• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권4호
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• pp.1122-1140
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• 2024

The importance of indoor positioning has grown in numerous application areas such as emergency response, logistics, and industrial automation. In ships, indoor positioning is also needed to provide services to passengers on board. Due to the complex structure and dynamic nature of ship environments, conventional positioning techniques have limitations in providing accurate positions. Compared to other indoor positioning technologies, Bluetooth 5.1-based indoor positioning technology is highly suitable for ship environments. Bluetooth 5.1 attains centimeter-level positioning accuracy by collecting In-phase and Quadrature (IQ) samples from wireless signals. However, distorted IQ samples can lead to significant errors in the final estimated position. Therefore, we propose an indoor positioning method for ships that utilizes a Deep Neural Network (DNN) combined with IQ fingerprint maps to overcome the challenges associated with accurate location detection within the ship. The results indicate that the accuracy of our proposed method can reach up to 97.76%.

• Journal of the Korean Institute of Telematics and Electronics D
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• 제36D2호
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• pp.62-70
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• 1999

This paper introduces a possibility of a low-cost, high-resolution fingerprint sensor chip. The test chip is composed of $64{\times}256$ sensing cells(chip size : $2.7mm{\times}10.8mm$). A new detection circuit of charge sharing is proposed, which eliminates the influences of internal parasitic copacitances. This the reduced sensing-capacitor size enables a high resolution of 600dpi, using even conventional 0.6${\mu}m$ CMOS process. The partial fingerprint image captured therefrom are synthesized into a full fingerprint image with a image synthesis algorithm. The problems and possibilities of image synthesis technique are also analyzed and discussed.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.82-85
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• 2004

This paper proposes an advanced circuit for the capacitive type fingerprint sensor signal processing and an effective isolation structure for minimizing an electrostatic discharge(ESD) influence and for removing a signal coupling noise of each sensor pixel. The proposed detection circuit increases the voltage difference between a ridge and valley about $80\%$ more than old circuit. The test chip is composed of $160\;\times\;192$ array sensing cells $(9,913\times11,666\;um^2).$ The sensor plate area is $58\;\times\;58\;um^2$ and the pitch is 60um. The image resolution is 423 dpi. The chip was fabricated on a 0.35um standard CMOS process. It successfully captured a high-quality fingerprint image and performed the registration and identification processing. The sensing and authentication time is 1 sec(.) with the average power consumption of 10 mW at 3.0V. The reveal ESD tolerance is obtained at the value of 4.5 kV.

• Journal of the Institute of Electronics Engineers of Korea CI
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• 제44권3호
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• pp.90-97
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• 2007

For a highly reliable fingerprint recognition system, the precise and accurate feature extraction is indispensable. In this paper, We propose a highly efficient crease extraction method, which can improve the accuracy of feature extraction within the fingerprint image. The proposed method applies the 1-dimensional directional slit for each pixel in fingerprint image. And then it calculates the average grey level and variance to determine whether the current pixel composes the crease, and estimates the direction of crease. Once the direction of every pixel in crease candidate area is estimated, it is decomposed into 8 different images depending on their direction. From the 8 directional images, the crease clusters are estimated by utilizing the property of crease area. The proposed method finally extracts the crease from the crease clusters estimated from directional images. In conclusion, the proposed method highly improved the accuracy of overall feature extraction by accurate and precise extraction of the crease from fingerprint image.

• Advances in Traditional Medicine
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• 제6권4호
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• pp.293-299
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• 2006

By using high-performance liquid chromatography-photodiode array detection, a simple and accurate chromatographic fingerprint method was developed for the identification of Radix Codonopsis (roots of Codonopsis) from different sources. Eighteen herbs of Codonopsis at different habitats in China, including roots from Codonopsis pilosula, Codonopsis pilosula var. modesta and Codonopsis tangshen were analyzed by the fingerprint. The amount of lobetyolin was calibrated, which was found to be more consistent in roots of Codonopsis pilosula as compared to that of Codonopsis pilosula var. modesta and Codonopsis tangshen. Having the fingerprint results, hierarchical clustering analyses were performed to classify the eighteen herbs into three groups: Codonopsis pilosula, Codonopsis pilosula var. modesta and Codonopsis tangshen. This clustering analysis agrees very well with the pharmacognostic identification result, and which could be used as a tool in the quality control of Radix Codonopsis.

• Journal of Communications and Networks
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• 제11권6호
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• pp.544-555
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• 2009

This work continues a trend of developments aimed at exploiting the physical layer of the open systems interconnection (OSI) model to enhance wireless network security. The goal is to augment activity occurring across other OSI layers and provide improved safeguards against unauthorized access. Relative to intrusion detection and anti-spoofing, this paper provides details for a proof-of-concept investigation involving "air monitor" applications where physical equipment constraints are not overly restrictive. In this case, RF fingerprinting is emerging as a viable security measure for providing device-specific identification (manufacturer, model, and/or serial number). RF fingerprint features can be extracted from various regions of collected bursts, the detection of which has been extensively researched. Given reliable burst detection, the near-term challenge is to find robust fingerprint features to improve device distinguishability. This is addressed here using wavelet domain (WD) RF fingerprinting based on dual-tree complex wavelet transform (DT-$\mathbb{C}WT$) features extracted from the non-transient preamble response of OFDM-based 802.11a signals. Intra-manufacturer classification performance is evaluated using four like-model Cisco devices with dissimilar serial numbers. WD fingerprinting effectiveness is demonstrated using Fisher-based multiple discriminant analysis (MDA) with maximum likelihood (ML) classification. The effects of varying channel SNR, burst detection error and dissimilar SNRs for MDA/ML training and classification are considered. Relative to time domain (TD) RF fingerprinting, WD fingerprinting with DT-$\mathbb{C}WT$ features emerged as the superior alternative for all scenarios at SNRs below 20 dB while achieving performance gains of up to 8 dB at 80% classification accuracy.

• Journal of Convergence for Information Technology
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• 제9권3호
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• pp.8-15
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• 2019

Recently, the importance of pre-shipment quality inspection has been emphasized due to the increase of STB supply. In this paper, we propose a method to support automation of quality inspection through simultaneous multi-channel input of STB video signal. The proposed method extracts a fingerprint using the center scan line of the image after stable video shot boundary detection using CeLDP combining color information and LDP code and performs synchronization between input video channels. The proposed method shows stronger shot boundary detection performance than the conventional shot detection method. Through the experiments applied to the real environment, it is possible to secure reliability and real-time quality check for synchronization between multi-channel inputs required for STB quality inspection. Also, based on the proposed method, we intend to study a large-scale quality inspection method in the future and propose a more effective quality inspection system.

• Journal of the Semiconductor & Display Technology
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• 제12권2호
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• pp.57-61
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• 2013

This paper presents adaptive neuro-fuzzy inference based defect detection method for various defect types, such as micro-crack, fingerprint and contamination, in heterogeneously textured surface of polycrystalline solar wafers. Polycrystalline solar wafer consists of various crystals so the surface of solar wafer shows heterogeneously textures. Because of this property the visual inspection of defects is very difficult. In the proposed method, we use local binary feature and fuzzy reasoning for defect detection. Experimental results show that our proposed method achieves a detection rate of 80%~100%, a missing rate of 0%~20% and an over detection (overkill) rate of 9%~21%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국해양정보통신학회 2008년도 추계종합학술대회 B
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• pp.571-574
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• 2008

In this paper, we propose $256{\times}256$ pixel array fingerprint sensor with an advanced circuits for detecting. The pixel level simple detection circuit converts from a small and variable sensing current to binary voltage out effectively. We minimizes an electrostatic discharge(ESD) influence by applying an effective isolation structure. The sensor circuit blocks were designed and simulated in standard CMOS $0.35{\mu}m$ process. Full custom layout is performed in the unit sensor pixel and auto placement and routing is performed in the full chip.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제13권3호
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• pp.531-536
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• 2009

In this paper, we propose $256{\times}256$ pixel array fingerprint sensor with an advanced circuits for detecting. The pixel level simple detection circuit converts from a small and variable sensing current to binary voltage out effectively. We minimizes an electrostatic discharge(ESD) influence by applying an effective isolation structure around the unit pixel. The sensor circuit blocks were designed and simulated in standard CMOS $0.35{\mu}m$ process. Full custom layout is performed in the unit sensor pixel and auto placement and routing is performed in the full chip.