• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.293-296
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• 2003

The enhancement of fingerprint image is necessary to improve the performance of fingerprint recognition. The enhancement of fingerprint image with Gabor Filter(GF) is widely used. However GF has the weakness such as long processing time and the sensitivity to ridge frequency. To overcome these weaknesses, we propose a Modified Anisotropic Gaussian Filter(MAGF) which is modified from Anisotropic Filter proposed by S. Greenburg's(SAF). This proposed MAGF can reduce the calculation time of ridge frequency and improve the weakness of sensitivity to ridge frequency. We also explained that MAGF is better than others mathematically and experimentally.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1C
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• pp.50-58
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• 2004

An image enhancement method using modified anisotropic diffusion filter is proposed in this paper. It employs sensor noise estimation and scale space methods based on the minimum reliable scale. Then the anisotropic diffusion filter is modified by the calculated critical value function and local gradient. Through simulation, it is verified that the proposed algorithm has the capability of little or no noise amplification in homogenous region as well as superior edge enhancement.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.835-836
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• 2008

This paper presents a new method of segmenting characters in a car licence plate which is less influenced by illumination variation. It uses an anisotropic filter to reduce the lighting noise and a histogram specification scheme to obtain the binary image. Anisotropic smoothing filter process the input images, which are acquired under different lighting conditions, so that they may have similar image quality. The enhanced performance of the proposed algorithm has been proved by the experiment.

• Journal of the Optical Society of Korea
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• v.17 no.1
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• pp.33-37
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• 2013

In this study a new design concept of the Fabry-Perot filter, constructed with an anisotropic space layer and a couple of isotropic mirrors, was proposed based on the Maxwell equations and the characteristic matrix method. The single- and double-cavity Fabry-Perot filters were designed, and their optical properties were investigated with a developed software package. In addition, the dependence of the transmittance and phase shift for two orthogonal polarization states on the column angle of the anisotropic space layer and the incidence angle were discussed. We demonstrated that the polarization state of electromagnetic waves and phase shifts can be modulated by exploiting an anisotropic space layer in a polarization F-P filter. Birefringence of the anisotropic space layer provided a sophisticated phase modulation with varied incidence angles over a broad range, resulting in a wide-angle phase shift. This new concept would be useful for designing optical components with isotropic and anisotropic materials.

• Journal of the Korean Society of Radiology
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• v.10 no.1
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• pp.45-51
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• 2016

The purpose of this study was tried to remove the noise and improve the spatial resolution in the computed tomography (CT) by using anisotropic 2-dimensional (2D) diffusion based filter. We used 4-channel multi-detector CT and american association of physicists in medicine (AAPM) phantom was used for CT performance evaluation to evaluate the image quality. X-ray irradiation conditions for image acquisition was fixed at 120 kVp, 100 mAs and scanned 10 mm axis with ultra-high resolution. The improvement of anisotropic 2D diffusion filtering that we suggested firstly, increase the contrast of the image by using histogram stretching to the original image for 0.4%, and multiplying the individual pixels by 1.2 weight value, and applying the anisotropic diffusion filtering. As a result, we could distinguished five holes until 0.75 mm in the original image but, five holes until 0.40 mm in the image with improved anisotropic diffusion filter. The noise of the original image was 46.0, the noise of the image with improved anisotropic 2D diffusion filter was decreased to 33.5(27.2%). In conclusion improved anisotropic 2D diffusion filter that we proposed could remove the noise of the CT image and improve the spatial resolution.

• Journal of the Semiconductor & Display Technology
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• v.13 no.3
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• pp.61-67
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• 2014

Micro-cracks in crystalline silicon wafer often result in wafer breakage in solar wafer manufacturing, and also their existence may lead to electrical failure in post fabrication inspection. Therefore, the reliable detection of micro-cracks is of importance in the photovoltaic industry. In this paper, an experimental method to select optimal parameters in anisotropic diffusion filter is proposed. It can reliably detect micro-cracks by the distinct extension of boundary as well as noise reduction in near-infrared image patterns of micro-cracks. Its performance is verified by experiments of several type cracks machined.

• Korean Journal of Remote Sensing
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• v.31 no.1
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• pp.21-28
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• 2015

The essential idea of de-noising is referring to neighboring pixels of a center pixel to be updated. Conventional adaptive de-noising filters use local statistics, i.e., mean and variance, of neighboring pixels including the center pixel. The drawback of adaptive de-noising filters is that their performance becomes low when edges are contained in neighboring pixels, while anisotropic diffusion de-noising filters remove adaptively noises and preserve edges considering intensity difference between neighboring pixel and the center pixel. The anisotropic diffusion de-noising filters, however, use only intensity difference between neighboring pixels and the center pixel, i.e., local statistics of neighboring pixels and the center pixel are not considered. We propose a new connectivity function of two adjacent pixels using statistics of neighboring pixels and apply connectivity function to diffusion coefficient. Experimental results using an aerial image corrupted by uniform and Gaussian noises showed that the proposed algorithm removed more efficiently noises than conventional diffusion filter and median filter.

• Geophysics and Geophysical Exploration
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• v.18 no.2
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• pp.74-84
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• 2015

To yield physically meaningful images through elastic reverse-time migration, the wavefield separation which extracts P- and S-waves from reconstructed vector wavefields by using elastic wave equation is prerequisite. For expanding the application of the elastic reverse-time migration to anisotropic media, not only the anisotropic modelling algorithm but also the anisotropic wavefield separation is essential. The anisotropic wavefield separation which uses pseudo-derivative filters determined according to vertical velocities and anisotropic parameters of elastic media differs from the Helmholtz decomposition which is conventionally used for the isotropic wavefield separation. Since applying these pseudo-derivative filter consumes high computational costs, we have developed the efficient anisotropic wavefield separation algorithm which has capability of parallel computing by using GPUs (Graphic Processing Units). In addition, the highly efficient anisotropic elastic reverse-time migration algorithm using MPI (Message-Passing Interface) and incorporating the developed anisotropic wavefield separation algorithm with GPUs has been developed. To verify the efficiency and the validity of the developed anisotropic elastic reverse-time migration algorithm, a VTI elastic model based on Marmousi-II was built. A synthetic multicomponent seismic data set was created using this VTI elastic model. The computational speed of migration was dramatically enhanced by using GPUs and MPI and the accuracy of image was also improved because of the adoption of the anisotropic wavefield separation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1C
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• pp.45-49
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• 2004

An image enhancement method using modified anisotropic diffusion filter is proposed in this paper. It employs sensor noise estimation and scale space methods based on the minimum reliable scale. Then the anisotropic diffusion filter is modified by the calculated critical value function and local gradient. Through simulation, it is verified that the proposed algorithm has the capability of little or no noise amplification in homogenous region as well as superior edge enhancement.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.36-41
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• 2018

An image intensifying device is equipment that makes weak objects visible in a dark environment, such as making nighttime bright enough to let objects be visually observed. It is possible to obtain a clear image by amplifying the light in the presence of a certain amount of weak light. However, in an extremely low-light environment, where even moonlight is not present, there is not enough light to amplify anything, and the sharpness of the screen deteriorates. In this paper, a method is proposed to improve image quality by using multiple filters and anisotropic diffusion for output noise of the image-intensifying device in extreme low-light environments. For the experiment, the output of the image-intensifying device was obtained under extremely low-light conditions, and signal processing for improving the image quality was performed. The configuration of the filters for signal processing uses anisotropic diffusion after applying a median filter and a Wiener filter for effective removal of salt-and-pepper noise and Gaussian noise, which constitute the main noise appearing in the image. Experimental results show that the improvement visually enhanced image quality. Both peak signal-to-noise ratio (PSNR) and SSIM, which are quantitative indicators, show improved values.