• The Journal of the Korea Contents Association
• /
• v.18 no.10
• /
• pp.431-442
• /
• 2018

2-dimensional barcode, QR code has been used for containing various information such as image, video, map, and business cards. Currently, a smartphone is used as a QR code scanner, displaying the code and converting it to a standard URL for a website. However, QR codes are not very common in encrypted application and so have a few applications. This paper proposes a new color-code, which integrates the conventional QR code and color design, and can be effectively used in some product certification system. The proposed method exploits the fact that genuine code is produced by CMYK color model, but the counterfeit is captured by RGB color model and during this process, color information of the code is changed. This paper introduces the color matrix model to measure the distortion between genuine code and counterfeit code. By investigating the statistical characteristics of color matrix, an effective detection of print image forgeries are designed. Various experiments with color codes show that the proposed system can be effectively used in product certification systems.

• Smart Structures and Systems
• /
• v.15 no.6
• /
• pp.1463-1479
• /
• 2015

Lamb waves have been a promising candidate for quantitative damage identification for various engineering structures, taking advantage of their superb capabilities of traveling for long distances with fast propagation and low attenuation. However, the application of Lamb waves in damage identification so far has been hampered by the fact that the characteristic signals associated with defects are generally weaker compared with those arising from boundary reflections, mode conversions and environmental noises, making it a tough task to achieve satisfactory damage identification from the time series. With awareness of this challenge, this paper proposes a time reversal-based technique to enhance the strength of damage-scattered signals, which has been previously applied to bulk wave-based damage detection successfully. The investigation includes (i) an analysis of Lamb wave propagation in a plate, generated by PZT patches mounted on the structure; (ii) an introduction of the time reversal theory dedicated for waveform reconstruction with a narrow-band input; (iii) a process of enhancing damage-scattered signals based on time reversal focalization; and (iv) the experimental investigation of the proposed approach to enhance the damage identification on a composite plate. The results have demonstrated that signals scattered by delamination in the composite plate can be enhanced remarkably with the assistance of the proposed process, benefiting from which the damage in the plate is identified with ease and high precision.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.2
• /
• pp.169-174
• /
• 2003

The trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online, or an offline internet, so it is expected to make a problem more and more. The goal of intrusion detection is to identify unauthorized use, misuse, and abuse of computer systems by both system insiders and external penetrators in real time. In fact, the general security system based on Internet couldn't cope with the attack properly, if ever. other regular systems have depended on common vaccine softwares to cope with the attack. But in this paper, we will use the positive selection and negative selection mechanism of T-cell, which is the biologically distributed autonomous system, to develop the self/nonself recognition algorithm and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. For making it come true, we will apply AIS to the network environment, which is a computer security system.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.23 no.1
• /
• pp.69-79
• /
• 2013

Recently, many enterprises are suffering from advanced types of malware and their variants including intelligent malware that can evade the current security systems. This addresses the fact that current security systems have limits on protecting advanced and intelligent security threats. To enhance the overall level of security, first of all, it needs to increase detection ratio of each security solution within a security system. In addition, it is also necessary to implement internetworking between multiple security solutions to increase detection ratio and response speed. In this paper, we suggest a collaborative security response method to overcome the limitations of the previous Internet service security solutions. The proposed method can show an enhanced result to respond to intelligent security threats.

• The Journal of the Korea Contents Association
• /
• v.19 no.11
• /
• pp.270-277
• /
• 2019

These days, with the advent of digital broadcasting, media environment offers users an opportunity to enjoy differentiated contents in a more aggressive fashion through user-media interactions based on computer technology. In fact, the development of contents which can induce spontaneous acts from users such as outdoor ads which use certain sensors and devices and exhibition halls has been active. With the development of low-price motion recognition devices, people have been able to enjoy diverse interaction-applied media by recognizing users' motion data without body contact. In this paper, we developed an interactive media player that can recognize the user's motion and control the video in the web service environment without installing a specific program. In addition, we set user motion recognition range and developed a user motion recognition algorithm suitable for the Leap Motion equipment installed in the kiosk. The results of this study can be experienced by various interactive media such as interactive tourism, education, and movie contents in kiosks that can be installed in public places.

• Journal of the Institute of Convergence Signal Processing
• /
• v.10 no.3
• /
• pp.164-169
• /
• 2009

This paper proposes a road detection method using BP(Back-Propagation) neural network based on texture information of the each candidate road region segmented for satellite images. To segment the candidate road regions, the histogram-based binarization method proposed by N.Otsu is firstly performed and the neighboring regions surrounding road regions are then removed. And after extracting the principal color using the histogram of the segmented foreground, the candidate road regions are classified into the regions within ${\pm}25$ of the principal color. Finally, the road regions are segmented using BP neural network based on texture information of the candidate regions. The texture information in this paper is calculated using co-occurrence matrix and is used as an input data of the BP neural network. The proposed method is based on the fact that the road has the constant intensity and shape. The experiment demonstrated the validity of the proposed method and showed 90% detection accuracy for the various images.

• Journal of Internet Computing and Services
• /
• v.5 no.6
• /
• pp.79-91
• /
• 2004

Various facial pose detection and recognition has been a difficult problem. The problem is due to the fact that the distribution of various poses in a feature space is mere dispersed and more complicated than that of frontal faces, This thesis proposes a robust pose-expression-invariant face recognition method in order to overcome insufficiency of the existing face recognition system. First, we apply the TSL color model for detecting facial region and estimate the direction of face using facial features. The estimated pose vector is decomposed into X-V-Z axes, Second, the input face is mapped by deformable template using this vectors and 3D CANDIDE face model. Final. the mapped face is transformed to frontal face which appropriates for face recognition by the estimated pose vector. Through the experiments, we come to validate the application of face detection model and the method for estimating facial poses, Moreover, the tests show that recognition rate is greatly boosted through the normalization of the poses and expressions.

• Korean Journal of Remote Sensing
• /
• v.12 no.1
• /
• pp.43-59
• /
• 1996

The objective of this research is to investigate the potential of relational matching in one of the fundamental photogrammetric processes, that is initial approximation problem. The automatic relative orientation procedures of aerial stereopairs have been investigated. The fact that the existing methods suffer from approximations, distortions (geometric and radiometric), occlusions, and breaklines is the motivation to investigate relational matching which appears to be a much more general solution. An elegant way of solving the initial approximation problem by using distinct(special) relationship from relational description is suggested and experimented. As for evaluation function, the cost function was implemented. The detection of erroneous matching is incorporated as a part of proposed relational matching scheme. Experiments with real urban area images where large numbers of repetitive patterns, breaklines, and occluded areas are present prove the feasibility of implementation of the proposed relational matching scheme. The investigation of relational matching in the domain of image matching problem provides advantages and disadvantages over the existing image matching methods and shows the future area of development and implementation of relational matching in the field of digital photogrammetry.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.11
• /
• pp.4290-4309
• /
• 2020

In recent years, advancements in machine learning capabilities have allowed it to see widespread adoption for tasks such as object detection, image classification, and anomaly detection. However, despite their promise, a limitation lies in the fact that a network's performance quality is based on the data which it receives. A well-trained network will still have poor performance if the subsequent data supplied to it contains artifacts, out of focus regions, or other visual distortions. Under normal circumstances, images of the same scene captured from differing points of focus, angles, or modalities must be separately analysed by the network, despite possibly containing overlapping information such as in the case of images of the same scene captured from different angles, or irrelevant information such as images captured from infrared sensors which can capture thermal information well but not topographical details. This factor can potentially add significantly to the computational time and resources required to utilize the network without providing any additional benefit. In this study, we plan to explore using image fusion techniques to assemble multiple images of the same scene into a single image that retains the most salient key features of the individual source images while discarding overlapping or irrelevant data that does not provide any benefit to the network. Utilizing this image fusion step before inputting a dataset into the network, the number of images would be significantly reduced with the potential to improve the classification performance accuracy by enhancing images while discarding irrelevant and overlapping regions.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.678-681
• /
• 2004

In this paper, efficient tracking of a moving object using optimal representative blocks is implemented by a mobile robot with a pan-tilt camera. The key idea comes from the fact that when the image size of moving object is shrunk in an image frame according to the distance between the camera of mobile robot and the moving object, the tracking performance of a moving object can be improved by changing the size of representative blocks according to the object image size. Motion estimation using Edge Detection(ED) and Block-Matching Algorithm(BMA) is often used in the case of moving object tracking by vision sensors. However these methods often miss the real-time vision data since these schemes suffer from the heavy computational load. In this paper, the optimal representative block that can reduce a lot of data to be computed, is defined and optimized by changing the size of representative block according to the size of object in the image frame to improve the tracking performance. The proposed algorithm is verified experimentally by using a two degree-of-freedom active camera mounted on a mobile robot.