• Journal of Digital Convergence
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• v.12 no.4
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• pp.319-326
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• 2014

According to the increasing mobile security users who have experienced authentication failure by forgetting passwords, user names, or a response to a knowledge-based question have preference for biological information such as hand geometry, fingerprints, voice in personal identification and authentication. Therefore biometric verification of personal identification and authentication for mobile security provides assurance to both the customer and the seller in the internet. Our study focuses on human hand biometric information recognition system for personal identification and personal Authentication, including its shape, palm features and the lengths and widths of the fingers taken from mobile phone photographs such as iPhone4 and galaxy s2. Our hand biometric information recognition system consists of six steps processing: image acquisition, preprocessing, removing noises, extracting standard hand feature extraction, individual feature pattern extraction, hand biometric information recognition for personal identification and authentication from input images. The validity of the proposed system from mobile phone image is demonstrated through 93.5% of the sucessful recognition rate for 250 experimental data of hand shape images and palm information images from 50 subjects.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1153-1160
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• 2018

As the number of online game users increases and the market size grows, various kinds of cheating are occurring. Game bots are a typical illegal program that ensures playtime and facilitates account leveling and acquisition of various goods. In this study, we propose a method to detect game bots based on user action time interval (ATI). This technique observes the behavior of the bot in the game and selects the most frequent actions. We distinguish between normal users and game bots by applying Machine Learning to feature frequency, ATI average, and ATI standard deviation for each selected action. In order to verify the effectiveness of the proposed technique, we measured the performance using the actual log of the 'Aion' game and showed an accuracy of 97%. This method can be applied to various games because it can utilize all actions of users as well as character movements and social actions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.160-166
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• 2020

As mobile-based hardware technology develops, many kinds of applications are also being developed. In addition, there is an increasing demand to automatically check that the interface of these applications works correctly. In this paper, we describe a method for accurately detecting faulty images from applications by comparing major characteristics from input color images. For this purpose, our method first extracts major characteristics of the input image, then calculates the differences in the extracted major features, and decides if the test image is a normal image or a faulty image dissimilar to the reference image. Experiment results show that the suggested approach robustly determines similar and dissimilar images by comparing major characteristics from input color images. The suggested method is expected to be useful in many real application areas related to computer vision, like video indexing, object detection and tracking, image surveillance, and so on.

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.471-480
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• 2002

In this paper, we implemented a real-time system improving the performance of the paper currency discrimination by integrating a weighted region of interest matching algorithm with a weighted shape feature matching algorithm of the blocked image. The system classifies the paper currency by comparing a query image with compared images based on the database that contain images of paper currency. Especially, the system has good efficiency at the contaminated, rotated, and translated paper currency. The system hardware consists of three parts as follows : the paper currency image acquired by CIS(contact image sensor) is applied to the pre-processing part with A/D converter and PLD. Finally the pre-processed image data are classified by the main image processing part with a high-speed DSP based on the proposed algorithm.

• Journal of KIISE:Software and Applications
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• v.28 no.11
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• pp.864-873
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• 2001

In this paper, a new approach to building a registration authority for issuing PKI-based certificates is presented to make the process of identifying an individual more secure and reliable by utilizing human iris recognition technology. The tasks of the proposed system associated with the manipulation of irises except for the general functions of registration authorities can be categorized into three modules, the acquisition of iris images, the registration of iris information, and the verification of users by means of iris patterns. The information among the three modules is safely exchanged through encryption and decryption with a symmetric cryptographic method. As a feature extraction method for a given iris image, a wavelet transform is applied to represent a feature vector with a small dimension of information obtained by subsampling an image corresponding to lower frequency bands successively without loss of information. Through the experiments on human iris recognition technology we proposed and applied to the registration authority, the potential of biometric technology in various applications is confirmed.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.421-433
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• 2011

The importance of acquisition of road information has recently been increased with a rapid growth of spatial-related services such as urban information system and location based service. This paper proposes an automatic road extraction method using object-based approach which was issued alternative of pixel-based method recently. Firstly, the spatial objects were created by MSRS(Modified Seeded Region Growing) method, and then the key road objects were extracted by using properties of objects such as their shape feature information and adjacency. The omitted road objects were also traced considering spatial correlation between extracted road and their neighboring objects. In the end, the final road region was extracted by connecting discontinuous road sections and improving road surfaces through their geometric properties. To assess the proposed method, quantitative analysis was carried out. From the experiments, the proposed method generally showed high road detection accuracy and had a great potential for the road extraction from high resolution satellite images.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.1
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• pp.111-122
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• 2018

Using OAuth protocol, third-party applications on the Android operating system use user's credentials or access tokens that have access authority on user's resources to gain user's account and personal information from account information providers. These credentials and token information are stored in the device by the OAuth data management method provided by the Android operating system. If this information is leaked, the attacker can use the leaked credential and token data to get user's personal data without login. This feature enables the digital forensic investigator to collect data directly from the remote server of the services used by the target of investigation in terms of collecting evidence data. Evidence data collected at a remote location can be a basis for secondary warranties and provide evidence which can be very important evidence when an attacker attempts to destroy evidence, such as the removal of an application from an Android device. In this paper, we analyze the management status of OAuth tokens in various Android operating system and device environment, and show how to collect data of various third party applications using it. This paper introduces a method of expanding the scope of data acquisition by collecting remote data of the services used by the subject of investigation from the viewpoint of digital forensics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.41-43
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• 2022

In order to prevent and block infectious diseases caused by the recent COVID-19 pandemic, non-contact biometric information acquisition and analysis technology is attracting attention. The invasive and attached biometric information acquisition method accurately has the advantage of measuring biometric information, but has a risk of increasing contagious diseases due to the close contact. To solve these problems, the non-contact method of extracting biometric information such as human fingerprints, faces, iris, veins, voice, and signatures with automated devices is increasing in various industries as data processing speed increases and recognition accuracy increases. However, although the accuracy of the non-contact biometric data acquisition technology is improved, the non-contact method is greatly influenced by the surrounding environment of the object to be measured, which is resulting in distortion of measurement information and poor accuracy. In this paper, we propose a context-based bio-signal modeling technique for the interpretation of personalized information (image, signal, etc.) for bio-information analysis. Context-based biometric information modeling techniques present a model that considers contextual and user information in biometric information measurement in order to improve performance. The proposed model analyzes signal information based on the feature probability distribution through context-based signal analysis that can maximize the predicted value probability.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.140-143
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• 2007

Fingerprint Recognition System is made up of Off-line treatment and On-line treatment; the one is registering all the information of there trieving features which are retrieved in the digitalized fingerprint getting out of the analog fingerprint through the fingerprint acquisition device and the other is the treatment making the decision whether the users are approved to be accessed to the system or not with matching them with the fingerprint features which are retrieved and database from the input fingerprint when the users are approaching the system to use. In matching between On-line and Off-line treatment, the most important thing is which features we are going to use as the standard. Therefore, we have been using "Delta" and "Core" as this standard until now, but there might have been some deficits not to exist in every person when we set them up as the standards. In order to handle the users who do not have those features, we are still using the matching method which enables us to make up of the spanning tree or the triangulation with the relations of the spanned feature. However, there are some overheads of the time on these methods and it is not sure whether they make the correct matching or not. In this paper, introduces a new data structure, called Union and Division, representing binary fingerprint image. Minutiae detecting procedure using Union and Division takes, on the average, 32% of the consuming time taken by a minutiae detecting procedure without using Union and Division.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.161-170
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• 2012

This paper presents an efficient and robust approach for determining the correspondence between unbalanced stereo images. The disparity vectors were used instead of feature points, such as corners, to calculate a correspondence relationship. For a faster and optimal estimation, the vectors were classified into several regions, and the homography of each region was calculated using the RANSAC algorithm. The correspondence image was calculated from the images transformed by each homography. Although it provided good results under normal conditions, it was difficult to obtain reliable results in an unbalanced stereo pair. Therefore, a balancing method is also proposed to minimize the unbalance effects using the histogram specification and structural similarity index. The experimental results showed that the proposed approach outperformed the baseline algorithms with respect to the speed and peak-signal-to-noise ratio. This work can be applied to practical fields including 3D depth map acquisition, fast stereo coding, 2D-to-3D conversion, etc.