• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1904-1926
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• 2016

Iris recognition for biometric personnel identification has gained much interest owing to the increasing concern with security today. The image quality plays a major role in the performance of iris recognition systems. When capturing an iris image under uncontrolled conditions and dealing with non-cooperative people, the chance of getting non-ideal images is very high owing to poor focus, off-angle, noise, motion blur, occlusion of eyelashes and eyelids, and wearing glasses. In order to improve the accuracy of iris recognition while dealing with non-ideal iris images, we propose a novel algorithm that improves the quality of degraded iris images. First, the iris image is localized properly to obtain accurate iris boundary detection, and then the iris image is normalized to obtain a fixed size. Second, the valid region (iris region) is extracted from the segmented iris image to obtain only the iris region. Third, to get a well-distributed texture image, bilinear interpolation is used on the segmented valid iris gray image. Using contrast-limited adaptive histogram equalization (CLAHE) enhances the low contrast of the resulting interpolated image. The results of CLAHE are further improved by stretching the maximum and minimum values to 0-255 by using histogram-stretching technique. The gray texture information is extracted by 1D Gabor filters while the Hamming distance technique is chosen as a metric for recognition. The NICE-II training dataset taken from UBRIS.v2 was used for the experiment. Results of the proposed method outperformed other methods in terms of equal error rate (EER).

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.75-82
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• 2021

Mastitis in cows is a major factor that hinders dairy productivity of farms, and many attempts have been made to solve it. However, research on mastitis has been limited to diagnosis rather than prediction, and even this is mostly using a single sensor. In this study, a predictive model was developed using multivariate data including biometric data and environmental data. The data used for the analysis were collected from robot milking machines and sensors installed in farmhouses in Chungcheongnam-do, South Korea. The recurrent neural network model using three weeks of data predicts whether or not mastitis is diagnosed the next day. As a result, mastitis was predicted with an accuracy of 82.9%. The superiority of the model was confirmed by comparing the performance of various data collection periods and various models.

• Journal of Biomedical Engineering Research
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• v.25 no.1
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• pp.43-47
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• 2004

Interests in human brain functionality and its connectivity have much frown up. DTI (Diffusion tensor imaging) has been known as a non-invasive MR) technique capable of providing information on water diffusion in tissues and the organization of white matter tract. Thus. It can provide us the information on the direction of brain fiber tract and the connectivity among many important cortical regions which can not be examined by other anatomical or functional MRI techniques. In this study. was used the 24 bit color coding scheme on the IDL platform in the windows environment to visualize the orientation of major fiber tracts of brain such as main association, projection, commissural fibers and corticospinal tracts. We additionally implemented a color coding scheme for each directional component and FA (fractional anisotropy), and used various color tables for them to be visualized more definitely. Consequently we implemented a fancy and basic technique to visualize the directional information of fiber tracts efficiently and we confirmed the feasibility of the 24 bit color coding scheme in DTI by visualizing main fiber tracts.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.87-95
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• 2022

Recently, with the development of smart technology, in medical information platform, patient's biometric data is measured in real time and accumulated into database, and it is possible to determine the patient's emergency situations. Medical staff can easily access patient information after simple authentication using a mobile terminal. However, in accessing medical information using the mobile terminal, it is necessary to study authentication in consideration of the patient situations and mobile terminal. In this paper, we studied on medical information platforms based on big data processing and edge computing for supporting automatic authentication in emergency situations. The automatic authentication system that we had studied is an authentication system that simultaneously performs user authentication and mobile terminal authentication in emergency situations, and grants upper-level access rights to certified medical staff and mobile terminal. Big data processing and analysis techniques were applied to the proposed platform in order to determine emergency situations in consideration of patient conditions such as high blood pressure and diabetes. To quickly determine the patient's emergency situations, edge computing was placed in front of the medical information server so that the edge computing determine patient's situations instead of the medical information server. The medical information server derived emergency situation decision values using the input patient's information and accumulated biometric data, and transmit them to the edge computing to determine patient-customized emergency situation. In conclusion, the proposed medical information platform considers the patient's conditions and determine quick emergency situations through big data processing and edge computing, and enables rapid authentication in emergency situations through automatic authentication, and protects patient's information by granting access rights according to the patient situations and the role of the medical staff.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.31-40
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• 2018

With the development of IT technology recently, medical information systems are being constructed in an integrated u-health environment through cloud services, IoT technologies, and mobile applications. These kinds of medical information systems should provide the medical staff with authorities to access patients' medical information for emergency status treatments or therapeutic purposes. Therefore, in the medical information systems, the reliable and prompt authentication processes are necessary to access the biometric information and the medical information of the patients in charge of the medical staff. However, medical information systems are accessing with simple and static user authentication mechanism using only medical ID / PWD in the present system environment. For this reason, in this paper, we suggest a dynamic situation authentication mechanism that provides transparency of medical information access including various authentication factors considering patient's emergency status condition and dynamic situation authentication system supporting it. Our dynamic Situation Authentication is a combination of user authentication and mobile device authentication, which includes various authentication factor attributes such as emergency status, role of medical staff, their working hours, and their working positions and so forth. We designed and implemented a dynamic situation authentication system including emergency status decision, dynamic situation authentication, and authentication support DB construction. Finally, in order to verify the serviceability of the suggested dynamic situation authentication system, the medical staffs download the mobile application from the medical information server to the medical staff's own mobile device together with the dynamic situation authentication process and the permission to access medical information to the patient and showed access to medical information.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.25-34
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• 2020

In the current medical information system, a system environment is constructed in which Biometric data generated by using IoT or medical equipment connected to a patient can be stored in a medical information server and monitored at the same time. Also, the patient's biometric data, medical information, and personal information after simple authentication using only the ID / PW via the mobile terminal of the medical staff are easily accessible. However, the method of accessing these medical information needs to be improved in the dimension of protecting patient's personal information, and provides a quick authentication system for first aid. In this paper, we implemented an automatic authentication system based on the patient's situation and evaluated its performance. Patient's situation was graded into normal and emergency situation, and the situation of the patient was determined in real time using incoming patient biometric data from the ward. If the patient's situation is an emergency, an emergency message including an emergency code is send to the mobile terminal of the medical staff, and they attempted automatic authentication to access the upper medical information of the patient. Automatic authentication is a combination of user authentication(ID/PW, emergency code) and mobile terminal authentication(medical staff's role, working hours, work location). After user authentication, mobile terminal authentication is proceeded automatically without additional intervention by medical staff. After completing all authentications, medical staffs get authorization according to the role of medical staffs and patient's situations, and can access to the patient's graded medical information and personal information through the mobile terminal. We protected the patient's medical information through limited medical information access by the medical staff according to the patient's situation, and provided an automatic authentication without additional intervention in an emergency situation. We performed performance evaluation to verify the performance of the implemented automatic authentication system.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.53-61
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• 2020

Recently, as the uncontact service is activated in earnest due to the Corona 19 virus, the necessity of system development to provide non-face-to-face contact remote medical service has increased. In this study, we propose a smart healthcare system, Rm_She(Remote Medical Smart Healthcare System). Rm_She can collect and manage various vital signs information by connecting various healthcare products that detect bio-signals based on IoT to one application. The health check app (HC_app) is used to connect vital sign measurement devices to a wireless LAN and receive vital sign values from the HC_app. Then, the vital signs are output to the user on the smartphone, and the corresponding information is transmitted to the healthcare management server. The healthcare server receives the measured values and stores them in a database, and the stored measured values are provided as a web service so that medical staff can remotely monitor them in real time.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.9
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• pp.345-350
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• 2018

This study is an algorithm for detecting vein pattern features important for finger vein recognition. The feature detection algorithm is important because it greatly affects recognition results in pattern recognition. The recognition rate is degraded because the reference is changed according to the finger position change. In addition, the image obtained by irradiating the finger with infrared light is difficult to separate the image background and the blood vessel pattern, and the detection time is increased because the image preprocessing process is performed. For this purpose, the presented algorithm can be performed without image preprocessing, and the detection time can be reduced. SWDA (Down Slope Trace Waveform) algorithm is applied to the finger vein images to detect the fingertip position and vein pattern. Because of the low infrared transmittance, relatively dark vein images can be detected with minimal detection error. In addition, the fingertip position can be used as a reference in the classification stage to compensate the decrease in the recognition rate. If we apply algorithms proposed to various recognition fields such as palm and wrist, it is expected that it will contribute to improvement of biometric feature detection accuracy and reduction of recognition performance time.

• Journal of KIISE:Software and Applications
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• v.28 no.11
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• pp.864-873
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• 2001

In this paper, a new approach to building a registration authority for issuing PKI-based certificates is presented to make the process of identifying an individual more secure and reliable by utilizing human iris recognition technology. The tasks of the proposed system associated with the manipulation of irises except for the general functions of registration authorities can be categorized into three modules, the acquisition of iris images, the registration of iris information, and the verification of users by means of iris patterns. The information among the three modules is safely exchanged through encryption and decryption with a symmetric cryptographic method. As a feature extraction method for a given iris image, a wavelet transform is applied to represent a feature vector with a small dimension of information obtained by subsampling an image corresponding to lower frequency bands successively without loss of information. Through the experiments on human iris recognition technology we proposed and applied to the registration authority, the potential of biometric technology in various applications is confirmed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.3
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• pp.206-211
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• 2020

It is Face recognition is a very important process in image monitoring and it is a form of biometric technology. The recognition process involves many variables and is highly complex, so the software development has only begun recently with the development of hardware. Face detection technology using the CCTV is a process that precedes face analysis, and it is a technique that detects where the face is in the image. Research in face detection and recognition has been difficult because the human face reacts sensitively to different environmental conditions, such as lighting, color of skin, direction, angle and facial expression. The utility and importance of face recognition technology is coming into the limelight over time, but many aspects are being overlooked in the facial area detection technology that must precede face recognition. The system in this paper can detect tilted faces that cannot be detected by the AdaBoost detector and It could also be used to detect other objects.