• Journal of Biosystems Engineering
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• v.35 no.6
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• pp.450-457
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• 2010

Although cherry tomato is one of major vegetables consumed in fresh vegetable market, the quality grading method is mostly dependant on size measurement using drum shape sorting machines. Using Visible/Near-infrared spectroscopy, apparatus to be able to acquire transmittance spectrum data was made and used to estimate firmness, sugar content, and acidity of cherry tomatoes grown at hydroponic and soil culture. Partial least square (PLS) models were performed to predict firmness, sugar content, and acidity for the acquired transmittance spectra. To enhance accuracy of the PLS models, several preprocessing methods were carried out, such as normalization, multiplicative scatter correction (MSC), standard normal variate (SNV), and derivatives, etc. The coefficient of determination ($R^2_p$) and standard error of prediction (SEP) for the prediction of firmness, sugar, and acidity of cherry tomatoes from green to red ripening stages were 0.859 and 1.899 kgf, with a preprocessing of normalization, 0.790 and $0.434^{\circ}Brix$ with a preprocessing of the 1st derivative of Savitzky Golay, and 0.518 and 0.229% with a preprocessing normalization, respectively.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.3
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• pp.547-552
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• 2019

Recently, the massive growth in the scale of data has been observed as a major issue in the Big Data. Furthermore, the Big Data should be preprocessed for normalization to get a high performance of the Machine learning since the Big Data is also an input of Machine Learning. The performance varies by many factors such as the scope of the columns in a Big Data or the methods of normalization preprocessing. In this paper, the various types of normalization preprocessing methods and the scopes of the Big Data columns will be applied to the SVM(: Support Vector Machine) as a Machine Learning method to get the efficient environment for the normalization preprocessing. The Machine Learning experiment has been programmed in Python and the Jupyter Notebook.

• The Journal of Bigdata
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• v.8 no.1
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• pp.61-71
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• 2023

With the development of data-driven decision-making and sophisticated big data processing technique, there is a growing demand for information on how to process data. However, recent studies with data preprocessing mentioned only as a means to achieve a result. Therefore, in this study, we aimed to write in detail about the data processing pipeline, include preprocessing data. In particular, we shares the context and domain knowledge to aid fluent understand of the research.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.814-818
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• 2004

Off-line handwritten character recognition is in difficulty of incomplete preprocessing because it has not dynamic and timing information besides has various handwriting, extreme overlap of the consonant and vowel and many error image of stroke. Consequently off-line handwritten character recognition needs to study about preprocessing of various methods such as binarization and thinning. This paper considers running time of watershed algorithm and the quality of resulting image as preprocessing For off-line handwritten Korean character recognition. So it proposes application of effective watershed algorithm for segmentation of character region and background region in gray level character image and segmentation function for binarization image and segmentation function for binarization by extracted watershed image. Besides it proposes thinning methods which effectively extracts skeleton through conditional test mask considering running time and quality. of skeleton, estimates efficiency of existing methods and this paper's methods as running time and quality. Watershed image conversion uses prewitt operator for gradient image conversion, extracts local minima considering 8-neighborhood pixel. And methods by using difference of mean value is used in region merging step, Converted watershed image by means of this methods separates effectively character region and background region applying to segmentation function. Average execution time on the previous method was 2.16 second and on this paper method was 1.72 second. We prove that this paper's method removed noise effectively with overlap stroke as compared with the previous method.

• Fashion & Textile Research Journal
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• v.17 no.5
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• pp.838-843
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• 2015

In this study, a cotton knit was dyed with elm bark extract; subsequently, the dyed fabric was measured according to the types of mordants and the preprocessing cationizers used. Additionally, antibiosis against super bacteria was examined. The results follow. First, the color of the dyed cotton knit appeared reddish and yellowish for fabrics treated with non-mordants and mordants. When preprocessing with a cationizer was conducted, the dyeing properties were the best. Second. even when mordants were not used for dyeing, color fastness after washing, sweating, and rubbing was generally good Grade 4 and 5. Color fastness after exposure to sunlight was the best Grade 4 for fabric prepared with ferrous sulfate as the mordant. Third. as for antimicrobial properties, or resistance to super bacteria, the growth of bacteria was suppressed in a meaningful way for fabrics treated with non-mordants and mordants, compared to the control group fabric. The dyeing methods with the most powerful antimicrobial effects were dyeing after preprocessing with a cationizer and preparing fabric with copper sulfate as the mordant. The results stated above show that in case of dyeing with elm bark extract, preprocessing of the cotton knit with a cationizer and dying with copper mordant displayed high levels of antimicrobial properties that were useful for resisting super bacteria. Of these the dyeing properties were the best when preprocessing with a cationizer.

• The Journal of the Korea Contents Association
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• v.13 no.10
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• pp.62-70
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• 2013

DIBR(Depth Image Based Rendering) is a kind of view synthesis algorithm to generate images at free view points from the reference color image and its depth map. One of the main challenges of DIBR is the occurrence of holes that correspond to uncovered backgrounds at the synthesized view. In order to cover holes efficiently, two main approaches have been actively investigated. One is to develop preprocessing algorithms for depth maps or parallax maps to reduce the size of possible holes, and the other is to develop hole filling methods to fill the generated holes using adjacent pixels in non-hole areas. Most conventional preprocessing algorithms for reducing the size of holes are based on the smoothing process of depth map. Filtering of depth map, however, attenuates the resolution of depth map and generates geometric distortions. In this paper, we proposes a novel preprocessing algorithm for parallax map to improve the performance of hole-filling by avoiding the drawbacks of conventional methods.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.236-245
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• 2008

Robust face recognition under various illumination environments is very difficult and needs to be accomplished for successful commercialization. In this paper, we propose an efficient illumination preprocessing method for face recognition. illumination preprocessing algorithm based on anisotropic smoothing is well known to be effective among illumination normalization methods but deteriorates the intensity contrast of the original image, and incurs less sharp edges. The proposed method in this paper improves the previous anisotropic smoothing based illumination normalization method so that it increases the intensity contrast and enhances the edges while diminishing effects of illumination. Due to the result of these improvements, face images preprocessed by the proposed illumination preprocessing method becomes to have more distinctive feature vectors(Gabor feature vectors). Through experiments of face recognition using Gabor jet similarity, the effectiveness of the proposed illumination preprocessing method is verified.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.79-85
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• 2019

Recently, small radar require the development of small millimeter wave radar with high distance resolution to disable the target's system with a single strike. Small millimeter wave radar with high distance resolution need to process large amounts of data in real time to acquire and track target. In this paper, we summarized the real-time data preprocessing method to process the large amount of data required for small millimeter wave radar. In addition, the digital IF(Intermediate Frequency) receiver, Window processing, and, DFT(Discrete Fourier Transform) functions presented by real-time data preprocessing are implemented using FPGA(Field Programmable Gate Array). Finally the implemented real-time data preprocessing module was applied to the signal processor for small millimeter wave radar and verified by performance test related to the real-time preprocessing function.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.12
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• pp.609-619
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• 2015

A preprocessing scheme utilizing multi-division of the ROI (region of interest) in a chemiluminescence image during inversion is proposed. The resulting inverted image shows the flame's structure, which can be useful for studying combustion instability. The flame structure is often quantitatively visualized with PLIF (planar laser-induced fluorescence) images as well. The chemiluminescence image, which is a line-integral of the flame, needs to be preprocessed before inversion, mainly due to the inherent noise and the assumption of axisymmetry during the inversion. The feasibility of the multi-division preprocessing technique has been tested with experimentally-obtained OH PLIF and $OH^*$ chemiluminescence images of jet and swirl-stabilized flames burning substitute natural gas (SNG). It turns out that the technique outperforms two conventional methods, specifically, the technique without preprocessing and the one with uni-division, reconstructing the SNG flame structures much better than its two counterparts when compared using corresponding OH PLIF images. The characteristics of the optimum degree of polynomials to be applied for curve-fitting of the flame region data for the multi-division method involving two flames has also been investigated.

• Korean Journal of Metals and Materials
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• v.49 no.8
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• pp.657-663
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• 2011

This study represents the results of the peel strength and surface morphology according to the preprocessing times of polyimide (PI) in a Cu/Ni/PI structure flexible copper clad laminate production process based on the polyimide. Field emission scanning electron microscopy, X-ray diffraction, and X-ray photoelectron spectroscopy were used to analyze the surface morphology, crystal structure, and interface binding structure of sputtered Ni, Cu, and electrodeposited copper foil layers. The surface roughness of Ni, Cu deposition layers and the crystal structure of electrodeposited Cu layers were varied according to the preprocessing times. In the RF plasma times that were varied by 100-600 seconds in a preprocessing process, the preprocessing applied by about 300-400 seconds showed a homogeneous surface morphology in the metal layers and that also represented high peel strength for the polyimide. Considering the effect of peel strength on plastic deformation, preprocessing times can reasonably be at about 400 seconds.