• Spatial Information Research
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• v.18 no.3
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• pp.23-32
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• 2010

LIDAR data are useful for forest applications such as bare-earth DEM generation for forest areas, and estimation of tree height and forest biomass. As a core preprocessing procedure for most forest applications, this study attempts to develop an efficient method to detect forest areas from LIDAR data. First, we suggest three perceptual cues based on multiple return characteristics, height deviation and spatial distribution, being expected as reliable perceptual cues for forest area detection from LIDAR data. We then classify the potential forest areas based on the individual cue and refine them with a bi-morphological process to eliminate falsely detected areas and smoothing the boundaries. The final refined forest areas have been compared with the reference data manually generated with an aerial image. All the methods based on three types of cues show the accuracy of more than 90%. Particularly, the method based on multiple returns is slightly better than other two cues in terms of the simplicity and accuracy. Also, it is shown that the combination of the individual results from each cue can enhance the classification accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.350-356
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• 2017

With increasing attention to real-time body detection, active research is being conducted on human body detection based on skin color. Despite this, most existing skin detection methods utilize static skin color models and have detection rates in images, in which colors are distorted. This study proposed a method of detecting the skin region using a fuzzy classification of the gradient map, saturation, and Cb and Cr in the YCbCr space. The proposed method, first, creates a gradient map, followed by a saturation map, CbCR map, fuzzy classification, and skin region binarization in that order. The focus of this method is to rigorously detect human skin regardless of the lighting, race, age, and individual differences, using features other than color. On the other hand,the borders between these features and non-skin regions are unclear. To solve this problem, the membership functions were defined by analyzing the relationship between the gradient, saturation, and color features and generate 108 fuzzy rules. The detection accuracy of the proposed method was 86.35%, which is 2~5% better than the conventional method.

• Proceedings of the Korea Information Assurance Society Conference
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• 2004.05a
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• pp.251-257
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• 2004

Todays, the more information technologies(IT) like internet is developed, the more main facilities of individuals and social organizations get deeply involved in IT. Also, the trend of cyber threats such as internet worms and viruses is moving from local pc attacks to IT infrastructure attacks by exploiting inherent vulnerabilities of IT. Social organizations has a limit to response these attacks individually, and so the systematic coordinate center for social organizations is necessary. To analyze and share cyber threat information is performed prior to the construction of the coordinate center. In this paper, we survey domestic alert systems for cyber threats of related organizations and companies, and then classify them into two categories by the range of threat assessment: global alert systems for global If infrastructure and individual alert systems for each threat. Next, we identify problems of domestic alert systems and suggest approaches to resolve them.

• Explosives and Blasting
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• v.24 no.1
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• pp.29-37
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• 2006

The demand of the bulk emulsion explosives is being increased more and more by using the mechanization loading system in a domestic tunnel sites. Thus, a rational design criteria that is suitable for rock and circumstance condition has been required. In this study, authors investigated a optimum specific charging weight and resonable charging weight based on domestic blasting construction cases, which were performed by using a mechanization bulk emulsion explosives loading system up to now. Authors also analyzed the blasting results and got the following formula $({\Upsilon}= 0.669 + (0.0154{\times}RMR),\;r=0.81)$ from the relationship between a optimum specific charging weight of bulk exp. and rock mass rating. A range of resonable charging weight with a drilling depth is calculated considering a rock conditions.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1465-1473
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• 2006

In this paper, we present an approach for facial expression recognition using Active Shape Models(ASM) and a state-based model in image sequences. Given an image frame, we use ASM to obtain the shape parameter vector of the model while we locate facial feature points. Then, we can obtain the shape parameter vector set for all the frames of an image sequence. This vector set is converted into a state vector which is one of the three states by the state-based model. In the classification step, we use the k-NN with the proposed similarity measure that is motivated on the observation that the variation-regions of an expression sequence are different from those of other expression sequences. In the experiment with the public database KCFD, we demonstrate that the proposed measure slightly outperforms the binary measure in which the recognition performance of the k-NN with the proposed measure and the existing binary measure show 89.1% and 86.2% respectively when k is 1.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.205-211
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• 2019

Steganalysis is a technique that aims to detect and recover data hidden by steganography. Steganalytic methods detect hidden data by analyzing visual and statistical distortions caused during data embedding. However, for recovering the hidden data, they need to know which steganographic methods the hidden data has been embedded by. Therefore, we propose a hierarchical convolutional neural network (CNN) structure that identifies a steganographic method applied to an input image through multi-level classification. We trained four base CNNs (each is a binary classifier that determines whether or not a steganographic method has been applied to an input image or which of two different steganographic methods has been applied to an input image) and connected them hierarchically. Experimental results demonstrate that the proposed hierarchical CNN structure can identify four different steganographic methods (LSB, PVD, WOW, and UNIWARD) with an accuracy of 79%.

• Korean Journal of Ichthyology
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• v.26 no.4
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• pp.249-258
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• 2014

To examine the taxonomic status of Acheilognathus sp. specimens from the Geum River, morphological and genetical characteristics of A. sp., A. yamatsutae and A. majusculus were investigated and compared in detail. Specimens of A. sp. could be distinguished from the other two species by the combination of some morphological characters such as nuptial color, vertebrae, gillrakers and etc. Males of A. sp. had red bands on the outer margin of dorsal and anal fins and a white band on the outer margin of ventral fin in breeding season. A. sp. had larger maximum body length and somewhat more vertebrae than A. yamatsutae, and had fewer gillrakers than A. majusculus. A. sp. appeared as a monophyletic group with A. majusculus and A. cyanostigma based on genetic analysis. In addition, it had even more close relationship with other congeners than A. yamatsutae. Therefore it is presumed that A. sp. from the Geum River may be a distinct species in genus Acheilognathus.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.2
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• pp.89-94
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• 2016

This paper proposed a facial expression recognition approach using SIFT feature and SVM classifier. The SIFT was generally employed as feature descriptor at key-points in object recognition fields. However, this paper applied the SIFT descriptor as feature vector for facial expression recognition. In this paper, the facial feature was extracted by applying SIFT descriptor at each sub-block image without key-point detection procedure, and the facial expression recognition was performed using SVM classifier. The performance evaluation was carried out through comparison with binary pattern feature-based approaches such as LBP and LDP, and the CK facial expression database and the JAFFE facial expression database were used in the experiments. From the experimental results, the proposed method using SIFT descriptor showed performance improvements of 6.06% and 3.87% compared to previous approaches for CK database and JAFFE database, respectively.

• Journal of Korean Society of Steel Construction
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• v.23 no.2
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• pp.147-158
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• 2011

The purpose of this research was to analyze the connections of the seismic-performance values for domestic-performance-based designs. Basic research on the performance design method has been increasing of late, along with performance-based organization investigations. These investigations concern the performance level state of steel structure buildings. According to the performance limit state, seismic-performance values should be presented as appropriate steel structure engineering amounts. The first step, based on the full-scale steel structure experiments, involves researching on the making of a basic document. The moment-rotation angle relationship results of the experiment on the moment-frame connection were used to assort the functional and undamaged limits, which were assumed to be less than the yield moment. Moreover, the repairable and safety limits, which were assumed to exist between the yield and maximum moments, were assorted by investigating the accumulated plastic deformation ratio.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1992-1998
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• 2007

It is important to obtain conn cytodiagnosis to classify background, cytoplasm, and nucleus from the diagnostic image. This study mose an algorithm that detects and classifies carcinoma cells of the uterine cervix in Pap smear using features of cervical cancer. It applies Median filter and Gaussian filter to get noise-removed nucleus area and also applies Kapur method in binarization of the resultant image. We apply 8-directional contour tracking algorithm and stretching technique to identify and revise clustered cells that often hinder to obtain correct analysis. The resulted nucleus area has distinguishable features such as cell size, integration rate, and directional coefficient from normal cells so that we can detect and classify carcinoma cells successfully. The experiment results show that the performance of the algorithm is competitive with human expert.