• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.3
• /
• pp.147-156
• /
• 2024

This paper introduces the design of a turtle neck posture correction and prevention system for users of digital devices for a long time. The number of forward head posture patients in Korea increased by 13% from 2018 to 2021, and has not yet improved according to the latest statistics at the present time. Because of the nature of the disease, prevention is more important than treatment. Therefore, in this paper, we designed a system based on built-camera in most laptops to increase the accessiblility of the system, and utilize the features such as Pose Estimation, Face Landmarks Detection, Iris Tracking, and Depth Estimation of Google Mediapipe to prevent the need to produce artificial intelligence models and allow users to easily prevent forward head posture.

• Journal of the Korean institute of surface engineering
• /
• v.55 no.6
• /
• pp.342-352
• /
• 2022

Purine catabolite screening enables reliable diagnosis of certain diseases. In this regard, the development of a facile detection strategy with high sensitivity and selectivity is demanded for point-of-care applications. In this work, the simultaneous detection of uric acid (UA), xanthine (XA), and hypoxanthine (HX) was carried out as model purine catabolites by surface-enhanced Raman Spectroscopy (SERS). The detection assay was conducted by employing high-aspect ratio Au nanopillar substrates coupled with in-situ Au electrodeposition on the substrates. The additional modification of the Au nanopillar substrates via electrodeposition was found to be an effective method to encapsulate molecules in solution into nanogaps of growing Au films that increase metal-molecule contact and improve substrate's sensitivity and selectivity. In complex solutions, the approach facilitated ternary identification of UA, XA, and HX down to concentration limits of 4.33 𝜇M, 0.71 𝜇M, and 0.22 𝜇M, respectively, which are comparable to their existing levels in normal human physiology. These results demonstrate that the proposed platform is reliable for practical point-of-care analysis of biofluids where solution matrix effects greatly reduce selectivity and sensitivity for rapid on-site disease diagnosis.

• International Journal of Computer Science & Network Security
• /
• v.22 no.9
• /
• pp.280-286
• /
• 2022

Facial recognition system is a biometric manipulation. Its applicability is simpler, and its work range is broader than fingerprints, iris scans, signatures, etc. The system utilizes two technologies, such as face detection and recognition. This study aims to develop a facial recognition system to recognize person's faces. Facial recognition system can map facial characteristics from photos or videos and compare the information with a given facial database to find a match, which helps identify a face. The proposed system can assist in face recognition. The developed system records several images, processes recorded images, checks for any match in the database, and returns the result. The developed technology can recognize multiple faces in live recordings.

• Journal of Korea Multimedia Society
• /
• v.15 no.6
• /
• pp.722-730
• /
• 2012

Recently, eye image information has been widely used for iris recognition or gaze detection in biometrics or human computer interaction. According as long distance camera-based system is increasing for user's convenience, the noises such as eyebrow, forehead and skin areas which can degrade the accuracy of eye detection are included in the captured image. And fast processing speed is also required in this system in addition to the high accuracy of eye detection. So, we compared the most widely used algorithms for eye detection such as AdaBoost eye detection algorithm, adaptive template matching+AdaBoost algorithm, CAMShift+AdaBoost algorithm and rapid eye detection method. And these methods were compared with images including light changes, naive eye and the cases wearing contact lens or eyeglasses in terms of accuracy and processing speed.

• The Plant Pathology Journal
• /
• v.27 no.3
• /
• pp.291-296
• /
• 2011

In order to detect quarantine plant viruses, we developed reverse transcription-polymerase chain reaction (RT-PCR) primer pairs for five single-stranded (ss) plant RNA viruses that are not currently reported in Korea but could be potential harmful plant viral pathogens. Three viruses such as Chilli veinal mottle virus (ChiVMV), Colombian datura virus (CDV), and Tobacco etch virus (TEV) belong to the genus Potyvirus while Chrysanthemum stem necrosis virus (CSNV) and Iris yellow spot virus (IYSV) are members of the genus Tospovirus. To design RT-PCR primers, we used reported gene sequences corresponding to the capsid protein and polyprotein for ChiVMV, CDV, and TEV while using nucleocapsid protein regions for CSNV and IYSV. At least two different primer pairs were designed for each virus. Fifteen out of 16 primer pairs were successfully applied in detection of individual quarantine virus with high specificity and efficiency. Taken together, this study provides a rapid and useful protocol for detection of five quarantine viruses.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.05a
• /
• pp.61-64
• /
• 2011

There are many applications that require robust and accurate eye tracking, such as human-computer interface(HCI). In this paper, a novel approach for eye tracking with a principal component analysis on rotated face. In the process of iris detection, intensity information is used. First, for select eye region using principal component analysis. Finally, for eye detection using eye region's intensity. The experimental results show good performance in detecting eye from FERET image include rotate face.

• Journal of KIISE:Software and Applications
• /
• v.37 no.11
• /
• pp.859-865
• /
• 2010

In this paper, a new method for finger vein recognition is proposed. Researchers are recently interested in the finger vein recognition since it is a good way to avoid the forgery in finger prints recognition and the inconveniences in obtaining images of the iris for iris recognition. The vein images are processed to obtain the line shaped vein images through the local histogram equalization and a thinning process. This thinned vein images are processed for matching, using a new matching algorithm, named HS(HeeSung) matching algorithm. This algorithm yields an excellent recognition rate when it is applied to the curve-linear images processed through a thinning or an edge detection. In our experiment with the finger vein images, the recognition rate has reached up to 99.20% using this algorithm applied to 650finger vein images(130person ${\times}$ 5images each). It takes only about 60 milliseconds to match one pair of images.

• Journal of the Korea Convergence Society
• /
• v.9 no.8
• /
• pp.1-8
• /
• 2018

In the field of biometric security such as face and iris recognition, it is essential to extract facial features such as eyes and lips. In this paper, we have studied a method of detecting eye and lip region in face image using faster R-CNN. The faster R-CNN is an object detection method using deep running and is well known to have superior performance compared to the conventional feature-based method. In this paper, feature maps are extracted by applying convolution, linear rectification process, and max pooling process to facial images in order. The RPN(region proposal network) is learned using the feature map to detect the region proposal. Then, eye and lip detector are learned by using the region proposal and feature map. In order to examine the performance of the proposed method, we experimented with 800 face images of Korean men and women. We used 480 images for the learning phase and 320 images for the test one. Computer simulation showed that the average precision of eye and lip region detection for 50 epoch cases is 97.7% and 91.0%, respectively.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.27 no.2
• /
• pp.305-314
• /
• 2017

Recently, user authentication through biometric traits such as fingerprint and iris raise more and more attention especially in mobile commerce and fin-tech fields. In particular, commercialized authentication methods using fingerprint recognition are widely utilized mainly because customers are more adopted and used to fingerprint recognition applications. In the meantime, the security issues caused by fingerprint falsification bring lots of attention. In this paper, we propose a new method to improve the performance of fake fingerprint detection using CNN(Convolutional Neural Network). It is common practice to increase the amount of learning data by using affine transformation or horizontal reflection to improve the detection rate in CNN characteristics that are influenced by learning data. However, in this paper we propose an effective data augmentation method based on the database difficulty level. The experimental results confirm the validity of proposed method.

• Journal of Biomedical Engineering Research
• /
• v.30 no.2
• /
• pp.113-121
• /
• 2009

This study aims at designing and evaluating light source devices that can stably generate light with various wavelengths in order to make possible PDD using a photosensitizer and diagnosis using auto-fluorescence. The light source was a Xenon lamp and filter wheel, composed of an optical output control through Iris and filters with several wavelength bands. It also makes the inducement of auto-fluorescence possible because it is designed to generate a wavelength band of 380-420nm, 430-480nm, and 480-560nm. The transmission part of the light source was developed to enhance the efficiency of light transmission. To evaluate this light source, the characteristics of light output and wavelength band were verified. To validate the capability of this device as PDD, the detection of auto-fluorescence using mouse models was performed.