• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.789-793
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• 1990

Preprocessing technique of the measurement bearing data is presented to improve the tar-get estimation accuracy for the bearing-only target notion analysis (TMA). Computer simulation is performed to compare with respect to the extended Kalman filter. By computer simulation, the target filter estimator with preprocessing Is both stable and robust to the measurement bearing noise.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.217-221
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• 1988

Preprocessing is indispensable to eliminate local granularities prior to region growing. In this paper, we examined the effects of preprocessing in S&M region growing technique. Experimental results show that a modified Nagao filter removes the local granularities well and compensates for the defects of Nagao filter.

• Journal of Biomedical Engineering Research
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• v.22 no.3
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• pp.285-291
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• 2001

In this paper, we designed two preprocessing adaptive filter - high pass filter and notch filter - using FPGA. For minimizing the calculation load of multi-channel and high-resolution ECG system, we utilize FPGA rather than digital signal processing chip. To implement the designed filters in FPGA, we utilize FPGA design tool(Altera corporation, MAX-PLUS II) and CSE database as test data. In order to evaluate the performance in terms of processing time, we compared the designed filters with the digital filters implemented by ADSP21061(Analog Devices). As a result, the filters implemented by FPGA showed better performance than the filters based on ADSP21061. As a consequence of examination, we conclude that FPGA is a useful solution in multi-channel and high-resolution signal processing.

• Journal of the Semiconductor & Display Technology
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• v.9 no.3
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• pp.65-69
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• 2010

The stereoscopic vision system is the algorithm to obtain the depth of target object of stereo vision image. This paper presents an efficient disparity matching method using nagao filter, octree color quantization and dynamic programming algorithm. we describe methods for performing color quantization on full color RGB images, using an octree data structure. This method has the advantage of saving a lot of data. We propose a preprocessing stereo matching method based on Nagao-filter algorithm using color information. using the nagao filter, we could obtain effective depth map and using the octree color quantization, we could reduce the time of computation.

• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1591-1600
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• 2011

The skyline of a multidimensional data set is the maximal subset whose elements are not dominated by other elements of the set. Skyline computation is considered to be very useful for a decision making system that deals with multidimensional data analyses. Recently, a great deal of interests has been shown to improve the performance of skyline computation algorithms. In order to speedup, the number of comparisons between data elements should be reduced. In this paper, we propose a filter lining scheme to accomplish such objectives. The scheme divides the multidimensional data space into angle-based partitions, and places a filter for each partition, and then connects them together in order to establish the final filter line. The filter line can be used to eliminate data, that are not part of the skyline, from the original data set in the preprocessing stage. The filter line is adaptively improved during the data scanning stage. In addition, skylines are computed for each remaining data partition, and are then merged to form the final skyline. Our scheme is an improvement of the previously reported simple preprocessing scheme using simple filters. The performance of the scheme is shown by experiments.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.309-315
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• 2009

Image reconstruction of Inverse Fourier Transform after Frequency Domain Data is filtered applies to Image signal acquired from MR. There are various kinds of image processing techniques; image preprocessing, image reconstruction, image compression, image restoration image mixture, noise and artifact elimination, and image quality improvement. In this paper, optimum filter applicable to diagnosis in clinic by comparing and analyzing the characteristics of the filter will be explained. Fermi-Dirac filter will improve the image quality better than the previous MR image.

• Journal of the Korean Geographical Society
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• v.51 no.4
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• pp.509-523
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• 2016

The soil prediction can provide quantitative soil information for sustainable mountainous ecosystem management. Visible near infrared spectroscopy, one of soil prediction methods, has been applied to predict several soil properties with effective costs, rapid and nondesctructive analysis, and satisfactory accuracy. Spectral preprocessing is a essential procedure to correct noisy spectra for visible near infrared spectroscopy. However, there are no attempts to evaluate various spectral preprocessing methods. We tested 5 different pretreatments, namely continuum removal, Savitzky-Golay filter, discrete wavelet transform, 1st derivative, and 2nd derivative to predict soil carbon(C) and nitrogen(N). Partial least squares regression was used for the prediction method. The total of 153 soil samples was split into 122 samples for calibration and 31 samples for validation. In the all range, absorption was increased with increasing C contents. Specifically, the visible region (650nm and 700nm) showed high values of the correlation coefficient with soil C and N contents. For spectral preprocessing methods, continuum removal had the highest prediction accuracy(Root Mean Square Error) for C(9.53mg/g) and N(0.79mg/g). Therefore, continuum removal was selected as the best preprocessing method. Additionally, there were no distinct differences between Savitzky-Golay filter and discrete wavelet transform for visual assessment and the methods showed similar validation results. According to the results, we also recommended Savitzky-Golay filter that is a simple pre-treatment with continuum removal.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.191-199
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• 2021

A distillation column, which is a main facility of the chemical process, separates the desired product from a mixture by using the difference of boiling points. The distillation process requires the optimization and the prediction of operation because it consumes much energy. The target process of this study is difficult to operate efficiently because the composition of feed flow is not steady according to the supplier. To deal with this problem, we could develop a data-driven model to predict operating conditions. However, data preprocessing is essential to improve the predictive performance of the model because the raw data contains outlier and noise. In this study, after optimizing the predictive model based long-short term memory (LSTM) and Random forest (RF), we used a low-pass filter and one-class support vector machine for data preprocessing and compared predictive performance according to the method and range of the preprocessing. The performance of the predictive model and the effect of the preprocessing is compared by using R2 and RMSE. In the case of LSTM, R2 increased from 0.791 to 0.977 by 23.5%, and RMSE decreased from 0.132 to 0.029 by 78.0%. In the case of RF, R2 increased from 0.767 to 0.938 by 22.3%, and RMSE decreased from 0.140 to 0.050 by 64.3%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.1
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• pp.1-11
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• 2005

The paper proposes a preprocessing method for efficient processing of XML queries in information retrieval with a large amount of XML documents. The conventional preprocessing methods filter out XML documents by parsing XML document for keyword of query or by comparing query signatures with signatures of XML document to be generated. But these methods are dependent on a query and are very in efficient for a large amount of XML documents. For this, we generate a universal DTD based on ontology of a domain. The universal DTD is applicable to the XML documents when they contain information of a same domain even when they have different structures and attributes. Then, using the universal DTD, we filter out the XML documents that are not bounded in the domain. We evaluate the performance of this method through experiments.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.560-563
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• 1999

In this paper, we present an optimal hardware implementation for preprocessing of a person identification algorithm utilizing vein pattern of dorsal surface of hand. For the vein pattern recognition, the computational burden of the algorithm lies mainly in the preprocessing of the input images, especially in lowpass filtering. we could reduce the identification time to one tenth by hardware design of the lowpass filter compared to sequential computations. In terms of the computation accuracy, the simulation results show that the CSD code provided an optimized coefficient value with about 91.62% accuracy in comparison with the floating point implementation of current coefficient value of the lowpass filter. The post-simulation of a VHDL model has been performed by using the ModelSim$^{TM}$. The implemented chip operates at 20MHz and has the operational speed of 55.107㎳.㎳.