• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.413-415
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• 2021

This paper proposes a nail detection algorithm using OpenPose and implements virtual nail art using it. Based on the key points detected by OpenPose, the finger area is detected using skin color characteristics for each finger. The nail region is detected from the edge image of the detected finger region. Then, a virtual nail art is implemented by synthesizing nail tips in the nail area. In a somewhat controlled shooting environment, simulation results show that the proposed algorithm detects nail areas well and implements virtual nail art well.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.154-163
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• 2023

With the rapid development of AI technology, ChatGPT and other AI content creation tools are becoming common, and users are becoming curious and adopting them. These tools, unlike search engines, generate results based on user prompts, which puts them at risk of inaccuracy or plagiarism. This allows unethical users to create inappropriate content and poses greater educational and corporate data security concerns. AI content detection is needed and AI-generated text needs to be identified to address misinformation and trust issues. Along with the positive use of AI tools, monitoring and regulation of their ethical use is essential. When detecting content created by AI with an AI content detection tool, it can be used efficiently by using the appropriate tool depending on the usage environment and purpose. In this paper, we collect data on AI content detection tools and compare and analyze the functions and characteristics of AI content detection tools to help meet these needs.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1475-1490
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• 2021

Detecting oil spill area using statistical characteristics of SAR images has limitations in that classification algorithm is complicated and is greatly affected by outliers. To overcome these limitations, studies using neural networks to classify oil spills are recently investigated. However, the studies to evaluate whether the performance of model shows a consistent detection performance for various oil spill cases were insufficient. Therefore, in this study, two CNNs (Convolutional Neural Networks) with basic structures(Simple CNN and U-net) were used to discover whether there is a difference in detection performance according to the structure of CNN and distribution characteristics of oil spill. As a result, through the method proposed in this study, the Simple CNN with contracting path only detected oil spill with an F1 score of 86.24% and U-net, which has both contracting and expansive path showed an F1 score of 91.44%. Both models successfully detected oil spills, but detection performance of the U-net was higher than Simple CNN. Additionally, in order to compare the accuracy of models according to various oil spill cases, the cases were classified into four different categories according to the spatial distribution characteristics of the oil spill (presence of land near the oil spill area) and the clarity of border between oil and seawater. The Simple CNN had F1 score values of 85.71%, 87.43%, 86.50%, and 85.86% for each category, showing the maximum difference of 1.71%. In the case of U-net, the values for each category were 89.77%, 92.27%, 92.59%, and 92.66%, with the maximum difference of 2.90%. Such results indicate that neither model showed significant differences in detection performance by the characteristics of oil spill distribution. However, the difference in detection tendency was caused by the difference in the model structure and the oil spill distribution characteristics. In all four oil spill categories, the Simple CNN showed a tendency to overestimate the oil spill area and the U-net showed a tendency to underestimate it. These tendencies were emphasized when the border between oil and seawater was unclear.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.535-543
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• 2018

Recently, level meters have been associated with the safety and maintenance of industrial sites and require a wide measurement range. Generally, to ensure the measurement range of the level meter, the measurement environment is improved to reduce the noise or to compensate the distortion of the signal through signal processing. The noise of FMCW (Frequency Modulated Continuous Wave) radar level meter or the distortion of the signal affects the near region characteristics of the level gauge, resulting in a reduction of the minimum detection distance. In this paper, an equalizer filter considering characteristics of window function and bit spectrum is applied to remove the noise in the near region of the level meter to improve the minimum detection distance performance and to improve the measurement reliability in the vicinity of the level meter, which is relatively difficult to detect, we want to improve the detection range.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.1
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• pp.47-58
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• 2011

MTI filter is used to separate target signal from clutter in many radar signal processing. By suppressing clutter before CFAR detection, the detection performance can be improved. As a radar system designed, a design engineer generally takes averaged SNR and CNR into account and does not include the effect of MTI filter's frequency response. In practice, when the signals including clutter are pass through the filter, SNR is widely varying according to target velocity and CNR is also varying according to clutter center frequency and spectrum spreading. In this paper, we have derived the relationship between the MTI filter's frequency response and a target's velocity and a clutter's spectrum characteristics. With the variation of SNR and CNR at the filter output, the detection performance of CFAR has been analyzed by the simulation and has made certain of their influences on the performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.442-450
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• 2014

This paper is a study of the propagation characteristic of matching liquids in the skin-covered breast model. In order to evaluate the matching liquids, we investigated six kinds of matching liquids applied to proposed 1-D breast model from frequency range of 3~6 GHz. A uniform plane wave is projected / transmitted inside the multi-layered breast model. Then the propagation characteristics inside the model and the transmission loss of each matching liquids were analyzed. The studying method presented in the paper can be used in the breast cancer detection system, the field of cancer detection using human tissue and the field of other medical devices. This paper was applied to the breast cancer detection system. Consequently, these studies could be used to determine the suitable type of matching liquids for breast cancer detection system and to apply useful for performance analysis.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1337-1345
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• 1996

Edge detection is the first step and very important step in image nalyisi. In this paper, proposed edge detection algorithm based on informations of edge structures and it is different from other classical edge detection operators such asgradient and surface fitting algorithm. The firs, we defined characteristics of edge structures such as continuity, thinness, localization, length. The second, we defined valid edge structures and ideal edge pixel positions in $3\times3$ window based on edge characteristics of edge structures. And we proposed twelve windows for enhance dissimilarity regions based on valid edge structures and ideal edge pixel positions. In specially, proposed algorithm was shown better performance of edge detection than other operators such as gradient operator and the LoG(Laplacian of gradient) operator of zero crossings in noisy test image with $\sigma=30$.

• International Journal of Highway Engineering
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• v.19 no.5
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• pp.69-75
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• 2017

PURPOSES : The purpose of this study is to evaluate different types of Ground Penetrating Radar (GPR) testing for characterizing the road cavity detection. The impulse and step-frequency-type GPR tests were conducted on a full-scale testbed with an artificial void installation. After analyzing the response signals of GPR tests for detecting the road cavity, the characteristics of each GPR response was evaluated for a suitable selection of GPR tests. METHODS : Two different types of GPR tests were performed to estimate the limitation and accuracy for detecting the cavities underneath the asphalt pavement. The GPR signal responses were obtained from the testbed with different cavity sizes and depths. The detection limitation was identified by a signal penetration depth at a given cavity for impulse and step-frequency-type GPR testing. The unique signal characteristics was also observed at cavity sections. RESULTS : The impulse-type GPR detected the 500-mm length of cavity at a depth of 1.0 m, and the step-frequency-type GPR detected the cavity up to 1.5 m. This indicates that the detection capacity of the step-frequency type is better than the impulse type. The step-frequency GPR testing also can reflect the howling phenomena that can more accurately determine the cavity. CONCLUSIONS :It is found from this study that the step-frequency GPR testing is more suitable for the road cavity detection of asphalt pavement. The use of step-frequency GPR testing shows a distinct image at the cavity occurrences.

• Journal of the Korean Institute of Gas
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• v.11 no.4
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• pp.47-53
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• 2007

The safe operation of high pressure pipe line systems is of significant importance. Leaks due to faulty operation from the pipelines can lead to considerable product losses and to exposure of community to dangerous gases. There are several leak detection methods, which have been recently suggested on pipeline network. The negative pressure wave detection technology, which has advantages of short time detection availability, accurate leaking location estimate capability and cost effective, is concentrated in this study. Theoretical analysis of the flow characteristics for leaking through a hole on the pipe wall has been performed by using CFD++, commercial CFD package. The results of 3-dimensional analysis near leaking hole confirm the occurrence of negative pressure wave and verify the characteristics of propagation of the wave which travels with speed equal to the speed of sound in the pipeline contents. For the application of long pipe line system. The method of 1-dimensional analysis has been suggested and verified with results of CFD++.

• Journal of KIISE:Information Networking
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• v.30 no.4
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• pp.504-512
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• 2003

In this paper, we propose a new adaptive dissolve detection method based on the analysis of a dissolve modeling error which is the difference between an ideally modeled dissolve curve with no correlation and an actual dissolve curve including a correlation. The proposed dissolve detection method consists of two steps. First, candidate dissolve regions are extracted using the characteristics of a downward convex parabola, then each candidate region is verified based oil the dissolve modeling error. If the dissolve modeling error for a candidate region is less than a threshold defined by the target modeling error with a target correlation, the candidate region is determined as a resolve region with a lower correlation than the target correlation. The threshold is adaptively determined based on the variances between the candidate regions and the target correlation. By considering the correlation between neighbor scenes, the proposed method is able to be a semantic scene-change detector. The proposed method was tested on various types of data and its performance proved to be more accurate and reliable regardless of variation of variance of test sequences when compared with other commonly use methods.