• Proceedings of the KIEE Conference
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• 1979.08a
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• pp.158-159
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• 1979

Based on minimum-mean-sqare error criterion, a noise filtering algorithm for the reconstruction of an image function from noisy projection data is suggested. The filter is constructed with a few projection data. This algorithm requires less computational time compared with other noise filtering algorithm.

• Convergence Security Journal
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• v.2 no.1
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• pp.77-86
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• 2002

In this paper, we propose a segmentation algorithm that can reliably separate moving objects from noisy background in the image sequence received from a camera at the fixed position. Image segmentation is one of the most difficult process in image processing and an adoption in the change of environment must be considered for the increase in the accuracy of the image. The proposed algorithm consists of four process : generation of the difference image between the input image and the reference image, removes the background noise using the background nois modeling to a difference image histogram, then selects the candidate initial region using local maxima to the difference image, and gradually expanding the connected regions, region by region, using the shape information. The test results show that the proposed algorithm can detect moving objects like intruders very effectively in the noisy environment.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.276-284
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• 2009

In this paper, we develop the image transfer remote maintenance monitoring system for hand held device which can compensate defects of human mistake. The human mistakes always happen when the worker communicate information each other to check and maintenance the equipment of the power plant under bad circumstance such as small place and long distance in power plant. A worker couldn't converse with other when in noisy place like Power plant. So, we make some hand device for handy size and able to converse in noisy place. The developed system can have improvement of productivity through increasing plant operation time. And developed system is composed of advanced H/W(hard ware) system and S/W(soft ware)system. The H/W system consist of media server unit, communication equipment with hand held device, portable camera, mike and head set. The advanced s/w system consist of data base system, client pc(personal computer) real time monitoring system which has server GUI(graphic user interface) program, wireless monitoring program and wire ethernet communication program. The client GUI program is composed of total solution program as pc camera program, and phonetic conversation program etc.. We analyzed the required items and investigated applicable part in the image transfer remote maintenance monitoring system with hand held device. Also we investigated linkage of communication protocol for developed prototype, developed software tool of two-way communication and realtime recording skill of voice with image. We confirmed the efficiency by the field test in preventive maintenance of plant power.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.965-970
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• 2010

In this paper, a iterative image restoration method is proposed to restore for noisy-blurred images. In conventional method, regularization is usually applied to all over the without considering the local characteristics of image. As a result, ringing artifacts appear in edge regions and the noise amplification is introduced in flat regions. To solvethis problem we proposed an adaptive regularization iterative restoration using directional regularization operator considering edges in four directions and the regularization operator with no direction for flat regions. We verified that the proposed methods showed better results in the suppression of the noise amplification in flat regions, and introduced less ringing artifacts in edge regions. As a result it showed visually better image and improved better ISNR further than the conventional methods.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.3-6
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• 2003

A nonlinear iterative filtering based on local statistics and anisotropic diffusion is introduced. Local statistics determines the diffusion coefficient at each iteration step. Anisotropic diffusion can be seen as estimates a piecewise smooth image from the noisy input image in the experimental section, our results are shown to suppress noise with preserving the edges. Therefore, it enhances the image and improves performance.

• Current Optics and Photonics
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• v.2 no.1
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• pp.69-78
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• 2018

This paper presents a precise edge detection algorithm for the critical dimension (CD) measurement of a Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) pattern. The sigmoid surface function is proposed to model the blurred step edge. This model can simultaneously find the position and geometry of the edge precisely. The nonlinear least squares fitting method (Levenberg-Marquardt method) is used to model the image intensity distribution into the proposed sigmoid blurred edge model. The suggested algorithm is verified by comparing the CD measurement repeatability from high-magnified blurry and noisy TFT-LCD images with those from the previous Laplacian of Gaussian (LoG) based sub-pixel edge detection algorithm and error function fitting method. The proposed fitting-based edge detection algorithm produces more precise results than the previous method. The suggested algorithm can be applied to in-line precision CD measurement for high-resolution display devices.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.149-160
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• 2001

In this paper we employ two-sample location tests such as Wilcoxon test and T test for detecting edges in noisy images. For this, we compute a test statistic on pixel gray levels obtained using an edge-height parameter and compare it with a threshold determined by a significance level. Experimental results applied to sample images are given and performances of these tests in terms of the objective measure are compared.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.1
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• pp.8-16
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• 2014

We consider the visual barcode recognition problem in a noisy video data setup. Unlike most existing single-frame recognizers that require considerable user effort to acquire clean, motionless and blur-free barcode signals, we eliminate such extra human efforts by proposing a robust video-based barcode recognition algorithm. We deal with a sequence of noisy blurred barcode image frames by posing it as an online filtering problem. In the proposed dynamic recognition model, at each frame we infer the blur level of the frame as well as the digit class label. In contrast to a frame-by-frame based approach with heuristic majority voting scheme, the class labels and frame-wise noise levels are propagated along the frame sequences in our model, and hence we exploit all cues from noisy frames that are potentially useful for predicting the barcode label in a probabilistically reasonable sense. We also suggest a visual barcode tracking approach that efficiently localizes barcode areas in video frames. The effectiveness of the proposed approaches is demonstrated empirically on both synthetic and real data setup.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.1021-1024
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• 2000

In this paper we describe a nonparametric Wilcoxon test and a parametric Z test based on statistical hypothesis testing for the detection of edges. We use the threshold determined by specifying significance level $\alpha$, while Bovik, Huang and Munson[4] consider the range of possible values of test statistics for the threshold. From the experimental results of edge detection, the Z method performs sensitively to the noisy image, while the Wilcoxon method is robust over both noisy nd noise-free images. Comparison with our statistical tests and Sobel operator shows that our tests perform more effectively in both noisy and noise-free images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.147-153
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• 2004

This paper proposes an efficient edge detection using Van der Waerden statistic in original and noisy images. An edge is where the intensity of an image moves from a low value to a high value or vice versa. We describe a nonparametric Wilcoxon test and a parametric T test based on statistical hypothesis testing for the detection of edges. We use the threshold determined by specifying significance level $\alpha$, while Bovik, Huang and Munson consider the range of possible values of test statistics for the threshold. From the experimental results of edge detection, the T and Wilcoxon method perform sensitively to the noisy image, while the proposed Waerden method is robust over both noisy and noise-free images under $\alpha$=0.0005. Comparison with our statistical test and Sobel, LoG, Canny operators shows that Waerden method perform more effectively in both noisy and noise-free images.