• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.259-262
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• 1993

In this paper, a new pitch beginning point detection method by extracting the G-peak, is proposed. By the speech production model, the area of the first peak on a pitch interval of speech signals is emphasized. By using the above characteristics, this method have more advantages than the others for pitch beginning point detection. The defective decision caused by an impulsive noise is minimized and the pre-filtering is not necessary for this method, because the integration of signals takes place in the process.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.447-453
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• 1999

Salt accumulation is one of themajor problems in soils under protected cultivation . Since protected cultivation does not have rainfall or excessive irrigation, salt accumulaiton inthe soils is inevitable. In this study, characteristics of salt accumulation in soil column were ivestigated, and a salt-extracting method was tested to see its effectiveness. The results showed that the concentration of salt in top soil layers increased and electrical conductivity as thesalt concentration decreased especially in the top soil layer .When extraction medium was applied.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.4
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• pp.284-290
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• 2013

Feature detection is very important to image processing area. In this paper we compare and analyze some characteristics of image processing algorithms for corner and blob feature detection. We also analyze the simulation results through image matching process. We show that how these algorithms work and how fast they execute. The simulation results are shown for helping us to select an algorithm or several algorithms extracting corner and blob feature.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1769-1774
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• 2009

An algorithm for extracting the BJT DC model parameter values for SPICE model is proposed. The nonlinear optimization method for analyzing the device I-V data using the Levenberg-Marquardt algorithm is proposed and the method for calculating initial conditions of model parameters to improve the convergence characteristics is proposed. The base current and collector current obtained from the proposed method shows the root mean square error of 6.04% compared with the measured data of the PNP BJT named 2SA1980.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.7
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• pp.102-111
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• 1997

In this paper, a patern recognition method of surface mount device(SMD) IC using wavelet transform and neural network is proposed. We chose the feature parameter according to the characteristics of coefficient matrix which is obtained from four level discrete wavelet transform (DWT). These feature parameters are normalized and then used for the input vector of neural network which is capable of adapting the surroundings such as variation of illumination, arrangement of objects and translation. Experimental results show that when the same form of feature pattern, as is used for learning, is put into neural network and gained 100% rate ofrecognition irrespective of SMD IC kinds, location and variation of illumination. In the case of unused feature pattern for learning, the recognition rate is 85.9% under the similar surroundings, where as an average recognition rate is 96.87% for the case of reregulated value of illumination. Proosed method is relatively simple compared with the traditional space domain method in extracting the feature parameter and is also well suited for recognizing the pattern's class, position and existence. It can also shorten the processing tiem better than method extracting feature parameter with the use of discrete cosine transform(DCT) and adapt the surroundings such as variation of illumination, the arrangement and the translation of SMD IC.

• The Research Journal of the Costume Culture
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• v.19 no.2
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• pp.324-333
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• 2011

This study was accomplished for the purpose of developing a textile processing ingredient that is harmless to the human body and environment. The research method consists of dyeing cotton textiles by extracting the dye solution from ginseng. Then, chrominance, after treatment, antibacterial ratio and deodorization ratio of cotton fabrics dyed with ginseng extracts were tested and results were examined. The research procedure involved first extracting the dye solution from the ginseng's by-product (fine roots) and then dyeing was effectuated differently according to the test samples temperature and dyeing time requirements. Brightness in all dye substances was lower in pre-mordanting. Beige color could be extracted from pre-mordanted samples. And dark orange from postmordanted samples. Color-festness was high in all samples. Most of samples show a big antibacterial ratio and deodorization ratio. Through this research it has been discovered that, when applied to textiles, Korea's ginseng extract possessed reproducibility features as a natural dye and a possibility to be used in cutting which plays a crucial role in hygienic processing. In addition, by using ginseng's by-product for dyeing processing as the dye solution, efficient application of resources and occurrences of no water waste damages were demonstrated and thus, proved to be environmentally-friendly. Specifically, through this experiment, it was found that saponin, ginseng's special characteristics, possessed excellent antibacterial odor repelling functions to clothing as well as the capability to prevent skin disease.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.55-64
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• 2005

This study demonstrates the experiment based on digital photogrammetric processing for acquiring data related to slope monitoring. To apply dose-range digital photos for monitoring road rock slopes, digital elevation models and digital orthophotos were generated and 3D modelling was conducted for the visualization on a digital photogrammetric workstation. These digital photogrammetric products can be utilized as objective and scientific data not only for surveying and analyzing the shape and characteristics of the slopes but also for extracting various engineering data for building the database of the slopes and making the safety diagnosis of the slopes.

• Journal of information and communication convergence engineering
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• v.12 no.4
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• pp.263-270
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• 2014

Corner detection and feature extraction are essential aspects of computer vision problems such as object recognition and tracking. Feature detectors such as Scale Invariant Feature Transform (SIFT) yields high quality features but computationally intensive for use in real-time applications. The Features from Accelerated Segment Test (FAST) detector provides faster feature computation by extracting only corner information in recognising an object. In this paper we have analyzed the efficient object detection algorithms with respect to efficiency, quality and robustness by comparing characteristics of image detectors for corner detector and feature extractors. The simulated result shows that compared to conventional SIFT algorithm, the object recognition system based on the FAST corner detector yields increased speed and low performance degradation. The average time to find keypoints in SIFT method is about 0.116 seconds for extracting 2169 keypoints. Similarly the average time to find corner points was 0.651 seconds for detecting 1714 keypoints in FAST methods at threshold 30. Thus the FAST method detects corner points faster with better quality images for object recognition.

• Journal of Biomedical Engineering Research
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• v.39 no.2
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• pp.63-68
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• 2018

In modern society, speech recognition technology is emerging as an important technology for identification in electronic commerce, forensics, law enforcement, and other systems. In this study, we aim to develop an age classification algorithm for extracting only MFCC(Mel Frequency Cepstral Coefficient) expressing the characteristics of speech in Korean and applying it to deep learning technology. The algorithm for extracting the 13th order MFCC from Korean data and constructing a data set, and using the artificial intelligence algorithm, deep artificial neural network, to classify males in their 20s, 30s, and 50s, and females in their 20s, 40s, and 50s. finally, our model confirmed the classification accuracy of 78.6% and 71.9% for males and females, respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.153-160
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• 2016

A developed skill of an intelligent CCTV is also advancing by using its Image Acquisition Device. The most important part in the field of detecting comparatively fast moving objects is to effectively reduce the loads on updating the background image in order to achieve real-time update. However, the ability of the current general-purpose computer extracting the texture as characteristics has limits in application mostly due to the loads on processes. In this thesis, an algorithm for real-time updating the background image in an applied area such as detecting the fast moving objects like a driving car in a video of at least 30 frames per second is suggested and the performance is analyzed by a test of extracting object region from real input image.