• Title/Summary/Keyword: 핑거 프린트

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A Restoration Method for Geometric Distortions to Improve Scanned Books Identification (스캔 도서 식별 성능 향상을 위한 기하하적 왜곡 복원 방법)

  • Kim, Doyoung;Lee, Sang-Hoon;Jadhav, Sagar;Lee, Sanghoon
    • Journal of Broadcast Engineering
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    • v.20 no.3
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    • pp.379-387
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    • 2015
  • In recent years, copyright violations from illegal copying and distribution of e-comic contents have become an important issue. Fingerprinting techniques have been emerged to provide a fast and reliable identification method of identifying e-comic contents. When illegally scanned or camera captured comic contents are distributed, they suffer from distortions. So the fingerprint differs from the original version. This paper presents a restoration framework for correcting geometric distortions in distorted comics to improve the comic content identification.

Wi-Fi Fingerprint-based Indoor Movement Route Data Generation Method (Wi-Fi 핑거프린트 기반 실내 이동 경로 데이터 생성 방법)

  • Yoon, Chang-Pyo;Hwang, Chi-Gon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.458-459
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    • 2021
  • Recently, researches using deep learning technology based on Wi-Fi fingerprints have been conducted for accurate services in indoor location-based services. Among the deep learning models, an RNN model that can store information from the past can store continuous movements in indoor positioning, thereby reducing positioning errors. At this time, continuous sequential data is required as training data. However, since Wi-Fi fingerprint data is generally managed only with signals for a specific location, it is inappropriate to use it as training data for an RNN model. This paper proposes a path generation method through prediction of a moving path based on Wi-Fi fingerprint data extended to region data through clustering to generate sequential input data of the RNN model.

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Clustering Method for Classifying Signal Regions Based on Wi-Fi Fingerprint (Wi-Fi 핑거프린트 기반 신호 영역 구분을 위한 클러스터링 방법)

  • Yoon, Chang-Pyo;Yun, Dai Yeol;Hwang, Chi-Gon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.456-457
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    • 2021
  • Recently, in order to more accurately provide indoor location-based services, technologies using Wi-Fi fingerprints and deep learning are being studied. Among the deep learning models, an RNN model that can store information from the past can store continuous movements in indoor positioning, thereby reducing positioning errors. When using an RNN model for indoor positioning, the collected training data must be continuous sequential data. However, the Wi-Fi fingerprint data collected to determine specific location information cannot be used as training data for an RNN model because only RSSI for a specific location is recorded. This paper proposes a region clustering technique for sequential input data generation of RNN models based on Wi-Fi fingerprint data.

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Security Analysis and Improvement of an Anonymous Asymmetric Fingerprinting Scheme with Trusted Third Party (익명적 비대칭 핑거프린팅 기법의 보안 취약성 분석 및 개선 방안)

  • Kwon, Sae-Ran
    • Journal of KIISE:Computer Systems and Theory
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    • v.36 no.5
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    • pp.396-403
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    • 2009
  • An anonymous asymmetric fingerprinting protocol combined with watermarking techniques, is one of the copyright protection technologies keeping both right of a seller and that of a buyer, where a seller and an anonymous buyer perform such a protocol that employs various cryptographic tools in order that the seller does not know the exact watermarked copy that the buyer receives, while inserting an invisible non-removable fingerprint i.e., each different unique watermark, into each copy of the digital content to be sold. In such a protocol innocent buyers are kept anonymous during transactions, however, the unlawful reseller is unambiguously identified with a real identity as a copyright violator. In 2007, Yong and Lee proposed an anonymous asymmetric fingerprinting scheme with trusted third party. In this paper we point out the weakness of their scheme such as: the buyer with intention can remove the fingerprint in the watermarked content, because he/she can decrypt the encrypted fingerprint with a symmetric key using man-in-the-middle-attack; a real identity of a buyer can be revealed to the seller through the identification process even though he/she is honest. Furthermore, we propose an improved secure and efficient anonymous asymmetric fingerprinting scheme which enables to reduce the number of communication between the participants.

An indoor localization approach using RSSI and LQI based on IEEE 802.15.4 (IEEE 802.15.4기반 RSSI와 LQI를 이용한 실내 위치추정 기법)

  • Kim, Jung-Ha;Kim, Hyun-Jun;Kim, Jong-Su;Lee, Sung-Geun;Seo, Dong-Hoan
    • Journal of Advanced Marine Engineering and Technology
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    • v.38 no.1
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    • pp.92-98
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    • 2014
  • Recently, Fingerprint approach using RSSI based on WLAN has been many studied in order to construct low-cost indoor localization systems. Because this technique is relatively evaluated non-precise positioning technique compared with the positioning of Ultra-Wide-Band(UWB), the performance of the Fingerprint based on WLAN should be continuously improved to implement various indoor location. Therefore, this paper presents a Fingerprint approach which can improve the performance of localization by using RSSI and LQI contained IEEE 802.15.4 standard. The advantages of these techniques are that the characteristics of each location is created more clearly by utilizing RSSI and LQI and Fingerprint technique is improved by using the modified Euclidean distance method. The experimental results which are applied in NLOS indoor environment with various obstacles show that the accuracy of localization is improved to 22% compared to conventional Fingerprint.

Wireless LAN Based Indoor Positioning Using Received Signal Fingerprint and Propagation Prediction Model (수신 신호 핑거프린트와 전파 예측 모델을 이용한 무선랜 기반 실내 위치추정)

  • Kim, Hyunsu;Bae, Jimin;Choi, Jihoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38A no.12
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    • pp.1021-1029
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    • 2013
  • In this paper, we propose a new indoor location estimation method which combines the fingerprint technique with the propagation prediction model. The wireless LAN (WLAN) access points (APs) deployed indoors are divided into public APs and private APs. While the fingerprint method can be easily used to public APs usually installed in fixed location, it is difficult to apply the fingerprint scheme to private APs whose location can be freely changed. In the proposed approach, the accuracy of user location estimation is improved by simultaneously utilizing public and private APs. Specifically, the fingerprint method is used to the received signals from public APs and the propagation prediction model is employed to the signals from private APs. The performance of the proposed method is compared with that of conventional indoor location estimation schemes through measurements and numerical simulations in WLAN environments.

Automatic Music Summarization Method by using the Bit Error Rate of the Audio Fingerprint and a System thereof (오디오 핑거프린트의 비트에러율을 이용한 자동 음악 요약 기법 및 시스템)

  • Kim, Minseong;Park, Mansoo;Kim, Hoirin
    • Journal of Korea Multimedia Society
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    • v.16 no.4
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    • pp.453-463
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    • 2013
  • In this paper, we present an effective method and a system for the music summarization which automatically extract the chorus portion of a piece of music. A music summary technology is very useful for browsing a song or generating a sample music for an online music service. To develop the solution, conventional automatic music summarization methods use a 2-dimensional similarity matrix, statistical models, or clustering techniques. But our proposed method extracts the music summary by calculating BER(Bit Error Rate) between audio fingerprint blocks which are extracted from a song. But we could directly use an enormous audio fingerprint database which was already saved for a music retrieval solution. This shows the possibility of developing a various of new algorithms and solutions using the audio fingerprint database. In addition, experiments show that the proposed method captures the chorus of a song more effectively than a conventional method.

Wi-Fi Fingerprint Location Estimation System Based on Reliability (신뢰도 기반 Wi-Fi 핑거프린트 위치 추정 시스템)

  • Son, Sanghyun;Park, Youngjoon;Kim, Beomjun;Baek, Yunju
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38C no.6
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    • pp.531-539
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    • 2013
  • Fingerprinting technique uses the radio signal strength measured reference locations is typically used, although there are many Wi-Fi based location tracking techniques. However, it needs numerous reference locations for precision and accuracy. This paper the analyzes problems of previous techniques and proposes a fingerprinting system using reliability based on a signal strength map. The system collects the signal strength data from a number of reference locations designated by the developer. And then it generates path-loss models to one of the access points for each reference location. These models calculate the predicted signal strength and reliability for a lattice. To evaluate proposed method and system performance, We perform experiments in a $20m{\times}22m$ real indoor environment installed access points. According to the result, the proposed system reduced distance error than RADAR. Comparing the existing system, it reduced about 1.74m.

Audio Fingerprint Extraction Method Using Multi-Level Quantization Scheme (다중 레벨 양자화 기법을 적용한 오디오 핑거프린트 추출 방법)

  • Song Won-Sik;Park Man-Soo;Kim Hoi-Rin
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.4
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    • pp.151-158
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    • 2006
  • In this paper, we proposed a new audio fingerprint extraction method, based on Philips' music retrieval algorithm, which uses the energy difference of neighboring filter-bank and probabilistic characteristics of music. Since Philips method uses too many filter-banks in limited frequency band, it may cause audio fingerprints to be highly sensitive to additive noises and to have too high correlation between neighboring bands. The proposed method improves robustness to noises by reducing the number of filter-banks while it maintains the discriminative power by representing the energy difference of bands with 2 bits where the quantization levels are determined by probabilistic characteristics. The correlation which exists among 4 different levels in 2 bits is not only utilized in similarity measurement. but also in efficient reduction of searching area. Experiments show that the proposed method is not only more robust to various environmental noises (street, department, car, office, and restaurant), but also takes less time for database search than Philips in the case where music is highly degraded.

Video Fingerprinting System through Zero-based Code Modulation Technique (제로기반 코드 변조 기법을 통한 비디오 핑거프린팅 시스템)

  • Choi Sun Young;Lee Hae-Yeoun;Kang In Koo;Lee Heung-Kyu
    • The KIPS Transactions:PartB
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    • v.12B no.4 s.100
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    • pp.443-450
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    • 2005
  • Digital fingerprinting is a contents-protection technique, where customer information is inserted into digital contents. Fingerprinted contents undergo various attacks. Especially, attackers can remove easily the inserted fingerprint by collusion attacks, because digital fingerprinting inserts slightly different codes according to the customers. Among collusion attacks, averaging attack is a simple, fast, and efficient attack. In this paper, we propose a video fingerprinting system that is robust to the averaging attack. In order to achieve code efficiency and robustness against the averaging attack, we adopt anti-collusion code (fingerprint code) from GD-PBIBD theory. When the number of users is increased, the size of fingerprint code also grows. Thus, this paper addresses a zero-based code modulation technique to embed and detect this fingerprint code efficiently. We implemented a blind video fingerprinting system based on our proposed technique and performed experiments on various colluding cases. Based on the results, we could detect most of colluders. In the worst case, our scheme could trace at least one colluder successfully.