• Title/Summary/Keyword: Face identification

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De-Identified Face Image Generation within Face Verification for Privacy Protection (프라이버시 보호를 위한 얼굴 인증이 가능한 비식별화 얼굴 이미지 생성 연구)

  • Jung-jae Lee;Hyun-sik Na;To-min Ok;Dae-seon Choi
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.2
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    • pp.201-210
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    • 2023
  • Deep learning-based face verificattion model show high performance and are used in many fields, but there is a possibility the user's face image may be leaked in the process of inputting the face image to the model. Althoughde-identification technology exists as a method for minimizing the exposure of face features, there is a problemin that verification performance decreases when the existing technology is applied. In this paper, after combining the face features of other person, a de-identified face image is created through StyleGAN. In addition, we propose a method of optimizingthe combining ratio of features according to the face verification model using HopSkipJumpAttack. We visualize the images generated by the proposed method to check the de-identification performance, and evaluate the ability to maintain the performance of the face verification model through experiments. That is, face verification can be performed using the de-identified image generated through the proposed method, and leakage of face personal information can be prevented.

Face Recognition and Notification System for Visually Impaired People (시각장애인을 위한 얼굴 인식 및 알림 시스템)

  • Jin, Yongsik;Lee, Minho
    • IEMEK Journal of Embedded Systems and Applications
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    • v.12 no.1
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    • pp.35-41
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    • 2017
  • We propose a face recognition and notification system that can transform visual face information into tactile signals in order to help visually impaired people. The proposed system consists of a glasses type camera, a mobile computer and an electronic cane. The glasses type camera captures the frontal view of the user, and sends this image to mobile computer. The mobile computer starts to search for human's face in the image when obstacles are detected by ultrasonic sensors. In a case that human's face is detected, the mobile computer identifies detected face. At this time, Adaboost and compressive sensing are used as a detector and a classifier, respectively. After the identification procedures of the detected face, the identified face information is sent to controller attached to a cane using a Bluetooth communication. The controller generates motor control signals using Pulse Width Modulation (PWM) according to the recognized face labels. The vibration motor generates vibration patterns to inform the visually impaired person of the face recognition result. The experimental results of face recognition and notification system show that proposed system is helpful for visually impaired people by providing person identification results in front of him/her.

RFID Tag Protection using Face Feature

  • Park, Sung-Hyun;Rhee, Sang-Burm
    • Journal of the Semiconductor & Display Technology
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    • v.6 no.2 s.19
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    • pp.59-63
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    • 2007
  • Radio Frequency Identification (RFID) is a common term for technologies using micro chips that are able to communicate over short-range radio and that can be used for identifying physical objects. RFID technology already has several application areas and more are being envisioned all the time. While it has the potential of becoming a really ubiquitous part of the information society over time, there are many security and privacy concerns related to RFID that need to be solved. This paper proposes a method which could protect private information and ensure RFID's identification effectively storing face feature information on RFID tag. This method improved linear discriminant analysis has reduced the dimension of feature information which has large size of data. Therefore, face feature information can be stored in small memory field of RFID tag. The proposed algorithm in comparison with other previous methods shows better stability and elevated detection rate and also can be applied to the entrance control management system, digital identification card and others.

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Human Face Identification using KL Transform and Neural Networks (KL 변환과 신경망을 이용한 개인 얼굴 식별)

  • Kim, Yong-Joo;Ji, Seung-Hwan;Yoo, Jae-Hyung;Kim, Jung-Hwan;Park, Mignon
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.1
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    • pp.68-75
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    • 1999
  • Machine recognition of faces from still and video images is emerging as an active research area spanning several disciplines such as image processing, pattern recognition, computer vision and neural networks. In addition, human face identification has numerous applications such as human interface based systems and real-time video systems of surveillance and security. In this paper, we propose an algorithm that can identify a particular individual face. We consider human face identification system in color space, which hasn't often considered in conventional in conventional methods. In order to make the algorithm insensitive to luminance, we convert the conventional RGB coordinates into normalized CIE coordinates. The normalized-CIE-based facial images are KL-transformed. The transformed data are used as the input of multi-layered neural network and the network are trained using error-backpropagation methods. Finally, we verify the system performance of the proposed algorithm by experiments.

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A Study on Big Data Based Non-Face-to-Face Identity Proofing Technology (빅데이터 기반 비대면 본인확인 기술에 대한 연구)

  • Jung, Kwansoo;Yeom, Hee Gyun;Choi, Daeseon
    • KIPS Transactions on Computer and Communication Systems
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    • v.6 no.10
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    • pp.421-428
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    • 2017
  • The need for various approaches to non-face-to-face identification technology for registering and authenticating users online is being required because of the growth of online financial services and the rapid development of financial technology. In general, non-face-to-face approaches can be exposed to a greater number of threats than face-to-face approaches. Therefore, identification policies and technologies to verify users by using various factors and channels are being studied in order to complement the risks and to be more reliable non-face-to-face identification methods. One of these new approaches is to collect and verify a large number of personal information of user. Therefore, we propose a big-data based non-face-to-face Identity Proofing method that verifies identity on online based on various and large amount of information of user. The proposed method also provides an identification information management scheme that collects and verifies only the user information required for the identity verification level required by the service. In addition, we propose an identity information sharing model that can provide the information to other service providers so that user can reuse verified identity information. Finally, we prove by implementing a system that verifies and manages only the identity assurance level required by the service through the enhanced user verification in the non-face-to-face identity proofing process.

Vehicle Face Re-identification Based on Nonnegative Matrix Factorization with Time Difference Constraint

  • Ma, Na;Wen, Tingxin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.6
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    • pp.2098-2114
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    • 2021
  • Light intensity variation is one of the key factors which affect the accuracy of vehicle face re-identification, so in order to improve the robustness of vehicle face features to light intensity variation, a Nonnegative Matrix Factorization model with the constraint of image acquisition time difference is proposed. First, the original features vectors of all pairs of positive samples which are used for training are placed in two original feature matrices respectively, where the same columns of the two matrices represent the same vehicle; Then, the new features obtained after decomposition are divided into stable and variable features proportionally, where the constraints of intra-class similarity and inter-class difference are imposed on the stable feature, and the constraint of image acquisition time difference is imposed on the variable feature; At last, vehicle face matching is achieved through calculating the cosine distance of stable features. Experimental results show that the average False Reject Rate and the average False Accept Rate of the proposed algorithm can be reduced to 0.14 and 0.11 respectively on five different datasets, and even sometimes under the large difference of light intensities, the vehicle face image can be still recognized accurately, which verifies that the extracted features have good robustness to light variation.

A Study on the Improvement of User Identification of Non-Face-to-Face Financial Transactions with Messenger Phishing Case (비대면 금융거래 사용자 확인 개선방안 연구 - 메신저피싱 사례를 중심으로)

  • Eun Bi Kim;Ik Rae Jeong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.2
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    • pp.353-362
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    • 2023
  • Messenger phishing, communications frauds crime, exploits remote control of smartphones and non-face-to-face financial transactions, causing property damage due to money transfers, as well as account opening and loans in the name of victims. Such financial accidents may be careless of victims, but the current messenger phishing criminal method is intelligent and can be seen as digging into loopholes in the non-face-to-face user verification process. In this paper we analyze how messenger phishing uses loopholes in user identification procedures in non-face-to-face financial transactions. Through experiments, it is suggested to improve the non-face-to-face verification process for safer financial transactions.

Face Identification Using Topological Relationship between Lips′ Axes and Eyes (입술의 기울기특징과 눈과의 위상관계를 이용한 얼굴확인기법)

  • 김민석;한헌수
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2028-2031
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    • 2003
  • This paper proposes a face identification algorithm, robust on lighting condition and complex background. The proposed method estimates facial area under bad light condition by expanding face color boundaries and then finds a lip using the templates for lips. Then the eyes are found using their topological relationship with the long and short axes of lip area. The experimental results have shown that the proposed algorithm is robust on lighting conditions and complex background.

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A Study on Face Recognition Using Diretional Face Shape and SOFM (방향성 얼굴형상과 SOFM을 이용한 얼굴 인식에 관한 연구)

  • Kim, Seung-Jae;Lee, Jung-Jae
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.6
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    • pp.109-116
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    • 2019
  • This study proposed a robust detection algorithm. It detects face more stably with respect to changes in light and rotation for the identification of a face shape. Also it satisfies both efficiency of calculation and the function of detection. The algorithm proposed segmented the face area through pre-processing using a face shape as input information in an environment with a single camera and then identified the shape using a Self Organized Feature Map(SOFM). However, as it is not easy to exactly recognize a face area which is sensitive to light, it has a large degree of freedom, and there is a large error bound, to enhance the identification rate, rotation information on the face shape was made into a database and then a principal component analysis was conducted. Also, as there were fewer calculations due to the fewer dimensions, the time for real-time identification could be decreased.

Fusion algorithm for Integrated Face and Gait Identification (얼굴과 발걸음을 결합한 인식)

  • Nizami, Imran Fareed;Hong, Sug-Jun;Lee, Hee-Sung;Ann, Toh-Kar;Kim, Eun-Tai;Park, Mig-Non
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.11a
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    • pp.15-18
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    • 2007
  • Identification of humans from multiple view points is an important task for surveillance and security purposes. For optimal performance the system should use the maximum information available from sensors. Multimodal biometric systems are capable of utilizing more than one physiological or behavioral characteristic for enrollment, verification, or identification. Since gait alone is not yet established as a very distinctive feature, this paper presents an approach to fuse face and gait for identification. In this paper we will use the single camera case i.e. both the face and gait recognition is done using the same set of images captured by a single camera. The aim of this paper is to improve the performance of the system by utilizing the maximum amount of information available in the images. Fusion is considered at decision level. The proposed algorithm is tested on the NLPR database.

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