• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.6
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• pp.43-50
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• 2007

In this paper we propose a method that identifies users at H.264 streaming using watermarking with fingerprints. The watermark can efficiently reduce the potential danger of forgery or alteration. Especially a biometric watermark has various advantages. Among entire biometric characteristics, the fingerprint is the most convenient and economical. In this paper we propose a novel fingerprint-based watermarking technique that can survive under very low bit-rate compression. The proposed algorithm consists of enhancement of a fingerprint image, the watermark generation using the extracted feature coordinates, watermark insertion using discrete wavelet transform, and authentication. The proposed algorithm can achieve robust watermark extraction against 0.264 compressed videos.

• Genomics & Informatics
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• v.10 no.4
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• pp.249-255
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• 2012

In this study, fosmid cloning strategies were used to assess the microbial populations in water from the International Space Station (ISS) drinking water system (henceforth referred to as Prebiocide and Tank A water samples). The goals of this study were: to compare the sensitivity of the fosmid cloning strategy with that of traditional culture-based and 16S rRNA-based approaches and to detect the widest possible spectrum of microbial populations during the water purification process. Initially, microbes could not be cultivated, and conventional PCR failed to amplify 16S rDNA fragments from these low biomass samples. Therefore, randomly primed rolling-circle amplification was used to amplify any DNA that might be present in the samples, followed by size selection by using pulsed-field gel electrophoresis. The amplified high-molecular- weight DNA from both samples was cloned into fosmid vectors. Several hundred clones were randomly selected for sequencing, followed by Blastn/Blastx searches. Sequences encoding specific genes from Burkholderia, a species abundant in the soil and groundwater, were found in both samples. Bradyrhizobium and Mesorhizobium, which belong to rhizobia, a large community of nitrogen fixers often found in association with plant roots, were present in the Prebiocide samples. Ralstonia, which is prevalent in soils with a high heavy metal content, was detected in the Tank A samples. The detection of many unidentified sequences suggests the presence of potentially novel microbial fingerprints. The bacterial diversity detected in this pilot study using a fosmid vector approach was higher than that detected by conventional 16S rRNA gene sequencing.

• Convergence Security Journal
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• v.16 no.5
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• pp.57-63
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• 2016

In recent years, there is growing interest in 'Fin-tech' in the domestic and international financial sector. And a variety of services in such a situation has emerged. To ensure the safety of from hacking attacks, many new technologies have been developed. These leading technology is the Bio-authentication method that you consider applying to the financial sector. Bio authentication is using biometric information. Also it is known that can cope the threat of fabrication and modifying attacks with shared and stored. However, Recently, When you look at hacking incidents of biometric data(560 million cases) in the United States Office of Personnel Management and advent of the fingerprints counterfeit technology, We can be known that should be reconsidered about the safety of bio-certification. Especially, it should be provided with a response measures for the problem of embezzlement that biometric information already been leaked. Thereby In this paper, by investigating biometric technologies and practices applied and of the vulnerability factor in many industries, it expected to be utilized in the prepared threats countermeasures in accordance with the application of the biometric authentication technology in a future.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.88-100
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• 1998

In this paper, an algorithm for a real-time automatic fingerprint identification system is proposed. The fingerprint feature volume is extracted by considering distinct and local characteristics(such as intensity and image quality difference etc.) in fingerprint images, which makes the algorithm properly adaptive to various image acquisitionj methods. Also the matching technique is designed to be invariant on rotation, scaling and translation (RST) changes while being capable of real-time processing. And the classification of fingerprints is performed based on the ridge flow and the relations among singular points such as cores and deltas. The developed fingerprint identification algorithm has been applied to various sets of fingerprint images such as one from NIST(National Institute of Standards and Technology, USA), a pressed fingerprint database constructed according to Korean population distributions in sex, ages and jobs, and a set of rolled-than-scanned fingerprint images. The overall performance of the algorithm has been analyzed and evaluated to the false rejection ratio of 0.07% while holding the false acceptance ratio of 0%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.125-133
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• 2011

For any pattern matching based algorithm in WLAN environment, the characteristics of signal to noise ratio(SNR) to multiple access points(APs) are utilized to establish database in the training phase, and in the estimation phase, the actual two dimensional coordinates of mobile unit(MU) are estimated based on the comparison between the new recorded SNR and fingerprints stored in database. As fingerprinting method, k-nearest neighbor(KNN) has been widely applied for indoor location in wireless location area networks(WLAN), but its performance is sensitive to number of neighbors k and positions of reference points(RPs). So intuitive fuzzy c-means(IFCM) clustering algorithm is applied to improve KNN, which is the KNN/IFCM hybrid algorithm presented in this paper. In the proposed algorithm, through KNN, k RPs are firstly chosen as the data samples of IFCM based on signal to noise ratio(SNR). Then, the k RPs are classified into different clusters through IFCM based on SNR. Experimental results indicate that the proposed KNN/IFCM hybrid algorithm generally outperforms KNN, KNN/FCM, KNN/PFCM algorithm when the locations error is less than 2m.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.109-115
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• 2011

As fingerprinting method, k-nearest neighbor(KNN) has been widely applied for indoor location in wireless location area networks(WLAN), but its performance is sensitive to number of neighbors k and positions of reference points(RPs). So artificial neural network(ANN) clustering algorithm is applied to improve KNN, which is the KNN/ANN hybrid algorithm presented in this paper. For any pattern matching based algorithm in WLAN environment, the characteristics of signal to noise ratio(SNR) to multiple access points(APs) are utilized to establish database in the training phase, and in the estimation phase, the actual two dimensional coordinates of mobile unit(MU) are estimated based on the comparison between the new recorded SNR and fingerprints stored in database. In the proposed algorithm, through KNN, k RPs are firstly chosen as the data samples of ANN based on SNR. Then, the k RPs are classified into different clusters through ANN based on SNR. Experimental results indicate that the proposed KNN/ANN hybrid algorithm generally outperforms KNN algorithm when the locations error is less than 2m.

• The Plant Pathology Journal
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• v.29 no.4
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• pp.357-363
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• 2013

The fungus Venturia nashicola is the causal agent of scab on Asian pears. For the rapid and reliable identification as well as sensitive detection of V. nashicola, a PCR-based technique was developed. DNA fingerprints of three closely related species, V. nashicola, V. pirina, and V. inaequalis, were obtained by random amplified polymorphic DNA (RAPD) analysis. Two RAPD markers specific to V. nashicola were identified by PCR, after which two pairs of sequence characterized amplified region (SCAR) primers were designed from the nucleotide sequences of the markers. The SCAR primer pairs, designated as D12F/D12R and E11F/E11R, amplified 535-bp and 525-bp DNA fragments, respectively, only from genomic DNA of V. nashicola. The specificity of the primer sets was tested on strains representing three species of Venturia and 20 fungal plant pathogens. The nested PCR primer pair specific to V. nashicola was developed based on the sequence of the species-specific 525-bp DNA fragment amplified by primer set E11F/E11R. The internal primer pair Na11F/Na11R amplified a 235-bp fragment from V. nashicola, but not from any other fungal species tested. The nested PCR assay was sensitive enough to detect the specific fragment in 50 fg of V. nashicola DNA.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.77-85
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• 2010

Fingerprint image quality checking is one of the most important issues in on-line fingerprint recognition because the recognition performance is largely affected by the quality of fingerprint images. In the past, many related fingerprint quality checking methods have typically considered the local quality of fingerprint. However, It is necessary to estimate the global quality of fingerprint to judge whether the fingerprint can be used or not in on-line recognition systems. Therefore, in this paper, we propose both local and global-based methods to calculate the fingerprint quality. Local fingerprint quality checking algorithm considers both the condition of the input fingerprints and orientation estimation errors. The 2D gradients of the fingerprint images were first separated into two sets of 1D gradients. Then，the shapes of the PDFs(Probability Density Functions) of these gradients were measured in order to determine fingerprint quality. And global fingerprint quality checking method uses neural network to estimate the global fingerprint quality based on local quality values. We also analyze the matching performance using FVC2002 database. Experimental results showed that proposed quality check method has better matching performance than NFIQ(NIST Fingerprint Image Quality) method.

• Journal of Microbiology and Biotechnology
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• v.11 no.5
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• pp.788-797
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• 2001

The usefulness of three PCR methods were evaluated for the epidemiological typing of Staphylococcus aureus: an enterobacterial repetitive intergenic consensus sequence PCR (ERIC-PCR), repetitive extragenic palindromic element PCR (REP-PCR), and 16S-23S intergenic spacer PCR (ITS-PCR). The analysis was performed using a collection of S. aureus strains comprised of 6 reference and 79 isolates from patients with various diseases. Among the 85 S. aureus strains tested, 6 references and 6 isolates were found to be susceptible to methicillin, whereas the remaining 73 isolates were resistant to it. PCR methods are of special concern, as conventional phenotypic methods are unable to clearly distinguish among methicillin-resistant S. aureus (MRSA) strains. The ability of the techniques to detect different unrelated types was found to be as follows: ERIC-PCR, 19 types; REP-PCR, 36 types; and ITS-PCR, 14 types. On the basis of combining the ERIC, REP, and ITS fingerprints, the 85 S. aureus strains were grouped into 56 genetic types (designated G1 to G56). The diversities for the 85 S. aureus strains, calculated according to Simpson\`s index, were 0.88 for an ERIC-PCR, 0.93 for a REP-PCR, and 0.48 for an ITS-PCR, and the diversity increased up to 0.97 when an ERIC-PCR and REP-PCR were combined. The above discrimination indices imply that the genetic heterogeneity of S. aureus strains is high. Accordingly, this study demonstrates that DNA sequences from highly conserved repeats of a genome, particularly a combination of ERIC sequences and REP elements, are a convenient and accurate tool for the subspecies-specific discrimination and epidemiologic tracking of S. aureus.

• Journal of Microbiology and Biotechnology
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• v.9 no.6
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• pp.744-750
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• 1999

Forty alcohol yeast strains were isolated from the main mashes (10 strains from each mash) for brewing of 4 different kinds of Korean traditional liquor (3 different types of Yakju and 1 Takju). Thirty-eight out of 40 strains were identified to be the same strain, Saccharomyces boulardii, by the Automated Bacteria, Yeast, and Fungi Identification System (Biolog Co., U.S.A.) based on the metabolic fingerprints. One strain that showed the highest ethanol production among the 38 strains in YPD medium, designated SHY 111, was selected and used for differentiating from other yeast type strains using the polymerase chain reaction (PCR). Amplified DNA, from transcribed internal spacers of SHY 111 chromosomal DNA, was found to be the same in both size and sequence as those of S. cerevisiae KCCM 11215 (formerly S. coreanus) and S. boulardii along with that of S. cerevisiae AB 972, which was used as a type strain for the yeast genome project. However, when PCR was carried out with the intron splice site primer, it resulted in the amplification of the SHY 111-specific DNA fragment which was about 200 bp in size. When PCR was carried out using the primer to test diversity of 40 isolated yeast strains, it was found that the PCR patterns were similar to each other except for the 200 bp bands derived from all the 10 strains from one Yakju, and 2 strains from another Yakju. These results suggest the strain identified as S. boulardii by the Automated Identification System to be a dominant strain for the fermentation of Korean traditional liquors.