• Journal of Industrial Technology
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• v.18
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• pp.295-302
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• 1998

Classification of fingerprints is one of the major subjects on which many researchers have been studying for efficient identification. But fingerprints should be preprocessed in various ways prior to being classified. Factors such as the accuracy and the processing time should be considered in classification of fingerprints. In this paper, we propose a method for classifying fingerprints into several frequent patterns. This method consists of two stages. A fingerprint image is first converted to a skeleton form to find out the center. Then it is identified as a member of one of preclassified pattern by the frequency domain feature. Experiments show that the proposed method is quite useful in classifying fingerprints into typical patterns.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.1
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• pp.70-76
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• 2003

Digital watermarking is a technique embedding hidden information into multimedia data imperceptibly such as images and sounds. Generally an original image is transformed and coded watermark data is embedded in frequency domain watermarking models. In this paper, We propose a new data embedding method using Fresnel transform. A watermark image is fresnel-transformed and the intensity of transformed pattern is embedded into original image. Our watermarking model has the flexibility In data embedding. It is possible to get many embedding patterns from a single watermark image by using various distance parameters with Fresnel transform. All kinds of image models such af shape, letter and photo ran be used as a watermark data. The watermarking experiments were conducted to show the validity of the proposed method, and the results show that our method has the robustness against lossy compression, filtering and geometric transformation.

• Journal of Biosystems Engineering
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• v.22 no.2
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• pp.217-226
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• 1997

This study was to develop a machine vision system to detect and to discriminate 5 kinds of apple surface defectbruise, decay. fleck, worm hole and scar. To detect the defects from an image of apple, thresholding technique was applied to images on various frames (R, G, B, H, S and I) of the color machine vision and an image of near infrared (NIR). To discriminate the detected region of defect, various features of the 5 kind defect regions were extracted from the 4 kinds of images selected above. The features were size of area, roundness, axes length ratio, mean and valiance of pixel values, standard deviation of real part of amplitude spectrum in frequency domain obtained by Fourier transform of pixel data and mean and standard deviation of power spectrum obtained by the same transform of pixel data. Routines to discriminate the defects from the features of image were developed and tested to prove their validity. The test resulted that I-frame and NIR images were the most desirable. Accuracies of the two images to discriminate the defects were noted as 76% and 77%, respectively.

• Journal of Advanced Navigation Technology
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• v.12 no.6
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• pp.659-665
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• 2008

We demonstrate experimentally that the method of Two-pupil optical scanning technique with PAL-spatial light modulator is capable of performing real-time joint transform correlation(JTC) optical system. Optical addressing is achieved by the use of a photosensitive layer of $\alpha$ - Si which controls the electric field across the liquid crystal The demonstrated technique is based on two-pupil optical heterodyne scanning. The method is independent of a spatial light modulator (SLM) in the Fourier plane. We develop the theory of the technique and evaluate a performance of the method by experimentally estimating the correlation between the target image and the reference image.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.8
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• pp.984-996
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• 2007

This paper presents techniques of 2-D scattering center extraction and 2-B ISAR(Inverse SAR) image formation for scattering wave which is scattered by a target. In general, 2-D IFFT is widely used to obtain 2-D scattering center and ISAR image of targets. But, this method has drawbacks, that is poor in a resolution aspect. To overcome these shortcomings with the FT(Fourier Transform)-based method, various techniques of high resolution signal processing were developed. In this paper, algorithms of 2-D scattering center extraction and ISAR image formation such as 2-D MEMP(Matrix Enhancement and Matrix Pencil), 2-D ESPRIT(Estimation of Signal Parameter via Rotational Invariance Techniques) are described. In order to show the performances of each algorithm, we use scattering wave of the ideal point scatterers and F-18 aircraft to estimate 2-D scattering center and abtain 2-D ISAR image.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.169-172
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• 2008

Land-use or land-cover classification of satellite images is one of the important tasks in remote sensing application and many researchers have been tried to enhance classification accuracy. Previous studies show that the classification technique based on wavelet transform is more effective than that of traditional techniques based on original pixel values, especially in complicated imagery. Various wavelets can be used in wavelet transform. Wavelets are used as basis functions in representing other functions, like sinusoidal function in Fourier analysis. In these days, some basis functions such as Haar, Daubechies, Coiflets and Symlets are mainly used in 2D image processing. Selecting adequate wavelet is very important because different results could be obtained according to the type of basis function in classification. However, it is not easy to choose the basis function which is effective to improve classification accuracy. In this study, we computed the wavelet coefficients of satellite image using 10 different basis functions, and then classified test image. After evaluating classification results, we tried to ascertain which basis function is the most effective for image classification. We also tried to see if the optimum basis function is decided by energy parameter before classifying the image using all basis function. The energy parameter of signal is the sum of the squares of wavelet coefficients. The energy parameter is calculated by sub-bands after the wavelet decomposition and the energy parameter of each sub-band can be a favorable feature of texture. The decision of optimum basis function using energy parameter in the wavelet based image classification is expected to be helpful for saving time and improving classification accuracy effectively.

• The Journal of the Korea Contents Association
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• v.13 no.10
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• pp.1-8
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• 2013

In this paper, we propose a new method to correct the perspective distortion that occurs in the process of acquiring the integral images. In the proposed method, the distortion correction is based on the spectral characteristics of integral images. As element images of an integral image are repeated nearly periodically, its Fourier spectrum is given as an impulse train. On the contrary, the impulse train do not appear in the spectra of distorted images. In the proposed method, therefore, the perspective distortion parameters are detected by using the characteristics of the spectrum obtained through the Fourier transform, and then the distorted images are corrected by using the parameters. Through experiments, we verify that the proposed method effectively works for the perspective distortion correction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.379-385
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• 2004

Medical images are being managed more by PACS in general medical institutions. It is important to protect patients from being invaded their privacy related to the images. It is also necessary to confirm the ownership, the right of property of the medical images and notice whether the data are modified. In this paper, we propose a robust watermarking against RST attacks in medical images on the PACS. The proposed scheme modifies and improves Log-Polar Mapping and Fourier Mellin Transform in order to realize and recover serious image degradation and watermark data loss caused by the conversion between cartesian coordinate and log-polar coordinate. We used the radius and theta Look Up Table to solve the realization of the Fourier Mellin Transform, and inserted a watermark into 2D-DFT magnitudes using Spread Spectrum. Experimental results shows that this method are robust to rotation attack.

• Current Optics and Photonics
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• v.5 no.6
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• pp.672-679
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• 2021

We propose a high-speed layer-based algorithm for synthesizing computer-generated holograms (CGHs), featuring sparsity-based image segmentation and computational parallelism. The sparsity-based image segmentation of layer-based three-dimensional scenes leads to considerable improvement in the efficiency of CGH computation. The efficiency enhancement of the proposed algorithm is ascribed to the field localization of the fast Fourier transform (FFT), and the consequent reduction of FFT computational complexity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.7
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• pp.1575-1581
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• 2003

As a society has progressed rapidly toward a highly advanced digital information age, a multimedia communication service for acquisition, transmission and storage of image data as well as voice has being commercialized externally and internally. However, in the process of digitalization or transmission of data, noise is generated by several causes, and researches for eliminating those noises have been continued until now. There were the existing FFT(fast fourier transform) and STFT(short time fourier transform) for removing noise but it's impossible to know information about time and time-frequency localization capabilities has conflictive relationship. Therefore, for overcoming these limits, wavelet transform which is presented as a new technique of signal processing field is being applied in many fields recently. Because it has time-frequency localization capabilities it's Possible for multiresolution analysis as well as easy to analyze various signal. And when two wavelet base were designed to form Hilbert transform pair, wavelet pair provide superior performance than the existing DWT(discrete wavelet transform) in data characteristic detection. Therefore in this parer, we removed impulse noise by using adaptive-length median filter and two dyadic wavelet base which is designed by truncated coefficient vector.