• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.868-871
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• 2002

Nowadays, zerotrees based digital watermarking techniques are considered to be an efficient watermarking technique used for multimedia data in a compressed form. This paper presents a technique for watermarking an image, by employing zerotrees derived from the wavelet packet coefficients of the transformed image to carry the watermark signal. By setting a proper threshold in zerotrees determining process, the watermark signal can be recovered without the need of original image. With our proposed technique, more amount of watermark signal can be embedded within the image, compared to ordinary wavelet transform based techniques. The experimental results show the improved performance in both qualities of the resultant watermarked image and robustness of the embedded watermark signal against common signal processing such as brightness/contrast enhancement, high-pass filtering, Gaussian noise adding and JPEG compression scheme

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.5039-5055
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• 2018

The quality of natural outdoor images captured by visible camera sensors is usually degraded by the haze present in the atmosphere. In this paper, a fast image dehazing method based on visible image and near-infrared fusion is proposed. In the proposed method, a visible and a near-infrared (NIR) image of the same scene is fused based on the dual-tree complex wavelet transform (DT-CWT) to generate a dehazed color image. The color of the fusion image is regulated through haze concentration estimated by dark channel prior (DCP). The experiment results demonstrate that the proposed method outperforms the conventional dehazing methods and effectively solves the color distortion problem in the dehazing process.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.965-968
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• 2016

This paper describes a new speckle noise reduction methode on the sonar image using TVG Filtering and PDF wavelet transform. The speckle noise makes the degrading image to discriminate the various object on the ocean bed. The TVG filter removes the speckle noise by gain with observing the results timely and inductively. The experimental result is that speckle noise is reduced to 90 %. Thus the proposed technique leads the mage recognition to be enhanced in the submarine environment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.10
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• pp.1508-1515
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• 2017

This paper proposes the defect detection method for automatic inspection machines in printed circuit boards (PCBs) manufacturing system. The defects of PCB such as open, short, pin hole and scratch can be detected by comparing the standard image and the target image. The standard image is obtained from CAD file such as ODB++ format, and the target image is obtained by arranging, filtering and binarization of captured PCB image. Since the PCB size is too large and image resolution is too high, the image processing requires a lot of memory and computational time. The wavelet transform is applied to compress the standard and target images, which results in reducing the memory and computational time. To increase the inspection accuracy, we utilize the he HH-domain as well as LL-domain of the transformed images. Experimental results are finally presented to show the performance improvement of the proposed method.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.23-26
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• 2003

디지털로 신호를 표현하는 방법은 기존 아날로그 표현하는 방법에 비해 많은 장점을 가지고 있다. 하지만 디지털로 된 데이터는 언제 어디서든 대단위 복제가 가능하다. 즉, 저작권 침해, 불법 복제 및 배포, 손쉽게 위조할 수 있다는 점이 그것이다. 디지털 영상 정보의 보호를 위해 디지털 영상의 불법적인 내용 조작을 막고, 영상의 소유권을 보장할 수 있는 방법으로 디지털 워터마크(Digital Watermark)가 있다. 디지털 워터마크는 공개키 알고리즘이나 방화벽 등으로 해독된 영상에 대하여 부가적인 보호를 제공한다. 본 논문에서는 디지털 영상 데이터의 정보 보호를 위해 주파수 영역에서의 웨이브릿 변환(Wavelet Transform)을 이용한 이미지 적용 디지털 워터마킹(Image-Adaptive Digital Watermarking) 방법을 제안한다. 이미지 적용 웨이브릿(Image-Adaptive Wavelet)은 영상을 주파수적으로 분해하면서 각 대역들의 공간 영역에서의 정보를 함께 지니고 JND(Just noticeable difference)을 포함한다. 이미지 적응 웨이브릿의 이러한 특성을 이용하여 다해상도 분해하고, 손실 압축(Loss Compression)이나 필터링(Filtering), 잡음(Noise)등에 크게 영향받는 저주파 성분과 인간의 시각적으로 큰 의미를 갖는 고주파 성분의 특성을 이용하여 워터마크를 삽입한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.883-900
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• 2017

In this paper block based blind secure gray image watermarking scheme based on discrete wavelet transform and singular value decomposition is proposed. In devising the proposed scheme, security is given high importance along with other two requirements: robustness and imperceptibility. The use of discrete wavelet transform not only improves robustness but the selection of bands with high tolerance towards noise caused an improvement in terms of imperceptibility. The robustness further improved due to the involvement of singular vectors along with singular values in watermark embedding and extraction process. Finally, to achieve security, the selected DWT band is decomposed into smaller blocks and random blocks are chosen for modification. Furthermore, the elements of left and right singular vectors of selected blocks are chosen based on their dependence upon each other for watermark embedding. Various experiments using different images as host and watermark were conducted to examine and validate the proposed technique. Additionally, the proposed technique is tested against various attacks like compression, affine transformation, cropping, translation, X shearing, scaling, Y shearing, filtering, blurring, different kinds of noises, histogram equalization, rotation, etc. Lastly, the proposed technique is compared with state-of-the-art watermarking techniques and their comparison shows significant improvement of proposed scheme over existing techniques.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.42-47
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• 2001

Analyzing the ECG signal, we can find heart disease, for example, arrhythmia and myocardial infarction, etc. Particularly, detecting arrhythmia is more important, because serious arrhythmia can take away the life from patients within ten minutes. In this paper, we would like to introduce the signal processing for ECG analysis and the device made for wireless communication of ECG data. In the signal processing, the wavelet transform decomposes the ECG signal into high and low frequency components using wavelet function. Recomposing the high frequency bands including QRS complex, we can detect QRS complex and eliminate the noise from the original ECG signal. To recognize the ECG signal pattern, we adopted the polynomial approximation partially and statistical method. The ECG signal is divided into small parts based on QRS complex, and then, each part is approximated to the polynomials. Comparing the approximated ECG pattern with the database, we can detect and classify the heart disease. The ECG detection device consists of amplifier, filters, A/D converter and RF module. After amplification and filtering, the ECG signal is fed through the A/D converter to be digitalized. The digital ECG data is transmitted to the personal computer through the RF transceiver module and serial port.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1299-1311
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• 2017

Sounds based machine fault diagnosis recovers all the studies that aim to detect automatically faults or damages on machines using the sounds emitted by these machines. Conventional methods that use mathematical models have been found inaccurate because of the complexity of the industry machinery systems and the obvious existence of nonlinear factors such as noises. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We present here an automatic fault diagnosis system of hand drills using discrete wavelet transform (DWT) and pattern recognition techniques such as principal component analysis (PCA) and artificial neural networks (ANN). The diagnosis system consists of three steps. Because of the presence of many noisy patterns in our signals, we first conduct a filtering analysis based on DWT. Second, the wavelet coefficients of the filtered signals are extracted as our features for the pattern recognition part. Third, PCA is performed over the wavelet coefficients in order to reduce the dimensionality of the feature vectors. Finally, the very first principal components are used as the inputs of an ANN based classifier to detect the wear on the drills. The results show that the proposed DWT-PCA-ANN method can be used for the sounds based automated diagnosis system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.89-95
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• 2017

UFMC is known as a candidate for the 5G wireless communication system because it is robust against ICI and better performs in asynchronous situation than OFDM. In the UFMC system, the filtering is performed for each subband so the performance of the filter is very important. The Dolph-Chebyshev filter has been used in conventional UFMC system because of its small out-of-band radiation. However it has distortion in the sub-band and skirt characteristics is not good enough. Therefore, it is necessary to study a new type of UFMC filter which reduces the distortion in the subband and has sharp skirt characteristics. In this paper we analyze the effect of filter frequency response in UFMC system and suggest the wavelet based type of filter that substitutes the Dolph-ChebyShev filter used in the conventional UFMC system. The simulation results show that wavelet filter has better BER performance in multipath fading channels than conventional filters.

• The Journal of Korean Association of Computer Education
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• v.5 no.4
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• pp.43-52
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• 2002

A theory of binary wavelets which are performed over binary field has been recently proposed. Binary wavelet transform (BWT) of binary images can be used as an alternative to the real-valued wavelet transform of binary images in image processing applications such as compression, edge detection, and recognition. The BWT, however, requires large amount of computations for binary wavelet reconstruction since its operation is accomplished by matrix multiplication. In this paper, an efficient binary wavelet reconstruction method which utilizes filtering operation instead of matrix multiplication is presented. Experimental results show that the proposed algorithm can significantly reduce the computational complexity of the BWT. For the reconstruction of an $N{\times}N$ image, the proposed technique requires only $2MN^2$ multiplications and $2N(M-1)^2$ additions when the filter length M, while the BWT needs $2N^3$ multiplications and $2N(N-1)^2$ additions.