• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.86-88
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• 2017

The digital door lock is an electronic door lock that uses a password system and has the function of automatically locking the door when the door is closed, thus eliminating the worry about the door lock. As the technology has gradually developed, various authentication technologies such as semiconductor key system, RFID, and fingerprint recognition have been introduced. However, there is a danger of copying the door lock key, and there are password stealing and infringement. In this paper, we develop a remote control system that can unlock or open a smartphone to supplement the user's risk. The system you are going to develop can use WiFi to check if the door is locked or open on your smartphone, and you can lock or unlock the door remotely.

• Smart Media Journal
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• v.6 no.3
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• pp.29-40
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• 2017

Lately weight for smartphone mounted to function for NFC is increasing, rapidly. Because of this, NFC related technology is made by many companies. We developed Gallery-Auction for security enhancements and new services of NFC-based 2 factor electronic payment system. Enhanced security features development of user authentication module through fingerprint recognition to apply FIDO authentication technology and developed electronic contract voice service of Gallery-Auction using TTS(Text to Speech). Therefore we enhanced convenient and simple authentication method and security through NFC mobile electronic payment.

• Proceedings of the Korean Society of Applied Pharmacology
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• 2007.11a
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• pp.19-27
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• 2007

An important potential of metabolomics-based approach is the possibility to develop fingerprints of diseases or cellular responses to classes of compounds with known common biological effect. Such fingerprints have the potential to allow classification of disease states or compounds, to provide mechanistic information on cellular perturbations and pathways and to identify biomarkers specific for disease severity and drug efficacy. Metabolic profiles of biological fluids contain a vast array of endogenous metabolites. Changes in those profiles resulting from perturbations of the system can be observed using analytical techniques, such as NMR and MS. $^1H$ NMR was used to generate a molecular fingerprint of serum or urinary sample, and then pattern recognition technique was applied to identity molecular signatures associated with the specific diseases or drug efficiency. Several metabolites that differentiate disease samples from the control were thoroughly characterized by NMR spectroscopy. We investigated the metabolic changes in human normal and clinical samples using $^1H$ NMR. Spectral data were applied to targeted profiling and spectral binning method, and then multivariate statistical data analysis (MVDA) was used to examine in detail the modulation of small molecule candidate biomarkers. We show that targeted profiling produces robust models, generates accurate metabolite concentration data, and provides data that can be used to help understand metabolic differences between healthy and disease population. Such metabolic signatures could provide diagnostic markers for a disease state or biomarkers for drug response phenotypes.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.421-426
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• 2019

Nowadays, various type of technologies are used for user authentication, such as knowledge based(ID/PW, etc.) authentication, biometric based(Iris/fingerprint/vein recognition) authentication, ownership based(OTP, security card, etc.) authentication. ID/PW authentication technology, a knowledge based authentication, despite the advantages of low in implementation and maintenance costs and being familiar to users, there are disadvantages of vulnerable to hacking attacks, Other authentication methods solve the vulnerability in ID/PW authentication technology, but they have high initial investment cost and maintenance cost and troublesome problem of reissuance. In this paper, we proposed to improve security and convenience over existing ID/PW based authentication technology, and to secure user authentication without restriction on the devices used for authentication.

• Journal of information and communication convergence engineering
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• v.21 no.3
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• pp.208-215
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• 2023

Deep learning techniques provide powerful solutions to several pattern-recognition problems, including Raman spectral classification. However, these networks require large amounts of labeled data to perform well. Labeled data, which are typically obtained in a laboratory, can potentially be alleviated by data augmentation. This study investigated various data augmentation techniques and applied multiple deep learning methods to Raman spectral classification. Raman spectra yield fingerprint-like information about chemical compositions, but are prone to noise when the particles of the material are small. Five augmentation models were investigated to build robust deep learning classifiers: weighted sums of spectral signals, imitated chemical backgrounds, extended multiplicative signal augmentation, and generated Gaussian and Poisson-distributed noise. We compared the performance of nine state-of-the-art convolutional neural networks with all the augmentation techniques. The LeNet5 models with background noise augmentation yielded the highest accuracy when tested on real-world Raman spectral classification at 88.33% accuracy. A class activation map of the model was generated to provide a qualitative observation of the results.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.6
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• pp.95-105
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• 2003

A novel reference point detection method is proposed by exploiting tile gradient probabilistic model that captures the curvature information of fingerprint. The detection of reference point is accomplished through searching and locating the points of occurrence of the most evenly distributed gradient in a probabilistic sense. The uniformly distributed gradient texture represents either the core point itself or those of similar points that can be used to establish the rigid reference from which to map the features for recognition. Key benefits are reductions in preprocessing and consistency of locating the same points as the reference points even when processing arch type fingerprints. Moreover, the new feature extraction method is proposed by improving the existing feature extraction using filterbank method. Experimental results indicate the superiority of tile proposed scheme in terms of computational time in feature extraction and verification rate in various noisy environments. In particular, the proposed gradient probabilistic model achieved 49% improvement under ambient noise, 39.2% under brightness noise and 15.7% under a salt and pepper noise environment, respectively, in FAR for the arch type fingerprints. Moreover, a reduction of 0.07sec in reference point detection time of the GPM is shown possible compared to using the leading the poincare index method and a reduction of 0.06sec in code extraction time of the new filterbank mettled is shown possible compared to using the leading the existing filterbank method.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.1-15
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• 2006

In Korea, a resident registration card has various personal information such as a present address, a resident registration number, a face picture and a fingerprint. A plastic-type resident card currently used is easy to forge or alter and tricks of forgery grow to be high-degree as time goes on. So, whether a resident card is forged or not is difficult to judge by only an examination with the naked eye. This paper proposed an automatic recognition method of a resident card which recognizes a resident registration number by using a refined ART2-based RBF network newly proposed and authenticates a face picture by a template image matching method. The proposed method, first, extracts areas including a resident registration number and the date of issue from a resident card image by applying Sobel masking, median filtering and horizontal smearing operations to the image in turn. To improve the extraction of individual codes from extracted areas, the original image is binarized by using a high-frequency passing filter and CDM masking is applied to the binaried image fur making image information of individual codes better. Lastly, individual codes, which are targets of recognition, are extracted by applying 4-directional contour tracking algorithm to extracted areas in the binarized image. And this paper proposed a refined ART2-based RBF network to recognize individual codes, which applies ART2 as the loaming structure of the middle layer and dynamicaly adjusts a teaming rate in the teaming of the middle and the output layers by using a fuzzy control method to improve the performance of teaming. Also, for the precise judgement of forgey of a resident card, the proposed method supports a face authentication by using a face template database and a template image matching method. For performance evaluation of the proposed method, this paper maked metamorphoses of an original image of resident card such as a forgey of face picture, an addition of noise, variations of contrast variations of intensity and image blurring, and applied these images with original images to experiments. The results of experiment showed that the proposed method is excellent in the recognition of individual codes and the face authentication fur the automatic recognition of a resident card.

• Journal of Sensor Science and Technology
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• v.11 no.5
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• pp.255-262
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• 2002

Human retina is able to detect the edge of an object effectively. We designed a CMOS vision chip by modeling cells of the retina as hardwares involved in edge detection. There are several fluctuation factors which affect characteristics of MOSFETs during CMOS fabrication process and this effect appears as output offset of the vision chip which is composed of pixel arrays and readout circuits. The vision chip detecting edge information from input image is used for input stage of other systems. Therefore, the output offset of a vision chip determine the efficiency of the entire performance of a system. In order to eliminate the offset at the output stage, we designed a vision chip by using CDS(Correlated Double Sampling) technique. Using standard CMOS process, it is possible to integrate with other circuits. Having reliable output characteristics, this chip can be used at the input stage for many applications, like targe tracking system, fingerprint recognition system, human-friendly robot system and etc.

• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.1-15
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• 2005

As organizations search fur more secure authentication methods (Dr user access, e-commerce, and other security applications, biometrics is gaining increasing attention. Biometrics offers greater security and convenience than traditional methods of personal recognition. In some applications, biometrics can replace or supplement the existing technology. In others, it is the only viable approach. Several biometric methods of identification, including fingerprint hand geometry, facial, ear, iris, eye, signature and handwriting have been explored and compared in this paper. They all are well suited for the specific application to their domain. This paper briefly identifies and categorizes them in particular domain well suited for their application. Some methods are less intrusive than others.

• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.33-41
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• 2011

RFID technology is already used in the various application fields such as identification card, traffic card and etc. Many RFID application systems using UHF have been developed in the field of asset management, logistics and security. Because a human being can make mistakes, we need the system that can efficiently manage the special assets such as small arms, jewelry and medicine and can monitor them in real time. In this paper, we proposed a special assets management system to keep assets in safe custody, to monitor their safety status in real time and to manage distribution channels and history of those assets. The developed system is called Smart Cabinet because it has cabinet's form. Smart Cabinet integrates such technologies as RFID, smart card, fingerprint recognition, several sensors and LCD display in order to provide the functions for special asset management. Those functions include condition monitoring of assets, traceability management, distribution channels and security logs, which are to interact with a management server. The article demonstrated the potentiality of RFID by presenting special asset management solutions dedicated to guns and medicine management, and also showed the effectiveness and possibility of those solutions.