• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.87-94
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• 2016

In this paper, we discuss a gait representation based on the width of silhouette in terms of discriminative power and robustness against the noise in silhouette image for gait recognition. Its sensitivity to the noise in silhouette image are rigorously analyzed using probabilistic noisy silhouette model. In addition, we develop a gait recognition system using width representation and identify subjects using the decision level fusion based on majority voting. Experiments on CASIA gait dataset A and the SOTON gait database demonstrate the recognition performance with respect to the noise level added to the silhouette image.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05b
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• pp.705-710
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• 1998

We describe a multigrid wavelet-based natural pixel (WNP) method for image reconstruction in emission computed tomography (ECT). The ECT is used to identify the tagged radioactive material's position in the body for detection of abnormal tissue such as tumor or cancer, as in SPECT and PET. With ECT methodology in parallel beam mode, we formulate a matrix-based reconstruction method for radionuclide sources in the human body. The resulting matrix for a practical problem is very large and nearly singular. To overcome this ill-conditioning, wavelet transform is considered in this study. Wavelets have inherent de-noising and multiscale resolution properties. Therefore, the multigrid wavelet-based natural pixel (WNP) method is very efficient to reconstruct image from projection data that is noisy and incomplete. We test this multigrid wavelet natural pixel (WNP) reconstruction method with the MCNP generated projection data for diagnosis of the simulated cancerous tumor.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.11
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• pp.1534-1541
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• 2003

A new window-based, user-friendly fringe analysis system is developed, especially for analyzing noisy interferograms. The system integrates three major techniques, that is fringe tracking, Phase shifting, and Fourier transform, into a single shell by employing a unified procedure. Since the system is made in a modular fashion and all processing modules can be shared for any technique, a user can select necessary modules and easily edit the applying order of them based on the user's analysis strategy, which should be changed depending on the noise level of the image. The system provides a high-level GUI and a variety of image handling tools and therefore users can easily access the system and produce the optimal results without giving up in the middle of a process even for severely noise-contaminated interferometric images.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.315-319
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• 2008

This paper describes a method for recognizing and measuring the motion of each individual leukocyte in microvessel from a sequence of images. A spatiotemporal image is generated whose spatial axes are parallel and vertical to vessel region contours. In order to enhance and extract only leukocyte traces with a turned velocity range even under noisy background, we use a combination of a filtering process using Gabor filters with sharp orientation selectivity and a subsequent 3D spatiotemporal grouping process. The proposed method is shown to be effective by experiments using image sequences of two kinds of microcirculation, rat mesentery microvessels and human retinal capillaries.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.1-8
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• 2015

Tracking of an object in 3D space performed in real-time is a significant task in different domains from autonomous robots to smart vehicles. In traditional methods, specific data acquisition equipments such as radars, lasers etc, are used. Contemporary computer technology development accelerates image processing, and it results in three-dimensional stereo vision to be used for localizing and object tracking in space. This paper describes a system for tracking three dimensional motion of an object using color information in real time. We create stereo images using pair of a simple web camera, raw data of an object positions are collected under realistic noisy conditions. The system has been tested using OpenCV and Matlab and the results of the experiments are presented here.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.425-428
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• 2003

Recently, the IDS(Intrusion Detection System) using a video camera is an important part of the home security systems which start gaining popularity. However, the video intruder detection has not been widely used in the home surveillance systems due to its unreliable performance in the environment with abrupt illumination change. In this paper, we propose an effective moving edge extraction algorithm from a sequence image. The proposed algorithm extracts edge segments from current image and eliminates the background edge segments by matching them with reference edge list, which is updated at every frame, to find the moving edge segments. The test results show that it can detect the contour of moving object in the noisy environment with abrupt illumination change.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1113-1116
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• 1999

In this papers, we proposes a efficient compression method of an image using the extraction of boundary region of DCT in MPEG-1. DCT coefficients have from low frequency to high frequency various components. After performing DCT to an image, the data is compressed to contain the boundary Region by quantization, and the information of boundary Region can be extracted by inverse DCT. In those, I chose frequency components susceptible to the boundary through the many experiences. In this paper, boundary can be selected by dividing low frequency by big quantization coefficient and dividing high frequency by small quantization coefficient without degrading visual qualify in MPEG-1. Also it is predicted that to reduce high frequency value will be good in noisy environments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.872-878
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• 2012

It is quite important to improve the visual acuity of a medical image by suppressing noisy parts and simultaneously keeping the details of signal components to draw the accurate diagnostics. With this aim, we suggest a novel method to generate Rotational Kernel Transformation (RKT) filter mask with applying Bresenham's algorithm and implement an nonlinear filtering algorithm to eliminate noises. As a result, we can find the fact that RKT filter mask can be automatically created and the visual acuity of a corrupted image can be elevated in terms of the signal-to-noise ratio (SNR) with applying the RKT filter.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3A
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• pp.284-289
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• 2002

In this paper, we propose the fast simulated annealing algorithm to decrease convergence rate in image segmentation using MRF. Simulated annealing algorithm has a good performance in noisy image or texture image, But there is a problem to have a long convergence rate. To fad a solution to this problem, we have labeled each pixel adaptively according to its intensity before simulated annealing. Then, we show the superiority of proposed method through experimental results.

• Current Optics and Photonics
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• v.7 no.6
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• pp.655-664
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• 2023

Ghost imaging (GI) technology is developing rapidly, but there are inevitably some limitations such as the influence of atmospheric turbulence. In this paper, we study a ghost imaging system in atmospheric turbulence and use a gamma-gamma (GG) model to simulate the medium to strong range of turbulence distribution. With a compressed sensing (CS) algorithm and generative adversarial network (GAN), the image can be restored well. We analyze the performance of correlation imaging, the influence of atmospheric turbulence and the restoration algorithm's effects. The restored image's peak signal-to-noise ratio (PSNR) and structural similarity index map (SSIM) increased to 21.9 dB and 0.67 dB, respectively. This proves that deep learning (DL) methods can restore a distorted image well, and it has specific significance for computational imaging in noisy and fuzzy environments.