• 대한의생명과학회지
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• 제24권4호
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• pp.292-304
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• 2018

Microbes is becoming increasingly forensic possibility as a consequence of advances in massive parallel sequencing (MPS) and bioinformatics. Human DNA typing is the best identifier, but it is not always possible to extract a full DNA profile namely its degradation and low copy number, and it may have limitations for identical twins. To overcome these unsatisfactory limitations, forensic potential for bacteria found in evidence could be used to differentiate individuals. Prokaryotic cells have a cell wall that better protects the bacterial nucleoid compared to the cell membrane of eukaryotic cells. Humans have an extremely diverse microbiome that may prove useful in determining human identity and may even be possible to link the microbes to the person responsible for them. Microbial composition within the human microbiome varies across individuals. Therefore, MPS of human microbiome could be used to identify biological samples from the different individuals, specifically for twins and other cases where standard DNA typing doses not provide satisfactory results due to degradation of human DNA. Microbial forensics is a new discipline combining forensic science and microbiology, which can not to replace current STR analysis methods used for human identification but to be complementary. Among the fields of microbial forensics, this paper will briefly describe information on the current status of microbiome research such as metagenomic code, salivary microbiome, pubic hair microbiome, microbes as indicators of body fluids, soils microbes as forensic indicator, and review microbial forensics as the feasibility of microbiome-based human identification.

• ETRI Journal
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• 제25권5호
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• pp.401-406
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• 2003

A biometric system determines the identity of a person by measuring physical features that can distinguish that person from others. Since biometric features have many variations and can be easily corrupted by noises and deformations, it is necessary to apply machine learning techniques to treat the data. When applying the conventional machine learning methods in designing a specific biometric system, however, one first runs into the difficulty of collecting sufficient data for each person to be registered to the system. In addition, there can be an almost infinite number of variations of non-registered data. Therefore, it is difficult to analyze and predict the distributional properties of real data that are essential for the system to deal with in practical applications. These difficulties require a new framework of identification and verification that is appropriate and efficient for the specific situations of biometric systems. As a preliminary solution, this paper proposes a simple but theoretically well-defined method based on a statistical test theory. Our computational experiments on real-world data show that the proposed method has potential for coping with the actual difficulties in biometrics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4456-4475
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• 2021

The system for re-identifying persons is used to find and verify the persons crossing through different spots using various cameras. Much research has been done to re-identify the person by utilising features with deep-learned or hand-crafted information. Deep learning techniques segregate and analyse the features of their layers in various forms, and the output is complex feature vectors. This paper proposes a distinctive framework called Integrated Level Feature Pattern (ILFP) framework, which integrates local and global features. A new deep learning architecture named modified XceptionNet (m-XceptionNet) is also proposed in this work, which extracts the global features effectively with lesser complexity. The proposed framework gives better performance in Rank1 metric for Market1501 (96.15%), CUHK03 (82.29%) and the newly created NEC01 (96.66%) datasets than the existing works. The mean Average Precision (mAP) calculated using the proposed framework gives 92%, 85% and 98%, respectively, for the same datasets.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 G
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• pp.2249-2251
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• 1998

This paper presents a lip print recognition by the pattern kernels for a personal identification. A lip print recognition is developed less than the other physical attribute that is a fingerprint, a voice pattern, a retinal blood-vessel pattern, or a facial recognition. A new method by the pattern kernels is pro for a lip print recognition. The pattern kerne function consisted of some local lip print p masks. This function identifies the lip print known person or an unknown person. The results show that the proposed algorithm the pattern kernels can the efficiently realized.

• 제어로봇시스템학회논문지
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• 제15권5호
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• pp.511-518
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• 2009

The surveillance robot has been an important component in the field of service robot industry. In the surveillance robot technology, one of the most important technology is to identify a person. In this paper, we propose a gait recognition method based on contourlet and fuzzy LDA (Linear Discriminant Analysis) for surveillance robots. After decomposing a gait image into directional subband images by contourlet, features are obtained in each subband by the fuzzy LDA. The final gait recognition is performed by a fusion technique that effectively combines similarities calculated respectively in each local subband. To show the effectiveness of the proposed algorithm, various experiments are performed for CBNU and NLPR DB datasets. From these, we obtained better classification rates in comparison with the result produced by previous methods.

• 정보와 통신
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• 제25권10호
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• pp.18-24
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• 2008

RFID(Radio Frequency Identification) 기술은 사물에 전자 태그를 부착하여 무선 인터페이스를 통해 사물의 정보를 자동으로 취득 할 수 있는 기술이다. 물류의 재고관리나 자동화 처리를 위해 주로 사용되었으나 최근에는 Cellular phone, PDA등 휴대용기기 에 RFID리더가 탑재되어 기존의 응용 이외에 다양한 서비스를 만들어 내려는 시도들이 나타나고 있다[1],[2]. 이는 궁극적으로는 모든 사물에 컴퓨팅 및 통신 기능을 부여하여 언제, 어디서, 무엇이든 통신이 가능한 환경을 구현함으로써 이제까지 사람 중심(Person to Person)에서 사물 중심(Machine to Machine) 정보화 사회로의 새로운 변화 시도이며 RFID기술은 진정한 Ubiquitous세상이 만들어지기 위한 주요 기술로서 지속적으로 발전되고 적용되어야 할 기술임이 분명하다. 이러한 사회적인 요구에 만족하기 위해서 RFID 기술도 변화하고 있고 새로운 기술적 이슈들이 나타나게 되었다. 본고에서는 RFID 기술의 변화를 알아보고, 특히 UHF 대역 RFID 리더가 Cellular phone에 내장되기 위해 소형화 및 저전력화가 되면서 발생하는 문제와 이의 해결방안을 살펴보고자 한다.

• International Journal of Computer Science & Network Security
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• 제24권3호
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• pp.107-112
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• 2024

Nowadays the deadly virus famous as COVID-19 spread all over the world starts from the Wuhan China in 2019. This disease COVID-19 Virus effect millions of people in very short time. There are so many symptoms of COVID19 perhaps the Identification of a person infected with COVID-19 virus is really a difficult task. Moreover it's a challenging task to identify whether a person or individual have covid test positive or negative. We are developing a framework in which we used machine learning techniques..The proposed method uses DecisionTree, KNearestNeighbors, GaussianNB, LogisticRegression, BernoulliNB , RandomForest , Machine Learning methods as the classifier for diagnosis of covid ,however, 5-fold and 10-fold cross-validations were applied through the classification process. The experimental results showed that the best accuracy obtained from Decision Tree classifiers. The data preprocessing techniques have been applied for improving the classification performance. Recall, accuracy, precision, and F-score metrics were used to evaluate the classification performance. In future we will improve model accuracy more than we achieved now that is 93 percent by applying different techniques

• 문화기술의 융합
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• 제2권4호
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• pp.71-76
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• 2016

본 논문에서는 미국, 영국, 일본, 중국, 한국의 비식별화 정책비교를 통하여 향후 비식별화 규제의 방향과 빅데이터 산업 활성화 방안을 제시한다. 비식별화 기술과 적정성 평가기준을 효율적으로 활용할 경우, 개인의 사생활을 침해하지 않고 개인정보보호법 제약을 피하면서 개인정보를 산업적으로 활용하여 서비스와 기술을 발전시킬 수 있다. 역작용으로는 비식별화 된 데이터들의 집합체로서 개인을 재식별 할 수 있는 재식별화 문제가 발생할 수 있다. 비즈니스 관점에서는 빅데이터 산업이 활성화되기 위해서 규제의 해소와 빅데이터 활용 등을 위한 제도완화가 필요하며 정보보호 측면에서의 보안강화 조치와 제도정비도 필요하다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.187-189
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• 2004

This paper presents the system widely used for extraction of human body recognition system in the field of bio-metric identification. The Human body recognition system is used in many fields. This biological is appled to the human recognition in banking and the access control with security. The important algorithm of the identification software usese hand lines and hand shape geometry. We used the simple algorithm and recognizing the person by their hand image from the input camera. The geometrical characteristics in hand shape such as length of finger to whole hand length thickness of finger to length, etc are used.

• 한국멀티미디어학회논문지
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• 제10권12호
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• pp.1577-1584
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• 2007

Fingerprint verification is being adopted widely to provide positive identification with a high degree of confidence in all practical areas. This popular usage requires reliable methods for matching of these patterns. To meet the latest expectations, the paper presents a pair wise distance histogram method for fingerprint matching. Here, we introduced a randomized algorithm which exploits pair wise distances between the pairs of minutiae, as a basic feature for match. The method undergoes two steps for completion i.e. first it performs the matching locally then global matching parameters are calculated in second step. The proposed method is robust to common problems that fingerprint matching faces, such as scaling, rotation, translational changes and missing points etc. The paper includes the test of algorithm on various randomly generated minutiae and real fingerprints as well. The results of the tests resemble qualities and utility of method in related field.