• Journal of Korean Society for Geospatial Information Science
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• v.10 no.5 s.23
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• pp.75-80
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• 2002

Depending upon geographical features and surrounding errors in the survey field, inaccurate positioning is inevitable in a kinematic DGPs survey. Therefore, a data inaccuracy detection algorithm and an interpolation algorithm are essential to meet the requirement of a digital map. In this study, GPS characteristics are taken into account to develop the data inaccuracy detection algorithm. Then, the data interpolation algothim is obtained, based on the feature type of the survey. A digital map for 20km of a rural highway is produced by the kinematic DGPS survey and the features of interests are lines associated with the road. Since the vertical variation of GPS data is relatively higher, the trimmed mean of vertical variation is used as criteria of the inaccuracy detection. Four cases of 0.5%, 1%, 2.5% and 5% trimmings have been experimented. Criteria of four cases are 69cm, 65cm, 61cm and 42cm, respectively. For the feature of a curved line, cublic spine interpolation is used to correct the inaccurate data. When the feature is more or less a straight line, the interpolation has been done by a linear polynomial. Difference between the actual distance and the interpolated distance are few centimeters in RMS.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.114-123
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• 2016

The effective feature extraction method for unmanned aerial vehicle (UAV) detection is proposed and verified in this paper. The UAV engine sound is harmonic complex tone whose frequency ratio is integer and its variation is continuous in time. Using these characteristic, we propose the feature vector composed of a mean and standard deviation of difference value between fundamental frequency with 1st overtone as well as mean variation of their frequency. It was revealed by simulation that the suggested feature vector has excellent discrimination in target signal identification from various interfering signals including frequency variation with time. By comparing Fisher scores, three features based on frequency show outstanding discrimination of measured UAV signals with low signal to noise ratio (SNR). Detection performance with simulated interference signal is compared by MFCC by using ELM classifier and the suggested feature vector shows 37.6% of performance improvement As the SNR increases with time, the proposed feature can detect the target signal ahead of MFCC that needs 4.5 dB higher signal power to detect the target.

• Journal of Biosystems Engineering
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• v.22 no.2
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• pp.227-236
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• 1997

Manual grading and sorting of red-ginsengs are inherently unreliable due to its subjective nature. A computerized technique based on optical and geometrical characteristics was studied for the objective quality evalution. Spectral reflectance of three categories of red-ginsengs - "Chunsam", "Chisam", "Yangsam" - were measured and analyzed. Variation of reflectance among parts of a single ginseng was more significant than variation among the quality categories of ginsengs. A PC-based image processing algorithm was developed to extract geometrical features such as length and thickness of body, length and number of roots, position of head and branch point, etc. The algorithm consisted of image segmentation, calculation of Euclidean distance, skeletonization and feature extraction. Performance of the algorithm was evaluated using sample ginseng images and found to be mostly sussessful.

• The Journal of Engineering Research
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• v.2 no.1
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• pp.13-21
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• 1997

This paper describes how to represent varations of feature parameters to improve recognition of continuous speech. For speech recognition, feature parameters, which are formant frequencies, pitches, logarithmic energies and zero crossing retes are used in general. But, their values and variations depend on speakers, for example disparities between man and woman, and on their age. It is difficult to decide a priority the value of the variation width. Hence, we try to represent this variation by introducing fuzziness and recognize a continuous speech by fuzzy inference using fuzzy production rules.

• Journal of the Semiconductor & Display Technology
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• v.15 no.3
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• pp.1-5
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• 2016

In order to apply sub-resolution assist feature (SRAF) in extreme ultraviolet lithography, the maximum non-printing SRAF width and lithography process margin needs to be improved. Through simulation, we confirmed that the maximum SRAF width of 6% attenuated phase shift mask (PSM) is large compared to conventional binary intensity mask. The increase in SRAF width is due to dark region's reflectivity of PSM which consequently improves the process window. Furthermore, the critical dimension error caused by variation of SRAF width and center position is reduced by lower change in diffraction amplitude. Therefore, we speculate that the margin of SRAF application will be improved by using PSM.

• Journal of Sasang Constitutional Medicine
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• v.29 no.1
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• pp.29-39
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• 2017

Objectives Facial features can be utilized as an indicator of Korean medical diagnosis. They are often measured by using the diagnostic device for an objective diagnosis. Accordingly, it is necessary to verify the reliability of the features which are obtained from the device for the accurate diagnosis. In this study, we attempt to evaluate the repeatability of facial feature variables using the Sasang Constitutional Analysis Tool(SCAT) for the Sasang Constitutional face diagnosis. Methods Facial pictures of two subjects were taken 24 times respectively for two days according to a standard guideline. In order to evaluate the repeatability, the coefficient of variation was calculated for the facial features extracted from frontal and profile images. Results The coefficient of variation was less than 10% in most of the facial features except the upper lip, trichion, and chins related features. Conclusions It was confirmed that the coefficient of variation was small in most of the features which enables the objective and reliable analysis of face. However, some features showed the low reliability because the location of facial landmarks related to them is ambiguous. In order to solve the problem, a clear basis for the location discussion is required.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1927-1943
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• 2016

Jitterbug is a passive network covert timing channel supplying reliable stealthy transmission. It is also the basic manner of some improved covert timing channels designed for higher undetectability. The existing entropy-based detection scheme based on training sample binning may suffer from model mismatching, which results in detection performance deterioration. In this paper, a new detection method based on the feature of Jitterbug covert channel traffic is proposed. A fixed binning strategy without training samples is used to obtain bins distribution feature. Coefficient of variation (CV) is calculated for several sets of selected bins and the weighted mean is used to calculate the final CV value to distinguish Jitterbug from normal traffic. Furthermore, the timing window parameter of Jitterbug is estimated based on the detected traffic. Experimental results show that the proposed detection method can achieve high detection performance even with interference of network jitter, and the parameter estimation method can provide accurate values after accumulating plenty of detected samples.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.64.3-64.3
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• 2017

For the detection of transient sources in optical wide field surveys like KMTNet Supernova Project, difference imaging technique is commonly used. As this method produces a fair amount of false positives, it is also common to utilize machine learning algorithms to screen likely true positives. While deep learning methods such as a convolutional neural network has been successfully applied recently, its application can be limited if the size of the training sample is small. I will discuss a variation of more conventional method that adopts the wavelet transform for feature engineering and its performance.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.07a
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• pp.9-12
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• 2015

In this paper, we propose a new feature matching algorithm by modifying and combining the FAST(Features from Accelerated Segment Test) feature detector and SURF feature descriptor which is robust to the distortion of the given image. Scale space is generated to consider the variation of the scale and determine the candidate of features in the image robust to the noise. The original FAST algorithm results in many feature points along edges. To solve this problem, we apply the principal curvatures for refining it. We also use SURF descriptor to make it robust against the variations in the image by rotation. Through the experiments, it is shown that the proposed algorithm has better performance than the conventional feature matching algorithms even though it has much less computational load. Especially, it shows a strength for noisy images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.131-146
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• 2021

Multimodal biometric-based recognition has been an active topic because of its higher convenience in recent years. Due to high user convenience of finger, finger-based personal identification has been widely used in practice. Hence, taking Finger-Print (FP), Finger-Vein (FV) and Finger-Knuckle-Print (FKP) as the ingredients of characteristic, their feature representation were helpful for improving the universality and reliability in identification. To usefully fuse the multimodal finger-features together, a new robust representation algorithm was proposed based on hierarchical model. Firstly, to obtain more robust features, the feature maps were obtained by Gabor magnitude feature coding and then described by Local Binary Pattern (LBP). Secondly, the LGBP-based feature maps were processed hierarchically in bottom-up mode by variable rectangle and circle granules, respectively. Finally, the intension of each granule was represented by Local-invariant Gray Features (LGFs) and called Hierarchical Local-Gabor-based Gray Invariant Features (HLGGIFs). Experiment results revealed that the proposed algorithm is capable of improving rotation variation of finger-pose, and achieving lower Equal Error Rate (EER) in our homemade database.