• ETRI Journal
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• v.16 no.1
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• pp.17-34
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• 1994

In this paper, we present an architecture of the constant false alarm rate (CFAR) detector called the generalized order statistics (GOS) CFAR detector, which covers various order statistics (OS) and cell-averaging (CA) CFAR detectors as special cases. For the proposed GOS CFAR detector, we obtain unified formulas for the false alarm and detection probabilities. By properly choosing coefficients of the GOS CFAR detector, one can utilize any combination of ordered samples to estimate the background noise level. Thus, if we use a reference window of size N, we can realize $(2^N-1)$ kinds of CFAR processors and obtain their performances from the unified formulas. Some examples are the CA, the OS, the censored mean level, and the trimmed mean CFAR detectors. As an application of the GOS CFAR detector to multiple target detection, we propose an algorithm called the adaptive mean level detector, which censors adaptively the interfering target returns in a reference window.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.237-243
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• 2015

In recent image processing, active researches have been made along with rapid development in digital times. However, it is know that the image degradation occurs due to various external factors in the processes of image data processing, transmission and storage, and the main reason of image degradation is due to the noise. Typical methods to remove the noise are CWMF(center weighted median filter), A-TMF(alpha-trimmed mean filter) and AWMF(adaptive weighted median filter) and these methods have a little bit lacking noise reduction characteristics in mixed noise environments. Therefore, in order to remove the mixed noise, image restoration filter processing algorithm was suggested in this paper which processes by applying the median value of the mask and space weighted value after noise judgment. And for the objective judgment, it was compared with existing methods and PSNR(peak signal to noise ratio) was used as a judgment standard.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.798-801
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• 2014

Nowadays, the demand for multimedia services has grown with the rapid evolution in the digital era. But due to external causes in the process of processing, transmitting and storing image data, the images are damaged. One of the major causes of such damage is known to be noise. Some of the most commonly used methods for removing noise are CWMF(center weighted median filter), A-TMF(alpha-trimmed mean filter) and AWMF(adaptive weighted median filter). However, these filters all leave a bit to be desired in removing noise in a complex noise environment. Therefore this paper suggest an image restoration filter algorithm that first judges the noise and sets a adjustment weight based on the median value and distance of the mask to remove the complex noise. For an objective analysis, the results were compared against existing methods and the PSNR(peak signal to noise ratio) was used as a reference.

• ETRI Journal
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• v.16 no.2
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• pp.15-25
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• 1994

In this paper we present a new formula which can predict the exact detection probability of a generalized order statistics (GOS) constant false alarm rate (DFAR) detector for a partially correlated Rayleigh target model (0 < $ \rho$< 1) in a closed form, where $\rho$ is the correlation coefficient between returned pulses. By simply substituting a set of specific coefficient into the derived formula, one can obtain the detection probability of any kind of CFAR detector. Detectors may include the order statistics CFAR detector, the censored mean level detector, and the trimmed mean CFAR detector, but are not necessarily restricted to them. The numerical result for the first order Markov correlation model as applied to some of the detectors shows that as $\rho$ increases from zero to one, higher signal-to-noise ratio is required to achieve the same detection probability.

• Korean journal of food and cookery science
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• v.23 no.3 s.99
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• pp.378-387
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• 2007

In this study, we investigated the application of HACCP for a prepared side dish of sweet potato stems, within a free meal service system for the elderly in the Sungnam area. Total bacterial counts (TBC) and levels of coliforms and Esherichia coli (E.coli) were analyzed through an eight step cooking process. The TBCs of the raw samples ranged between 3.30 and 1.37${\times}10^4$ CFU/g per 100 cm$^2$ The trimmed, blanched, and drained sweet potato stems showed a mean TBC value of 1.37${\times}10^4$ CFU/g, and the level of coliforms was 1.48${\times}10^3$ CFU/g. Among the eight samples, however, after stir-frying and serving, the TBC decreased to a standard satisfactory level, and a coliforms and E. coli were not found. A five step process was used and samples were taken to check the microbial quality of the cook and cooking equipment. Here we tested for TBC, coliforms, Staphylococcus aureus (S. aureus), and Salmonella. Specifically, the TBC and number of coliforms were examined on the cook's hand's, cutting board, and knife, as they represented hazards for cross-contamination. The three inspection steps of preparation of the trimmed, rinsed, blanched, and drained sweet potato stems, cook's' hands, cutting board and knife were all considered CCPs, and a manual of cooking process management was established to improve the risk factors in this study. In conclusion, this study reinforces that microbiological analysis is as a valuable tool for checking what points and stages of the cooking process must be controlled.

• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.3-9
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• 1999

In this paper, the characteristics of LFM and CW signals in active sonar environment is investigated. CA, OS and TM CFAR processors are applied to the received CW/LFM signals which are plotted in the range/doppler domain. The performances of detection are analyzed. Particularly, using the real data, we certified that the results of the experiments are identical with the theoretical performance.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.119-131
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• 1995

Based on Monte-Carlo simulation results we propose a robust analysis of variance procedure by utilizing trimmed mean and Winsorized variance. We deal with mainly the one-way classification case. We evaluate the empirical distribution of a pseudo-F statistic based on symmetrically Winsorized sum of squares when the population is normally distributed.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.371-383
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• 2000

Lindsay (1994) and Basu et al (1997) show that another density-based distance called the negative exponential disparity (NED) is an excellent competitor to the Hellinger distance (HD) in generating an asymptotically fully efficient and robust estimator. Bhattacharya and Basu (1996) consider estimation of the locations of several normal populations when an order relation between them is known to be true. They empirically show that the robust HD based weighted likelihood estimators compare favorably with the M-estimators based on Huber's $\psi$ function, the Gastworth estimator, and the trimmed mean estimator. In this paper we investigate the performance of the weighted likelihood estimator based on the NED as a robust alternative relative to that based on the HD. The NED based estimator is found to be quite competitive in the settings considered by Bhattacharya and Basu.

• Proceedings of the Safety Management and Science Conference
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• 1999.11a
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• pp.565-574
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• 1999

In reverse engineering area, it is rapidly developing reconstruction of surfaces from scanning or digitizing data, but geometric models of existing objects unavailable many industries. This paper describes new methodology of reverse engineering area, good strategies and important algorithms in reverse engineering area. Furthermore, proposing reconstruction of surface technique is presented. A method find base geometry and blending surface between them. Each based geometry is divided by triangular patch which are compared their normal vector for face grouping. Each group is categorized analytical surface such as a part of the cylinder, the sphere, the cone, and the plane that mean each based geometry surface. And then, each based geometry surface is implemented infinitive surface. Infinitive average surface's intersections are trimmed boundary representation model reconstruction. This method has several benefits such as the time efficiency and automatic functional modeling system in reverse engineering. Especially, it can be applied 3D scanner and 3D copier.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.3
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• pp.197-203
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• 1999

Depending on geographical features and error sources in the survey field, inaccurate data is inevitable in GPS kinematic survey for positioning with feature codes. In this study, the trimmed mean and the first order differential equation are used to develop an inaccurate positioning data detection algorithm, and a cubic spline curve and a linear polynomial are used to interpolate the inaccurate data. Based on interpolated data, a digital map for 30 km range of rural highway is produced and a corresponding GIS coverage map is obtained by analyzing and solving the problem associated with the map.