• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.957-964
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• 2011

The image stabilization is the procedure of stabilizing the blurred image with image processing method. Due to easy detection of global motion, PA(Projection algorithm) based on digital image stabilization has been studied by many researchers. PA has the advantage of easy implementation and low complexity, but in the case of serious rotational motion the accuracy of the algorithm will be cut down because of its fixed exploring range, and, on the other hand, if extending the exploring range, the block for detecting motion will become small, then we cannot detect correct global motion. In this paper, to overcome the drawback of conventional PA, an Iterative Projection Algorithm (IPA) is proposed, which improved the correctness of global motion by detecting global motion with detecting block which is appropriate to different extent of motion. With IPA, in the case of processing 1000 continual frames shot in automobile, compared with conventional algorithm and other detecting range, the results of PSNR is improved 6.8% at least, and 28.9% at the most.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.214-216
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• 2006

Expressive face and human body gestures are among the main non-verbal communication channels in human-human interaction. Understanding human emotions through body gesture is one of the necessary skills both for humans and also for the computers to interact with their human counterparts. Gesture analysis is consisted of several processes such as detecting of hand, extracting feature, and recognizing emotions. Skin color information for tracking hand gesture is obtained from face detection region. We have revealed relationships between paricular body movements and specific emotions by using HMM(Hidden Markov Model) classifier. Performance evaluation of emotional human body recognition has experimented.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1272-1274
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• 1996

This paper presents the development of tactile sensor systems for robot hand which are truly usable, robust, reliable and cheap system. The sensor incorporates multiple sensing subsystems for detecting distributed contact forces and surface characteristics. The fabrication and experimental evaluation of the tactile system and its electric interfaces are described. The results indicate that the system provides reasonable performances for practical applications requiring manipulation with tactile feedback.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.1000-1015
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• 2010

In this paper, we propose a novel algorithm for hand gesture recognition. The hand detection method is based on human skin color, and we use the boundary energy information to locate the hand region accurately, then the moment method will be employed to locate the hand palm center. Hand gesture recognition can be separated into 2 step: firstly, the hand posture recognition: we employ the parallel NNs to deal with problem of hand posture recognition, pattern of a hand posture can be extracted by utilize the fitting ellipses method, which separates the detected hand region by 12 ellipses and calculates the white pixels rate in ellipse line. the pattern will be input to the NNs with 12 input nodes, the NNs contains 4 output nodes, each output node out a value within 0~1, the posture is then represented by composed of the 4 output codes. Secondly, the hand gesture tracking and recognition: we employed the Kalman filter to predict the position information of gesture to create the position sequence, distance relationship between positions will be used to confirm the gesture. The simulation have been performed on Windows XP to evaluate the efficiency of the algorithm, for recognizing the hand posture, we used 300 training images to train the recognizing machine and used 200 images to test the machine, the correct number is up to 194. And for testing the hand tracking recognition part, we make 1200 times gesture (each gesture 400 times), the total correct number is 1002 times. These results shows that the proposed gesture recognition algorithm can achieve an endurable job for detecting the hand and its' gesture.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2727-2732
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• 2014

Recently, the researches of object tracking and recognition using Microsoft's Kinect are being actively studied. In this environment human hand detection and tracking is the most basic technique for human computer interaction. This paper proposes a method of improving the accuracy of the detected hand region's boundary in the cluttered background. To do this, we combine the hand detection results using the skin color with the extracted depth image from Kinect. From the experimental results, we show that the proposed method increase the accuracy of the hand region detection than the method of detecting a hand region with a depth image only. If the proposed method is applied to the sign language or gesture recognition system it is expected to contribute much to accuracy improvement.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.389-392
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• 2010

In this paper, it presents to detect location using structural information of hand from the input color images on Webcam and to recognize hand gestures. In this system, based on the skin color, the image changes a binary number and labels. Within each labeled area, we can find the Maximum Inscribed Circle using Voronoi Diagram. This circle can find the center of hand. And the circle extracts hand region from analyzing the ellipse elements to relate Maximum Inscribed Circle. We use the Maximum Inscribed Circle and the ellipse elements as characteristic of hand gesture recognition. In various environments, we cannot recognize the object that have similar colors like the background colors. But the proposed algorithm has the advantage that can be effectively eliminated about it.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.3
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• pp.248-257
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• 2007

This paper presents the control system for driving myoelectric hand prosthesis according to myoelectric signal generated in the human muscle. A surface myoelectric sensor for measuring myoelectric signal is designed a skin interface and a processing circuit according to myoelectric signal output property. The control system consists of two controller for driving dual motor, torque sensor for measuring out torque of motor, slip sensor for detecting slip of torque. The experimental results proved the proposed control system.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1225-1235
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• 2016

This paper presents a method for computer-assisted slide presentation using vision-based gesture recognition. The proposed method consists of a sequence of steps, first detecting a hand in the scene of projector beam, then estimating the smooth trajectory of a hand or a pointing finger using Kalman Filter, and finally interfacing to an application system. Additional slide navigation control includes moving back and forth the pages of the presentation. The proposed method is to help speakers for an effective presentation with natural improved interaction with the computer. In particular, the proposed method of using finger pointing is believed to be more effective than using a laser pointer since the hand, the pointing or finger are more visible and thus can better grab the attention of the audience.

• Smart Media Journal
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• v.4 no.1
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• pp.33-38
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• 2015

In this paper, we propose the methods not only to eliminate ELF(Extremely Low Frequency) EMI(Electro-Magnetic Interference) noice for extending recognition distance, but also to utilize the the PLN for detecting starting instance of a hand gesture using electric potential sensor. First, we measure strength of electric field generated in the smart devices such as TV and phone, and minimize EMI through efficient arrangement of the sensors. Meanwhile, we utilize the 60 Hz PLN to extract the starting point of hand gesture. Thereafter, we eliminate the PLN generated in the smart device and circuit of sensors. And then, we shield the sensors from an electric noise generated from devices. Finally, through analyzing the frequency components according to the gesture of target, we use the low pass filter and the Kalman filter for elimination of remaining electric noise. We analyze and evaluate the proposed ELF-band EMI eliminating method for non-contact remote sensing of the EPS(Electric Potential Sensor). Combined with a detecting technique of gesture starting point, the recognition distance for gestures has been proven to be extended to more than 3m, which is critical for real application.

• Smart Media Journal
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• v.6 no.2
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• pp.26-32
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• 2017

In this paper, we implement a signal-detecting electric circuit based LED lighting control system which is essential in NUI technology using EPIC converting surrounding earth electric field disturbance signals to electric potential signals. We used signal-detecting electric circuits which was developed to extract individual signal for each EPIC sensor while conventional EPIC-based development equipments provide limited forms of signals. The signals extracted from our developed circuit contributed to better performance as well as flexiblity in processes of feature extracting stage and pattern recognition stage. We designed a system which can control the brightness and on/off of LED lights with four hand gestures in order to justify its applicability to real application systems. We obtained faster pattern classification speed not only by developing an instruction system, but also by using interface control signals.