• Electronics and Telecommunications Trends
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• v.33 no.4
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• pp.43-53
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• 2018

As face recognition (FR) has been well studied over the past decades, FR technology has been applied to many real-world applications such as surveillance and biometric systems. However, in the real-world scenarios, FR performances have been known to be significantly degraded owing to variations in face images, such as the pose, illumination, and low-resolution. Recently, visual intelligence technology has been rapidly growing owing to advances in deep learning, which has also improved the FR performance. Furthermore, the FR performance based on deep learning has been reported to surpass the performance level of human perception. In this article, we discuss deep-learning based high-performance FR technologies in terms of representative deep-learning based FR architectures and recent FR algorithms robust to face image variations (i.e., pose-robust FR, illumination-robust FR, and video FR). In addition, we investigate big face image datasets widely adopted for performance evaluations of the most recent deep-learning based FR algorithms.

• The KIPS Transactions:PartB
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• v.8B no.2
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• pp.189-194
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• 2001

본 논문에서는 개인 식별을 위하여 복수 해상도 구조를 제시하였고 이 방법으로 구순문 인식을 구현하였다. 구순문 인식은 지문, 음성 패턴, 홍채 패턴과 얼굴 인식과 같은 신체적 특징에 비하여 상대적으로 연구가 많이 이루어지지 않은 신체적 특징이다. 구순문은 CCD 카메라를 이용할 경우 홍채나 얼굴 패턴 같은 다른 특징 요소와 연결하여 인식 시스템을 구축할 수 있는 장점을 가지고 있다. 구순문 인식을 위해 pattern kernels를 이용한 새로운 방법을 제시하였다. Pattern kernels는 여러 개의 local lip print mask들로 구성된 함수이며, lip print의 정보를 디지털 데이터로 전환시켜 준다. 복수 해상도를 가지는 인식 시스템은 단일 해상도의 시스템보다 더욱 신뢰적이며 인식률도 높다.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.4
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• pp.190-194
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• 2009

Iris recognition is a biometric technology which can identify a person using the iris pattern. Recently, using iris information is used in many fields such as access control and information security. But Perform complex operations to extract features of the iris. Because high-end hardware for real-time iris recognition is required. This paper is appropriate for the embedded environment using local gradient histogram embedded system with iris feature extraction methods based on USN(Ubiquitous Sensor Network). Experimental results show that the performance of proposed method is comparable to existing methods using Gabor transform noticeably improves recognition performance and it is noted that the processing time of the local gradient histogram transform is much faster than that of the existing method and rotation was also a strong attribute.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6133-6151
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• 2017

The field of periocular biometrics has gained wide attention as an alternative or supplemental means to conventional biometric traits such as the iris or the face. Periocular biometrics provide intermediate resolution between the iris and the face, which enables it to support both. We have developed a periocular recognition system by using uniform Multiscale Local Binary Pattern (uMLBP) and attribute features. The proposed system has been evaluated in terms of major factors that need to be considered on a mobile platform (e.g., distance and facial pose) to assess the feasibility of the use of periocular biometrics on mobile devices. Experimental results showed 98.7% of rank-1 identification accuracy on a subset of the Face Recognition Grand Challenge (FRGC) database, which is the best performance among similar studies.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1001-1007
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• 2020

In recent years, machine learning algorithms are continuously being used and expanded in various fields, such as facial recognition, signal processing, personal authentication, and stock prediction. In particular, various algorithms, such as deep learning, reinforcement learning, and Q-learning, are continuously being improved. Among these algorithms, the expansion of deep learning is rapidly changing. Nevertheless, machine learning algorithms have not yet been applied in several fields, such as personal authentication technology. This technology is an essential tool in the digital information era, walking recognition technology as promising biometrics, and technology for solving state-space problems. Therefore, algorithm technologies of deep learning, reinforcement learning, and Q-learning, which are typical machine learning algorithms in various fields, such as agricultural technology, personal authentication, wireless network, game, biometric recognition, and image recognition, are being improved and expanded in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.2087-2103
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• 2014

What is an ideal authentication method for smartphone banking services? And what are the critical elements to be considered when designing it? To provide valuable insight for these questions, this study investigates various authentication requirements to be considered in smartphone banking service with the aspect of security, convenience and cost. By applying Analytic Network Process (ANP), this study first analyzes priorities among the requirements and then draws an ideal authentication method for smartphone banking service. Moreover, a sensitivity analysis has been conducted by varying the relative importance of several requirements. The results from the judgment of 72 experts revealed that, although Korean government has obliged the use of Public Key certificate, OPT and biometric alternatives may prove to be more appropriate for the smartphone banking service. These results will contribute to the provision of more secured and convenient smartphone banking services.

• Smart Media Journal
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• v.9 no.2
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• pp.39-50
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• 2020

Derivation cryptographic keys from human biometrics opens a new promising research area when it can be used efficiently for not only verification or recognition tasks, but also symmetric-key based applications. Among existing biometric traits, face is considered as the most popular biometrics since facial features are informative and discriminative. In this paper, we present a comprehensive survey of Face-based key generation (FKGS). First, we summarize the trend of FKGS researches and sum up the methods which play important roles in the proposed key generation systems. Then we present the evaluation and the general performance analysis; from that, we give a discussion about the advantages and disadvantages of surveyed studies to clarify the fundamental requirements and the main challenges when implementing FKGS in practice. Finally, an outlook on future prospects is given.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.852-862
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• 2017

In this work a Discrete Cosine Transform (DCT)-based feature dimensionality reduced approach for fingerprint matching is proposed. The DCT is applied on a small region around the core point of fingerprint image. The performance of our proposed method is evaluated on a small database of Bologna University and two large databases of FVC2000. A dimensionally reduced feature vector is formed using only approximately 19%, 7%, and 6% DCT coefficients for the three databases from Bologna University and FVC2000, respectively. We compared the results of our proposed method with the discrete wavelet transform (DWT) method, the rotated wavelet filters (RWFs) method, and a combination of DWT+RWF and DWT+(HL+LH) subbands of RWF. The proposed method reduces the false acceptance rate from approximately 18% to 4% on DB1 (Database of Bologna University), approximately 29% to 16% on DB2 (FVC2000), and approximately 26% to 17% on DB3 (FVC2000) over the DWT based feature extraction method.

• Journal of the Optical Society of Korea
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• v.19 no.3
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• pp.303-310
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• 2015

An image-space telecentric lens for an intra-oral 3D scanner was designed and fabricated for dental application. Since a telecentric function can provide the same results regardless of image plane position, it helps to realize a more accurate image for an intra-oral scanner. The performance of the designed lens meets the required properties for HD resolution. In particular, lateral color is corrected within 1 pixel. This system achieves depth of focus of more than 3 mm. For user convenience, the developed system consists of a prism part and an imaging part. Both parts are optimized to reduce the front size and weight of the system. In order to make the parallax sights, parallax angle was determined to be 8 degrees between two optical systems.

• Annual Conference of KIPS
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• 2004.05a
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• pp.1115-1118
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• 2004

최근 자바카드 기술이 기존의 스마트카드 기술의 문제점들을 해결할 수 있는 새로운 대안으로 등장하고 있고, 카드 소유자의 사용자 인증은 자바카드의 활용을 위해 필수적인 부분이다. 이에 본 논문에서는 스마트카드 상에서 자바카드 실행 환경을 위한 바이오메트릭 API의 구현을 통해 사용자 인증 시스템 구축 방법에 관하여 기술하였다. 본 논문은 먼저 자바카드에 관한 기술 동향 및 분석 등을 기술하였고, 자바카드 바이오메트릭 API에 관하여 설명하였다. 또한, 구현된 바이오메트릭 API를 사용하여 기존의 스마트카드에서 사용되었던 다양한 인증 수단 외에 다양한 생체 정보들을 이용하여 사용자 인증을 제공할 수 있도록 하였다.