• International Journal of Internet, Broadcasting and Communication
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• 제15권4호
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• pp.1-8
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• 2023

This paper analyzes the trends of identification proofing services(PIPSs) to identify and authenticate users online and proposes a method to improve PIPS based on alternative means of resident registration numbers in Korea. Digital identity proofing services play an important role in modern society, but there are some problems. Since they handle sensitive personal information, there is a risk of information leakage, hacking, or inappropriate access. Additionally, online service providers may incur additional costs by applying different PIPSs, which results in online service users bearing the costs. In particular, in these days of globalization, different PIPSs are being used in various countries, which can cause difficulties in international activities due to lack of global consistency. Overseas online PIPSs include expansion of biometric authentication, increase in mobile identity proofing, and distributed identity proofing using blockchain. This paper analyzes the trend of PIPSs that prove themselves when identifying users of online services in non-face-to-face overseas situations, and proposes improvements by comparing them with alternative means of Korean resident registration numbers. Through the proposed method, it will be possible to strengthen the safety of Korea's PIPS and expand the provision of more reliable identification services.

• Asian-Australasian Journal of Animal Sciences
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• 제18권6호
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• pp.868-872
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• 2005

Individual management of the animal is the first step towards reaching the goal of precision livestock farming that aids animal welfare. Accurate recognition of each individual animal is important for precise management. Electronic identification of cattle, usually referred to as RFID (Radio Frequency Identification), has many advantages for farm management. In practice, however, RFID implementations can cause several problems. Reading speed and distance must be optimized for specific applications. Image processing is more effective than RFID for the development of precision farming system in livestock. Therefore, the aim of this paper is to attempt the identification of cattle by using image processing. The majority of the research on the identification of cattle by using image processing has been for the black-and-white patterns of the Holstein. But, native Japanese and Korean cattle do not have a consistent pattern on the body, so that identification by pattern is impossible. This research aims to identify to Japanese black cattle, which does not have a black-white pattern on the body, by using image processing and a neural network algorithm. 12 Japanese black cattle were tested. Values of input parameter were calculated by using the face image values of 12 cows. The face was identified by the associate neural memory algorithm, and the algorithm was verified by the transformed face image, for example, of brightness, distortion, noise and angle. As a result, there was difference due to a transformation ratio of the brightness, distortion, noise, and angle. The algorithm could identify 100% in the range from -30 to +30 degrees of brightness, -20 to +40 degrees of distortion, 0 to 60% of noise and -20 to +30 degree of angle transformed images.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 3부
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• pp.172-177
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• 2008

생체 인식은 개인의 고유한 생체 정보를 획득하여 개인 식별에 이용하는 기술로, 그중 얼굴 인식은 사용자의 편의성과 비강제성이라는 장점이 있는 응용기술로 평가 받고 있다. 본 논문에서는 얼굴인식 기술동향을 살펴보고 얼굴 영역 추출, 특정 추출, 매칭을 포함한 시스템에 대해 논한다. 얼굴 영역 추출에는 얼굴 형판 정합 방법과 얼굴 요소의 검출에 의한 방법을, 특정 추출에서는 PCA 와 LDA 등의 방법을, 그리고 매칭을 통한 인증 단계에서는 최근접 분류기를 소개한다. 다양한 얼굴 인식 기법들이 제시됨에 따라 공인된 성능 평가 방법이 필요하게 되는데, 대용량 표준 얼굴 DE의 구축과 얼굴 인식 성능 평가 방법 개발의 필요성을 제시한다. 향후 얼굴인식 시스템에서는 조명, 자세, 표정의 변화를 어떻게 보정하여 인식 할 것인가 하는 것이 연구되어야 할 핵심 분야로서 3차원 얼굴 영상 복원 기술을 통한 해결방법을 살펴본다.

• 한국지능시스템학회논문지
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• 제22권2호
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• pp.168-173
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• 2012

본 논문은 얼굴인식 시스템 상에서 마스크를 착용한 변장이미지가 입력 감지될 경우 나머지 노출된 부분의 특징만을 가지고 가려진 사람의 신원을 추정하는 방법을 기술한다. 얼굴영역 검출 후에 마스크상단의 눈 주변 이미지만을 가지고 특징점 추출을 실시하여 등록된 얼굴 인증 데이터 베이스와의 특징점 비교를 통해 사람의 신원을 추정한다. 매칭에 쓰일 특징점 추출에는 조명에 강인하고 영상의 크기와 회전에도 변하지 않는 특성을 가진 SIFT(Scale Invariant Feature Transform) 알고리즘을 이용한다. 특징점 매칭을 통해 정확한 매칭률은 전체 실험결과를 통해 평가한다.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1494-1507
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• 2018

Intelligent human identification using face information has been the research hotspot ranging from Internet of Things (IoT) application, intelligent self-service bank, intelligent surveillance to public safety and intelligent access control. Since 2D face images are usually captured from a long distance in an unconstrained environment, to fully exploit this advantage and make human recognition appropriate for wider intelligent applications with higher security and convenience, the key difficulties here include gray scale change caused by illumination variance, occlusion caused by glasses, hair or scarf, self-occlusion and deformation caused by pose or expression variation. To conquer these, many solutions have been proposed. However, most of them only improve recognition performance under one influence factor, which still cannot meet the real face recognition scenario. In this paper we propose a multi-scale parallel convolutional neural network architecture to extract deep robust facial features with high discriminative ability. Abundant experiments are conducted on CMU-PIE, extended FERET and AR database. And the experiment results show that the proposed algorithm exhibits excellent discriminative ability compared with other existing algorithms.

• Asian Journal for Public Opinion Research
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• 제3권2호
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• pp.84-105
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• 2016

The instability of social norms on the Internet causes the diversity of social identification. Meanwhile, the anonymity of online social identity and the chaos of the role-playing among the interacting participants cause an ambiguity of identity recognition, which intensifies anxiety about interpersonal interaction. Methods that promote face-to-face interpersonal interaction through the reconstruction of the identification to the social system and intergroup trust is worth further research. Based on a telephone survey of urban residents in thirty-six cities in China (N=1080), the study focuses on the influence of Internet use on interpersonal interaction of urban residents and the mediation effect of social identification. The results show that Internet use has a negative effect on the interpersonal interactions of urban residents, and social identification plays a mediating effect between Internet use and interpersonal interaction. Implications of the results are discussed.

• 한국지능시스템학회논문지
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• 제24권4호
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• pp.349-354
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• 2014

지금까지 스마트 카드의 사용자 인증은 단말기에서 PIN(Personal Information Number)을 대조하는 MOT(Match On Terminal)방식으로 이루어져 왔다. 이러한 기존의 방법은 사용자의 망각이나 분실로 인해 PIN정보가 유출될 위험이 있으며, 단말기에서 사용자 정보를 대조하기 때문에 사용자 정보에 대한 불법적인 접근 가능성이 높다. 따라서, 본 논문은 PIN방식과 비교하여 현저히 분실과 망각 위험이 낮은 생체정보를 이용하는 MOC(Match On Card)방식 사용자 인증 방법을 제안한다. 이를 위해, 제한적인 저장 공간을 가지고 있는 스마트 카드에도 저장 할 수 있는 저용량의 얼굴 생체벡터를 구성하고 낮은 연산속도를 가진 스마트 카드에서 실시간으로 매칭 결과를 알아 낼 수 있는 단순한 매칭 알고리즘을 제안한다.

• Journal of Information Processing Systems
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• 제14권5호
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• pp.1075-1086
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• 2018

In this paper a cross-validation algorithm for training probabilistic neural networks (PNNs) is presented in order to be applied to automatic face identification. Actually, standard PNNs perform pretty well for small and medium sized databases but they suffer from serious problems when it comes to using them with large databases like those encountered in biometrics applications. To address this issue, we proposed in this work a new training algorithm for PNNs to reduce the hidden layer's size and avoid over-fitting at the same time. The proposed training algorithm generates networks with a smaller hidden layer which contains only representative examples in the training data set. Moreover, adding new classes or samples after training does not require retraining, which is one of the main characteristics of this solution. Results presented in this work show a great improvement both in the processing speed and generalization of the proposed classifier. This improvement is mainly caused by reducing significantly the size of the hidden layer.

• International journal of advanced smart convergence
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• 제9권3호
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• pp.246-252
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• 2020

Facial recognition is a biometric technology that is used in various fields such as user authentication and identification of human characteristics. Face recognition applications are practically used in various fields, but very few applications have been developed to improve the factory work environment. We implemented applications that uses face recognition to identify a specific employee in a factory .work environment and provide customized information for each employee. Factory workers need documents describing the work in order to do their assigned work. Factory managers can use our application to register documents needed for each worker, and workers can view the documents assigned to them. Each worker is identified using face recognition, and by tracking the worker's face during work, it is possible to know that the worker is in the workplace. In addition, as a mobile app for workers is provided, workers can view the contents using a tablet, and we have defined a simple communication protocol to exchange information between our applications. We demonstrated the applications in a factory work environment and found several improvements were required for practical use. We expect these results can be used to improve factory work environments.

• 한국컴퓨터정보학회논문지
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• 제26권2호
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• pp.19-25
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• 2021

본 논문에서는 비전 기술과 딥러닝 기반의 얼굴인식을 통해 실종자를 식별하는 방법을 제안하였다. 모바일 디바이스에서 전송된 원본 이미지에 대해 얼굴인식에 적합하도록 이미지를 전처리한 후, 얼굴인식의 정확도 향상을 위한 이미지 데이터 증식과 CNN 기반 얼굴학습 및 검증을 통해 실종자를 인식하였다. 본 논문의 구현 결과를 이용하여 가상의 실종자 이미지를 식별한 결과, 원본 데이터와 블러 처리한 데이터를 함께 학습한 모델의 성능이 가장 우수하게 나왔다. 또한 사전학습된 가중치를 사용한 학습 모델은 사용하지 않은 모델보다 높은 성능을 보였지만, 편향과 분산이 높게 나오는 한계를 확인할 수 있었다.