• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.45-55
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• 2013

Thereby using smartphone and mobile device be more popular the more people utilize mobile device in many area such as education, news, financial. In January, 2007 Apple release i-phone it touch off rapid increasing in user of smartphone and it create new market and these broaden its utilization area. Smartphone use WiFi or 3G mobile radio communication network and it has a feature that can access to internet whenever and anywhere. Also using smartphone application people can search arrival time of public transportation in real time and application is used in mobile banking and stock trading. Computer's function is replaced by smartphone so it involves important user's information such as financial and personal pictures, videos. Present smartphone security systems are not only too simple but the unlocking methods are spreading out covertly. I-phone is secured by using combination of number and character but USA's IT magazine Engadget reveal that it is easily unlocked by using combination with some part of number pad and buttons Android operation system is using pattern system and it is known as using 9 point dot so user can utilize various variable but according to Jonathan smith professor of University of Pennsylvania Android security system is easily unlocked by tracing fingerprint which remains on the smartphone screen. So both of Android and I-phone OS are vulnerable at security threat. Compared with problem of password and pattern finger recognition has advantage in security and possibility of loss. The reason why current using finger recognition smart phone, and device are not so popular is that there are many problem: not providing reasonable price, breaching human rights. In addition, finger recognition sensor is not providing reasonable price to customers but through continuous development of the smartphone and device, it will be more miniaturized and its price will fall. So once utilization of finger recognition is actively used in smartphone and if its utilization area broaden to financial transaction. Utilization of biometrics in smart device will be debated briskly. So in this thesis we will propose fingerprint numbering system which is combined fingerprint and password to fortify existing fingerprint recognition. Consisted by 4 number of password has this kind of problem so we will replace existing 4number password and pattern system and consolidate with fingerprint recognition and password reinforce security. In original fingerprint recognition system there is only 10 numbers of cases but if numbering to fingerprint we can consist of a password as a new method. Using proposed method user enter fingerprint as invested number to the finger. So attacker will have difficulty to collect all kind of fingerprint to forge and infer user's password. After fingerprint numbering, system can use the method of recognization of entering several fingerprint at the same time or enter fingerprint in regular sequence. In this thesis we adapt entering fingerprint in regular sequence and if in this system allow duplication when entering fingerprint. In case of allowing duplication a number of possible combinations is $\sum_{I=1}^{10}\;{_{10}P_i}$ and its total cases of number is 9,864,100. So by this method user retain security the other hand attacker will have a number of difficulties to conjecture and it is needed to obtain user's fingerprint thus this system will enhance user's security. This system is method not accept only one fingerprint but accept multiple finger in regular sequence. In this thesis we introduce the method in the environment of smartphone by using multiple numbered fingerprint enter to authorize user. Present smartphone authorization using pattern and password and fingerprint are exposed to high risk so if proposed system overcome delay time when user enter their finger to recognition device and relate to other biometric method it will have more concrete security. The problem should be solved after this research is reducing fingerprint's numbering time and hardware development should be preceded. If in the future using fingerprint public certification becomes popular. The fingerprint recognition in the smartphone will become important security issue so this thesis will utilize to fortify fingerprint recognition research.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.313-316
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• 2002

The need to protect a main information and control a personal access using Biometrics in the intelligent building system is extended with growing the information and communication technologies in recent years. The fingerprint recognition technology is one of the biometrics methods available that has been widely used in various applications. But the present architecture of fingerprint recognition system has many of the problems because of centralized control network architecture. But we can solve the problems with distributed control network architecture. In this paper, the fingerprint recognition system uses the merit of the LonWorks. it is able to easily modularize the system and make up for the weak points in the typical fingerprint recognition system.

• Journal of Korea Multimedia Society
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• v.13 no.9
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• pp.1337-1347
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• 2010

Fingerprint recognition is a biometric technology to identify individual by using fingerprint features such ridges and valleys. Most fingerprint systems perform the recognition based on minutiae points after acquiring a fingerprint image from contact type sensor. They have an advantage of acquiring a clear image of uniform size by touching finger on the sensor. However, they have the problems of the image quality can be reduced in case of severely dry or wet finger due to the variations of touching pressure and latent fingerprint on the sensor. To solve these problems, the contactless capturing devices for a fingerprint image was introduced in previous works. However, the accuracy of detecting minutiae points and recognition performance are reduced due to the degradation of image quality by the illumination variation. So, this paper proposes a new LDP-based fingerprint recognition method. It can effectively extract fingerprint patterns of iterative ridges and valleys. After producing histograms of the binary codes which are extracted by the LDP method, chi square distance between the enrolled and input feature histograms is calculated. The calculated chi square distance is used as the score of fingerprint recognition. As the experimental results, the EER of the proposed approach is reduced by 0.521% in comparison with that of the previous LBP-based fingerprint recognition approach.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.653-662
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• 2002

Fingerprint recognition is a task to find a matching pattern in a database for a specific persons fingerprint. To accomplish this task, preprocessing, classification, and matching steps are taken for a large-scale fingerprint database but only the matching step is taken without classification for a small-scale database. The primary matching method is based on minutiae (ridge ending point, bifurcation). This matching method, however, requires a very complex computation to extract minutiae and match minutiae-to-minutiae accurately due to translation, rotation, nonlinear deformation of fingerprint and occurrence of spurious minutiae. In addition, this method requires a laborious preprocessing step in order to improve the quality of fingerprint Images. This paper proposes a new simple method to eliminate these problems. With this method, Gabor variance is used instead of minutiae for fingerprint recognition. The Gabor variance is computed from Gabor features that result from filtering a fingerprint image through Gabor filter. In this paper, this method is described and its test result is shown, demonstrating the potential of using this new method for fingerprint recognition.

• The Journal of the Korea Contents Association
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• v.2 no.4
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• pp.46-50
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• 2002

This paper suggests the adaptive binary method which applies advanced silt sum technique, so that threshold value can be changed heuristically according to the brightness of captured fingerprint image. Through this research, we tried to resolve threshold value setting issue by the local differences of brightness of fingerprint image in the binary image preprocessing. The experimental results show that our proposed preprocessing method demonstrates the better recognition accuracy and can be applied to minutiae extraction algorithm for fingerprint recognition system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.775-782
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• 2006

We generated blocks from the direction-extracted fingerprint during the pre-process of the fingerprint recognition algorithm and performed training by using the direction minutiae of each block as the input pattern of the neural network, so that we extracted the core points to use in the matching. Based on this, we designed the fingerprint recognition embedded system and tested it using the control board and the serial communication to utilize it for a variety of application systems. As a result, we can verify the reliance satisfactorily.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.347-352
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• 2004

We generated blocks from the direction-extracted fingerprint during the pre-process of the fingerprint recognition algorithm and performed training by using the direction minutiae of each block as the input pattern of the neural network, so that we extracted the core points to use in the matching. Based on this, we designed the fingerprint recognition embedded system and tested it by using the control board and the serial communication to utilize it for a variety of application systems. As a result, we can verify the reliance satisfactorily.

• Korean Journal of Remote Sensing
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• v.3 no.1
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• pp.25-39
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• 1987

The purpose of this research is to develop the Automatic Fingerprint Verfication System by digital computer based on specially in PC level. Fingerprint is used as means of personal identity verification in view of that it has the high reliability and safety. Fingerprint pattern recognition algorithm is constitute of 3 stages, namely of the preprocessing, the feature extraction and the recognition. The preprocessing stage includes smoothing, binarization, thinning and restoration. The feature extraction stage includes the extraction of minutiae and its features. The recognition stage includes the registration and the matching score calculation which measures the similarity between two images. Tests for this study with 325 pairs of fingerprint resulted in 100% of separation which which in turn is turned out to be the reliability of this algorithm.

• Journal of the Korea Society of Computer and Information
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• v.8 no.4
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• pp.63-68
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• 2003

Almost the system are usually taken by means of shapes and positions of ridge's end-points and bifurcation in the fingerprint recognition. but we studied about recognition of polluted fingerprint by chain code ridges. the results and sequence of processing are summarized as follows. (1)Capture several kinds of polluted fingerprint image. (2)Preprocessing(median filtering for removing noises, local and global histogram equalization, dilation and erosion, thinning and remove pseudo image), (3)Rebuild ridge line after Least Square Processing, (4)Compute distribution of chain code vector, (5)The results are almost same values of each vector of preprocessed fingerprint images. From the results, we can surmised more successful fingerprints recognition system in combination with other system by singular points

• Journal of Korea Multimedia Society
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• v.16 no.8
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• pp.914-926
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• 2013

Among the recent security systems, security system with fingerprint recognition gets many people's interests through the strengths such as exclusiveness, convenience, etc, in comparison with other security systems. The most important matters for fingerprint recognition system are reliability of matching between the fingerprint in database and user's fingerprint and rapid process of image processing algorithms used for fingerprint recognition. The existing fingerprint recognition system reduces the processing time by removing some processes in the feature extraction algorithms but has weakness of a reliability. This paper realizes the fingerprint recognition algorithm using MAMS(Multi-Access Memory System) for both the rapid processing time and the reliability in feature extraction and matching accuracy. Reliability of this process is verified by the correlation between serial processor's results and MAMS-PP64's results. The performance of the method using MAMS-PP64 is 1.56 times faster than compared serial processor.