• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.323-330
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• 2008

In this paper, we propose a new fingerprint sensing method that can reduce orientation error. General fingerprint input methods need finger to be put on the surface of a sensor. It can cause of rotation problem and it affects the recognition result significantly. This improved input method can minimize the rotation of a finger by holding double-sided sensor with both thumb and index finger at the same time. Whenever fingerprint is impressed, it has nearly the same orientation because sensors are located between two fingers. As a result, we can get a better performance in fingerprint recognition system, but it may need more hardware cost.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.375-385
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• 2012

The fingerprint is the identity authentication method which is representative uses biometrics. Compared with password methods there is a feature where the dangerousness of embezzling or lossing is few. With like these features using the fingerprint in OTP creations. In this paper, we introduce the developed prototype of OTP system using fingerprint. And the overcome method of OTP system's demerit using fingerprint which extracts few minutiae points into a whole fingerprint image is proposed. A few minutiae points wasn't generated many encryption key for OTP session. The proposed method is overlaid the same fingerprint simply and added many minutiae points as biased overlaid fingerprints. Hence the security of OTP using fingerprint and the randomness over password-guessing are strengthened.

• 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.

• Analytical Science and Technology
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• v.28 no.1
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• pp.26-32
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• 2015

The consistency and homogeneity of repetitive printing of artificial fingerprint were evaluated using a visual minutiae comparison method and an Automated Fingerprint Identification System (AFIS). The standard latent fingerprint pattern was prepared by the printing of a master digital fingerprint pattern with an inkjet printer cartridge case filled with artificial sweat. The master digital fingerprint pattern was prepared with a scanning of an inked fingerprint pattern of a living subject. The intensities of the master digital fingerprint pattern were adjusted by changing the 'output level' values of the Adobe Photoshop CS 5 software. Number of standard latent fingerprint patterns were printed and then developed with conventional latent fingerprint developing methods; ninhydrin treatment method and 1,2-indandion(1,2-IND)/$ZnCl_2$ treatment method. The ridge details of the latent fingerprint patterns developed with the reagents were visually compared with the inked fingerprint pattern and could confirm that the minutiae of both patterns are visually identical. The ridge detail of the inked fingerprint and reagent developed standard latent fingerprint patterns were compared with an AFIS. The average number of minutiae searched by the AFIS was $52.4{\pm}2.4$ (range = 48~56) for 50 ninhydrin developed latent fingerprint patterns, and $50.2{\pm}1.9$ (range = 47~53) for 50 1,2-IND/$ZnCl_2$ developed latent fingerprint patterns. These low standard deviation values over 50 repetitive printing demonstrated that the 50 standard latent patterns were printed with consistent and homogeneous manner.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.870-878
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• 2013

In this paper, we propose a novel fingerprint classification method to enhance the accuracy and efficiency of the fingerprint identification system, one of biometrics systems. According to the previous researches, fingerprints can be categorized into the several patterns based on their pattern of ridges and valleys. After construction of fingerprint database based on their patters, fingerprint classification approach can help to accelerate the fingerprint recognition. The reason is that classification methods reduce the size of the search space to the fingerprints of the same category before matching. First, we suggest a method to extract region of interest (ROI) which have real information about fingerprint from the image. And then we propose a feature extraction method which combines gray level co-occurrence matrix (GLCM) and wavelet features. Finally, we compare the performance of our proposed method with the existing method which use only GLCM as the feature of fingerprint by using the multi-layer perceptron and support vector machine.

• Journal of Broadcast Engineering
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• v.17 no.4
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• pp.659-669
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• 2012

This paper proposes the method to extract a binary audio fingerprint by combining several base binary fingerprints. Based on majority voting of base fingerprints, which are designed by mimicking the fingerprint used in Philips fingerprinting system, the proposed fingerprint is determined. In the matching part, the base fingerprints are extracted from the query, and distance is computed using the sum of them. In the experiments, the proposed fingerprint outperforms the base binary fingerprints. The method can be used for enhancing the existing binary fingerprint or for designing a new fingerprint.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1330-1337
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• 2017

In off-line phase of the preliminary Cut-off indoor positioning scheme, which is one of the indoor positioning scheme using the fingerprint, relative ranks of peak RSSIs received from beacons at each reference point are stored in the fingerprint map. In some reference points, signals of multiple beacons may be received. In this case, the relative ranks may be different when constructing fingerprint and when receiving signals in real-time. To solve this problem, we propose a method to utilize only up to five beacons with high ranking when constructing a fingerprint and when receiving signals in real-time and comparing them with stored information of a fingerprint. Experiments were conducted on the estimation probabilities and the average error when using this method. Those are compared with the previous methods. Experimental results show that the estimation probabilities and the average error are improved by removing only the remaining five beacons at each reference point of the fingerprint.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.800-808
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• 2008

A fingerprint verification system based on a set of invariant moment features and a nonlinear Back Propagation Neural Network(BPNN) verifier is proposed. An image-based method with invariant moment features for fingerprint verification is used to overcome the demerits of traditional minutiae-based methods and other image-based methods. The proposed system contains two stages: an off-line stage for template processing and an on-line stage for testing with input fingerprints. The system preprocesses fingerprints and reliably detects a unique reference point to determine a Region-of-Interest(ROI). A total of four sets of seven invariant moment features are extracted from four partitioned sub-images of an ROI. Matching between the feature vectors of a test fingerprint and those of a template fingerprint in the database is evaluated by a nonlinear BPNN and its performance is compared with other methods in terms of absolute distance as a similarity measure. The experimental results show that the proposed method with BPNN matching has a higher matching accuracy, while the method with absolute distance has a faster matching speed. Comparison results with other famous methods also show that the proposed method outperforms them in verification accuracy.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.29-34
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• 2002

Fingerprint recognition technology was studied by classification and matching. In general, there are five different classifications left loop, right loop, whore, arch, and tented-arch. These classifications are used to determine which class an individual's fingerprint belong to, thereby identifying the individual's fingerprint pattern. The result of this classification, which is sent to the large fingerprint database as an index, helps reduce the matching time and enhance the accuracy of fingerprint matching. The existing fingerprint classification method relies on the number and location of cores and delta points called singular points. The drawback of this method is the lack of accuracy stemming from the classification difficulty involving unclear and/or partially-erased fingerprints. The current paper presents an efficient classification method to rectify the problem associated with identifying Singular points from unclear fingerprints. This method, which is based on Gabor filter's unique characteristics for magnifying directional patterns and frequency range selections, improves fingerprint classification accuracy significantly. In this paper, this method is described and its test result is presented for verification.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.552-555
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• 1999

In this paper, a method for extracting the fingerprint regions and the table from fingerprint document which is the size of A4 including ten fingerprints images in a table is presented. The extraction of each fingerprint region is carried out by segmenting the foreground fingerprint region using a block filtering method and detecting its center point. The table extraction, by detecting a horizontal line using line tracing, and detecting a vertical line by its orthogonal equation. Here, T-shaped mask is proposed for finding the starting points of the vertical line intersecting horizontal line by the form of 'T'. Experimental results show above 95% correct rate of extracting the fingerprint region and table.