetic to be easy to make the hardware hereafter. Also, we made the new solution using mutilevel threshold to robust to common signal distortions and malicious attack, and to enhance quality of image in considering the human visual system. the experimental results showed that the proposed watermarking algorithm was superior to other similar water marking algorithm. We showed what it was robust to common signal processing and geometric transform such as brightness. contrast, filtering. scaling. JPEG lossy compression and geometric deformation.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.324-329
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• 2003

Spectral analysis is an important signal processing tool for time series data. The transformation of a time series into the frequency domain is the basis for a significant number of processing algorithms and interpretive methods. Recently developed transforms based on the new mathematical field of wavelet analysis bypass the resolution limitation and offer superior spectral decomposition. The discrete wavelet transform of Sonar data provides spectral localization of noises, hence noises can be filtered out successfully.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1296-1302
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• 1999

In this paper, we propose an algorithms for the mounted PCB classification system using wavelet transform and ART2 neural network. The feature informations of a mounted PCB can be extracted from the coefficient matrix of wavelet transform adapted subband concept. As the preprocessing process, only the PCB area in the input image is extracted by histogram method and the feature vectors are composed of using wavelet transform method. These feature vectors are used as the input vector of ART2 neural network. In the experiment using 55 mounted PCB images, the proposed algorithm shows 100% classification rate at the vigilance parameter $\rho$=0.99. The proposed algorithm has some advantages of the feature extraction in the compressed domain and the simplification of processing steps.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.39-47
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• 2023

This study compares various transformation techniques for multifocus image fusion. Multi-focus image fusion is a procedure of merging multiple images captured at unalike focus distances to produce a single composite image with improved sharpness and clarity. In this research, the purpose is to compare different popular frequency domain approaches for multi-focus image fusion, such as Discrete Wavelet Transforms (DWT), Stationary Wavelet Transforms (SWT), DCT-based Laplacian Pyramid (DCT-LP), Discrete Cosine Harmonic Wavelet Transform (DC-HWT), and Dual-Tree Complex Wavelet Transform (DT-CWT). The objective is to increase the understanding of these transformation techniques and how they can be utilized in conjunction with one another. The analysis will evaluate the 10 most crucial parameters and highlight the unique features of each method. The results will help determine which transformation technique is the best for multi-focus image fusion applications. Based on the visual and statistical analysis, it is suggested that the DCT-LP is the most appropriate technique, but the results also provide valuable insights into choosing the right approach.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.49-52
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• 1999

In this paper, we describe the structure of the DWMT (discrete wavelet multitone) transceiver for VDSL system. The DWMT transceiver is basically consisted of the transmultiplexer using cosine modulation filter bank (CMFB), time domain equalizer (TEQ) and frequency domain equalizer (FEQ) minimizing the effects of the transmission channel. For FEQ, we expanded the general LMS algorithm to 2-dimensions: time and subchannel axes and examined the 2-dimensional LMS methods with the various array size.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.706-715
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• 2004

In this paper, to decide the watermark embedding positions and embed the watermark we use the subband tee structure which is presented in the wavelet domain and the edge information in the spatial domain. The significant frequency region is estimated by the subband searching from the higher frequency subband to the lower frequency subband. LH1 subband which has the higher frequency in tree structure of the wavelet domain is divided into 4${\times}$4 submatrices, and the threshold which is used in the watermark embedding is obtained by the blockmatrix which is consists by the average of 4${\times}$4 submatrices. Also the watermark embedding position, Keymap is generated by the blockmatrix for the energy distribution in the frequency domain and the edge information in the spatial domain. The watermark is embedded into the wavelet coefficients using the Keymap and the random sequence generated by LFSR(Linear feedback shift register). Finally after the inverse wavelet transform the watermark embedded image is obtained. the proposed watermarking algorithm showed PSNR over 2㏈ and had the higher results from 2％ to 8％ in the comparison with the previous research for the attack such as the JPEG compression and the general image processing just like blurring, sharpening and gaussian noise.