• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1662-1665
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• 2002

This paper proposes a novel semantic feature detection (SFD) method for real-time image transmission of sign language and finger spelling. We extract semantic information as an interlingua from input text by natural language processing, and then transmit the semantic feature detection, which actually is a parameterized action representation, to the 3-D articulated humanoid models prepared in each client in remote locations. Once the SFD is received, the virtual human will be animated by the synthesized SFD. The experimental results based on Japanese sign langauge and Chinese sign langauge demonstrate that this algorithm is effective in real-time image delivery of sign language and finger spelling.

• Journal of Microbiology and Biotechnology
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• v.31 no.9
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• pp.1323-1329
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• 2021

Micro-scale magnetic beads are widely used for isolation of proteins, DNA, and cells, leading to the development of in vitro diagnostics. Efficient isolation of target biomolecules is one of the keys to developing a simple and rapid point-of-care diagnostic. A zinc finger protein (ZFP) is a double-stranded (ds) DNA-binding domain, providing a useful scaffold for direct reading of the sequence information. Here, we utilized two engineered ZFPs (Stx2-268 and SEB-435) to detect the Shiga toxin (stx2) gene and the staphylococcal enterotoxin B (seb) gene present in foodborne pathogens, Escherichia coli O157 and Staphylococcus aureus, respectively. Engineered ZFPs are immobilized on a paramagnetic bead as a detection platform to efficiently isolate the target dsDNA-ZFP bound complex. The small paramagnetic beads provide a high surface area to volume ratio, allowing more ZFPs to be immobilized on the beads, which leads to increased target DNA detection. The fluorescence signal was measured upon ZFP binding to fluorophore-labeled target dsDNA. In this study, our system provided a detection limit of ≤ 60 fmol and demonstrated high specificity with multiplexing capability, suggesting a potential for development into a simple and reliable diagnostic for detecting multiple pathogens without target amplification.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.847-850
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• 2008

On today, human is going to develop machine by using mutual communication to machine. Including vision - based HCI(Human Computer Interaction), the technique which to recognize finger and to track finger is important in HCI systems, in HCI systems. In order to divide finger, this paper uses more effectively dividing the technique using subtraction which is separation of background and foreground, as well as to divide finger from limited background and cluttered background. In order to divide finger, the finger is recognized to make "Template-Matching" by identified fingertip images. And, identified gestures be compared the tracked gesture after tracking recognized finger. In this paper, after obtaining interest area, not only using subtraction image and template-matching but to perform template-matching in the area. So, emphasis is placed on decreasing perform speed and reaction speed, and we propose technique which is more effectively recognizing gestures.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.3
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• pp.85-90
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• 2014

In this paper, we propose a virtual violin implementation using the detection of bowing and finger dropping position from the estimated finger tip and finger board information with the 3D image data from a Kinect. Violin finger board pattern and depth information are extracted from the color image and depth image to detect the touch event on the violin finger board and to identify the touched position. Final decision of activated musical alphabet is carried out with the finger drop position and bowing information. Our virtual violin uses PC MIDI to output synthesized violin sound. The experimental results showed that the proposed method can detect finger drop position and bowing detection with high accuracy. Virtual violin can be utilized for the easy and convenient interface for a beginner to learn playing violin with the PC-based learning software.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.5
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• pp.1-7
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• 2013

The present paper relates to a development of the Gear Detection Sensor for automotive manual transmission. To detect air gap from control finger to detecting zone of sensor based on non-contacted method, permanent magnet and linear type Hall IC are mounted in this sensor. Control finger is machined to 3 step heights to detect 3 gear stages such as In-Gear, Normal and Rear. After conducting actual experimentation based on exclusive Jig and FEM, it is described to consider possibility for automotive application of Gear Detection Sensor.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.701-709
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• 2019

Recently, heart rate signal, which is one of biological signals, have been used in various fields related to healthcare. Conventionally, most of the proposed heart rate signal detection methods are contact type methods, but there is a problem of discomfort that the subject have to contact with the device. In order to solve the problem, detection study by non-contact method has been progressed recently. The detected heart rate signal can be used for finger vein liveness detection and various application using heart rate. In this paper, we propose a method to obtain heart rate signal by using finger vein imaging system. The proposed method detected the signal from the changes of the brightness value in the time domain of the infrared finger vein images and converted it into the frequency domain using the image processing algorithm. After the conversion, we removed the noise not related to the heart rate signal through band-pass filtering. In order to evaluate the accuracy of the signal, we analyzed the correlation with the signal obtained simultaneously with the finger vein acquisition device and contact type PPG sensor approved by KFDA. As a result, it was possible to confirm that the heart rate signal detected in non-contact method through the finger vein image coincides with the waveform of actual heart rate signal.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.5
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• pp.129-137
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• 2019

Ubiquitous computing technology is emerging as information technology advances. In line with this, a number of studies are being carried out to increase device miniaturization and user convenience. Some of the proposed devices are user-friendly and uncomfortable with hand-held operation. To address these inconveniences, this paper proposed a virtual button that could be used in watching television. When watching a video on television, a camera is installed at the top of the TV, using the fact that the user watches the video from the front, so that the camera takes a picture of the top of the head. Extract the background and hand area separately from the filmed image, extract the outline to the extracted hand area, and detect the tip point of the finger. Detection of the end point of the finger produces a virtual button interface at the top of the image being filmed in front, and the button activates when the end point of the detected finger becomes a pointer and is located inside the button.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.53-63
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• 2019

To provide a hand gesture interface through deep learning in mobile environments, research on the light-weighting of networks is essential for high recognition rates while at the same time preventing degradation of execution speed. This paper proposes a method of real-time recognition of written characters in the air using a finger on mobile devices through the light-weighting of deep-learning model. Based on the SSD (Single Shot Detector), which is an object detection model that utilizes MobileNet as a feature extractor, it detects index finger and generates a result text image by following fingertip path. Then, the image is sent to the server to recognize the characters based on the learned OCR model. To verify our method, 12 users tested 1,000 words using a GALAXY S10+ and recognized their finger with an average accuracy of 88.6%, indicating that recognized text was printed within 124 ms and could be used in real-time. Results of this research can be used to send simple text messages, memos, and air signatures using a finger in mobile environments.

• Journal of Korea Multimedia Society
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• v.17 no.1
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• pp.60-68
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• 2014

Extensive researches on PC control system via interaction between PC and users are being conducted recently, especially on human finger recognition in the electronic devices. Heretofore, researches on methods to improve the accuracy of finger recognition in a single device and to control the devices with it have been the mainstream, whereas many different industries where finger recognition become more utilized are demanding researches on methods to selectively control the system of multiple devices for applications in various environments and situations. This article demonstrates attempts to selectively control one of two devices through finger recognition. Along with this, experiments conducted with 6 variable conditions are demonstrated here, where the optimal condition to increase the rate of successful selective finger recognition between two devices is studied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.2
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• pp.174-182
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• 2013

Most methods for fusion-based finger vein recognition were to fuse different features or matching scores from more than one trait to improve performance. To overcome the shortcomings of "the curse of dimensionality" and additional running time in feature extraction, in this paper, we propose a finger vein recognition technology based on matching score-level fusion of a single trait. To enhance the quality of finger vein image, the contrast-limited adaptive histogram equalization (CLAHE) method is utilized and it improves the local contrast of normalized image after ROI detection. Gabor features are then extracted from eight channels based on a bank of Gabor filters. Instead of using the features for the recognition directly, we analyze the contributions of Gabor feature from each channel and apply a weighted matching score-level fusion rule to get the final matching score, which will be used for the last recognition. Experimental results demonstrate the CLAHE method is effective to enhance the finger vein image quality and the proposed matching score-level fusion shows better recognition performance.