• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.280-286
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• 2022

Facial recognition system is a biometric manipulation. Its applicability is simpler, and its work range is broader than fingerprints, iris scans, signatures, etc. The system utilizes two technologies, such as face detection and recognition. This study aims to develop a facial recognition system to recognize person's faces. Facial recognition system can map facial characteristics from photos or videos and compare the information with a given facial database to find a match, which helps identify a face. The proposed system can assist in face recognition. The developed system records several images, processes recorded images, checks for any match in the database, and returns the result. The developed technology can recognize multiple faces in live recordings.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.1
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• pp.54-62
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• 2014

The Air and Space Interoperability Council (ASIC) has adopted the European Defence Agency (EDA) process for inter-regulatory military airworthiness authority recognition. However, there are gaps in the application of this process to nations outside of the European Union. This paper proposes a model that can effectively map diverse technical airworthiness regulatory frameworks. This model, referred to as the Product-Behaviour-Process (PBP) Bow-Tie model, provides the systematic structure needed to represent and compare regulatory frameworks. The PBP Bow-Tie model identifies key points of difference that need to be addressed, during inter-agency recognition between the two regulatory authorities. With the intention to adopt global use of the EDA process, the proposed PBP Bow-Tie model can be used as a basis for the successful recognition of regulatory frameworks outside of the European Union. Iris plots produced from the implementation of this model are presented, and proposed as a suitable means of illustrating the outcome of an assessment, and of supporting the comparisons of results. A comparative analysis of the Australian Defence Force and New Zealand Defence Force airworthiness regulatory frameworks is used as a case study. The case study clearly illustrates the effectiveness of the model in discerning regulatory framework differences; moreover, it has offered an opportunity to explore the limitations of the Iris plot.

• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.11-19
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• 2016

The personal identification based on the biometrics has emerged as one of the new trend. This study attempted to explore and examine the user recognition in the use of the personal identification based on the biometrics in the respect of self-efficacy, trustiness, security, and safety alongside the effect of the recognition on the future use intention through survey. The result of this study demonstrated the effect on the use intention of the perceived trustiness and ease of the fingerprint identification, perceived ease of the iris identification and the perceived trustiness of the vein identification. The result of this study is expected to suggest direction on the application of the biometrics considering user recognition.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.3
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• pp.14-24
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• 1996

A fuzzy classifier which needs various analyses of features using genetic algorithms is proposed. The fuzzy classifier has a simple structure, which contains a classification part based on fuzzy logic theory and a rule generation ation padptu sing genetic algorithms. The rule generation part determines optimal fuzzy membership functions and inclusior~ or exclusion of each feature in fuzzy classification rules. We analyzed recognition rate of a specific object, then added finer features repetitively, if necessary, to the object which has large misclassification rate. And we introduce repetitive analyses method for the minimum size of string and population, and for the improvement of recognition rates. This classifier is applied to three examples of the classification of iris data, the discrimination of thyroid gland cancer cells and the recognition of confusing handwritten and printed numerals. In the recognition of confusing handwritten and printed numerals, each sample numeral is classified into one of the groups which are divided according to the sample structure. The fuzzy classifier proposed in this paper has recognition rates of 98. 67% for iris data, 98.25% for thyroid gland cancer cells and 96.3% for confusing handwritten and printed numeral!;.

• The KIPS Transactions:PartB
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• v.8B no.2
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• pp.183-188
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• 2001

이 논문은 눈의 형태에 대한 정보를 이용하여 눈동자를 효과적으로 찾는 방법과 얼굴 특성을 반영하는 평가함수를 이용하여 눈동자, 입의 위치와 같은 얼굴 특징들을 인식하는 방법을 제안하였다. 색 정보를 이용하여 입술과 얼굴 영역을 추출하고 눈동자와 흰자위간의 명도 차를 이용하는 함수를 사용하여 눈동자를 인식하였다. 마지막으로 얼굴 특성을 반영하느 평가함수를 정의하고 이를 이용하여 최종적인 얼굴과 눈, 입을 인식하였다. 제안한 방법을 사용하여 여러 영상들에 대해 실험하여 좋은 결과를 얻었다.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1385-1392
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• 2013

There is a variety of researches about recognition system using biometric data these days. In this study, we propose a new algorithm, uses simultaneous equation that made of the edge of objects, to segment an iris region without threshold values from an anterior eye image. The algorithm attempts to find a center area through calculated outskirts information of an iris, and decides the area where the most points are accumulated. To verify the proposed algorithm, we conducted comparative experiments to Hough transform and Daugman's method, based on 50 images anterior eye images. It was found that proposed algorithm is 5 and 75 times faster than on each algorithm, and showed high accuracy of detecting a center point (95.36%) more than Hough transform (92.43%). In foreseeable future, this study is expected to useful application in diverse department of human's life, such as, identification system using an iris, diagnosis a disease using an anterior image.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.3
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• pp.565-577
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• 2019

In recent years, biometric authentication has been used for various applications. Since biometric features are unchangeable and cannot be revoked unlike other personal information, there is increasing concern about leakage of biometric information. Recently, Jin et al. proposed a new cancelable biometric scheme, called "Index-of-Max" (IoM) to protect fingerprint template. The authors presented two realizations, namely, Gaussian random projection-based and uniformly random permutation-based hashing schemes. They also showed that their schemes can provide high accuracy, guarantee the security against recently presented privacy attacks, and satisfy some criteria of cancelable biometrics. However, the authors did not provide experimental results for other biometric features (e.g. finger-vein, iris). In this paper, we present the results of applying Jin et al.'s scheme to iris data. To do this, we propose a new method for processing iris data into a suitable form applicable to the Jin et al.'s scheme. Our experimental results show that it can guarantee favorable accuracy performance compared to the previous schemes. We also show that our scheme satisfies cancelable biometrics criteria and robustness to security and privacy attacks demonstrated in the Jin et al.'s work.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.397-401
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• 1997

본 논문은 신경회로망과 Gabor변환을 홍채인식에 대한 연구이다. 현재 재발되고 있는 신원확인을 위한 여러 가지 인식 시스템 중 홍채인식의 특성과 비교우위적 장점을 소개하고, LVQ 신경회로망을 효과적인 초기화 방법과 Gabor변환을 이용한 홍채테이터의 특징추출에 대하여 논한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.299-301
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• 2005

본 연구는 생체정보를 이용하여 개인을 인증하고 확인하기 위한 방법으로 기존 단일 생체인식 기법의 단점을 보완하기 위해 홍채와 얼굴을 이용한 다중생체인식(Multi-Modal Biometrics Recognition)기법을 연구하였다. 중국 홍채 데이터베이스 CASIA(Chinese Academy of Science)에 Gabor Wavelet과 FLDA(Fuzzy Linear Discriminant Analysis)를 사용하여 특징벡터를 획득하였으며, FERET(FERET(Face Recognition Technology) 얼굴영상데이터를 사용하여 FERET 연구에서 매우 우수한 성능을 보인 EBGM알고리듬으로 특징벡터를 획득하였다. 이로부터 얻어진 두 score 값에 대하여 다양한 균등화 과정을 시도해 보았으며, 등록자와 침입자를 구분하기 위한 Fusion Algorithm으로 Bayesian Classifier, Support vector machine, Fisher's linear discriminant를 사용하였다. 또한, 널리 사용되는 방법 중 Weighted Summation을 이용하여 다중생체인식의 성능을 비교해 보았다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.1002-1003
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• 2019

Face recognition is an extensively researched area of computer vision. Visible, infrared, thermal, and 3D modalities have been used against various challenges of face recognition such as illumination, pose, expression, partial information, and disguise. In this paper we present a multi-modal approach to face recognition using convolutional neural networks. We use visible and thermal face images as two separate inputs to a multi-input deep learning network for face recognition. The experiments are performed on IRIS visible and thermal face database and high face verification rates are achieved.