• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.563-572
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• 2006

Advantage that light transmission treatment way of most suitable through skin can investigate light directly in part ar there is difference in ability photoelectricity month by diverse complexion of horn character department which is branch or head of a family outside part of skin and treatment according to various patient can be inappropriate. By result that this research uses color information after search each color ingredient that ingredient of HIS and YIQ that use method, color information to use skin impedance way and color information through skin area ion and difference video to do fixed measuring by light investigation way by skin impedance corresponds to skin color in an experiment though is most universal result according to patient's skin model area detection each single person's skin model through videotex automatically create and because measuring, investigate skin color, energy, wave length, approximately, transmission time, model of most suitable that draw pulse delay and so on and want and special quality, and saved standard of disease treatment pulse modeling by skin impedance, and design and manufacture light investigation pulse modeling system of most suitable by skin subordinate, and constructed suitable treatment pulse database by skin color.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.671-676
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• 2016

Recently, according to the limelight of Fintech, simple payment using biometric at smartphone is widely used. In this paper, we propose a new contactless biometric method using thumb image without additional sensors unlike previous biometrics such as fingerprint, iris, and vein recognition. In our method, length, width, and skin texture information are used as features. For that, illumination normalization, skin region segmentation, size normalization and alignment procedures are sequentially performed from the captured thumb image. Then, correlation coefficient is calculated for similarity measurement. To analyze recognition accuracy, genuine and imposter matchings are performed. At result, we confirmed the FAR of 1.68% at the FRR of 1.55%. In here, because the distribution of imposter matching is almost normal distribution, our method has the advantage of low FAR. That is, because 0% FAR can be achieved at the FRR of 15%, the proposed method is enough to 1:1 matching for payment verification.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.65-71
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• 2014

This paper present the multi-modal user distance estimation system using mono camera and mono microphone basically equipped with a mobile device. In case of a distance estimation method using an image, we is estimated a distance of the user through the skin color region extraction step, a noise removal step, the face and eyes region detection step. On the other hand, in case of a distance estimation method using speech, we calculates the absolute difference between the value of the sample of speech input. The largest peak value of the calculated difference value is selected and samples before and after the peak are specified as the ROI(Region of Interest). The samples specified perform FFT(Fast Fourier Transform) and calculate the magnitude of the frequency domain. Magnitude obtained is compared with the distance model to calculate the likelihood. We is estimated user distance by adding with weights in the sorted value. The result of an experiment using the multi-modal method shows more improved measurement value than that of single modality.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.29-36
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• 2008

In this paper we propose a real-time method to estimate a pointing region from two camera images. In general, a pointing target exists in the face direction when a human points to something. Therefore, we regard the direction of pointing as the straight line that connects the face position with the fingertip position. First, the method extracts two points in the face and the fingertips region by using detecting the skin color of human being. And we used the 3D geometric information to obtain a pointing detection and its region. In order to evaluate the performance, we have build up an ICIGS(Interactive Cinema Information Guiding System) with two camera and a beam project.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.195-198
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• 2013

Recognition and Tracking of interesting object is the significant field in Computer Vision. Mean-Shift algorithm have chronic problems that some errors are occurred when histogram of tracking area is similar to another area. in this paper, we propose to solve the problem. Each algorithm blocks skin color filtering, face detect and Mean-Shift started consecutive order assists better operation of the next algorithm. Avoid to operations of the overhead of tracking area similar to a histogram distribution areas overlap only consider the number of white pixels by running the Viola-Jones algorithm, simple arithmetic increases the convergence of the Mean-Shift. The experimental results, it comes to 78% or more of white pixels in the Mean-Shift search area, only if the recognition of the face area when it is configured to perform a Viola-Jones algorithm is tracking the object, was 100 percent successful.

• Journal of the Korea Society of Computer and Information
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• v.20 no.5
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• pp.13-20
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• 2015

In this paper, we propose an algorithm that can recognize not only the number of stretched fingers but also determination of attached fingers for extracting features required for hand gesture recognition. The proposed algorithm detects the hand area in the input image by the skin color range filter based on a color model and labeling, and then recognizes various hand gestures by extracting the number of stretched fingers and determination of attached fingers using curvature information extracted from outlines and feature points. Experiment results show that the recognition rate and the frame rate are similar to those of the conventional algorithm, but the number of gesture cases that can be defined by the extracted characteristics is about four times higher than the conventional algorithm, so that the proposed algorithm can recognize more various gestures.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.15-22
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• 2005

In this paper, we propose a face recognition system by using the CCD color image. We first get the face candidate image by using YCbCr color model and adaptive skin color information. And we use it initial curve of active contour model to extract face region. We use the Eye map and mouth map using color information for extracting facial feature from the face image. To obtain center point of Log-polar image, we use extracted facial feature from the face image. In order to obtain feature vectors, we use extracted coefficients from DCT and wavelet transform. To show the validity of the proposed method, we performed a face recognition using neural network with BP learning algorithm. Experimental results show that the proposed method is robuster with higher recogntion rate than the conventional method for the rotation and scale variant.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.39-47
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• 2010

A research of image-based articulated pose estimation has some problems such as detection of human feature, precise pose estimation, and real-time performance. In particular, various methods are currently presented for recovering many joints of human body. We propose the novel numerical inverse kinematics improved with the UKF(unscented Kalman filter) in order to estimate the human pose in real-time. An existing numerical inverse kinematics is required many iterations for solving the optimal estimation and has some problems such as the singularity of jacobian matrix and a local minima. To solve these problems, we combine the UKF as a tool for optimal state estimation with the numerical inverse kinematics. Combining the solution of the numerical inverse kinematics with the sampling based UKF provides the stability and rapid convergence to optimal estimate. In order to estimate the human pose, we extract the interesting human body using both background subtraction and skin color detection algorithm. We localize its 3D position with the camera geometry. Next, through we use the UKF based numerical inverse kinematics, we generate the intermediate joints that are not detect from the images. Proposed method complements the defect of numerical inverse kinematics such as a computational complexity and an accuracy of estimation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.56-63
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• 2007

In this paper, an eye tracking method is presented using a neural network (NN) and mean-shift algorithm that can accurately detect and track user's eyes under the cluttered background. In the proposed method, to deal with the rigid head motion, the facial region is first obtained using skin-color model and con-nected-component analysis. Thereafter the eye regions are localized using neural network (NN)-based tex-ture classifier that discriminates the facial region into eye class and non-eye class, which enables our method to accurately detect users' eyes even if they put on glasses. Once the eye region is localized, they are continuously and correctly tracking by mean-shift algorithm. To assess the validity of the proposed method, it is applied to the interface system using eye movement and is tested with a group of 25 users through playing a 'aligns games.' The results show that the system process more than 30 frames/sec on PC for the $320{\times}240$ size input image and supply a user-friendly and convenient access to a computer in real-time operation.

• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1439-1448
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• 2005

In this paper, after similarity of color information in above toro and geometry position analysis of important characteristic information in face and abstraction object that is inputted detects face area using comparison, describe about method to do user certification using ratio information and hair spring degree. Face abstraction algorithm that use color information has comparative advantages than face abstraction algorithm that use form information because have advantage that is not influenced facial degree or site etc. that tip. Because is based on color information, change of lighting or to keep correct performance because is sensitive about color such as background similar to complexion is difficult. Therefore, can be used more efficiently than method to use color information as that detect characteristic information of eye and lips etc. that is facial importance characteristic element except color information and similarity for each object achieves comparison. This paper proposes system that eye and mouth's similarity that calculate characteristic that is ratio red of each individual after divide face by each individual and is segmentalized giving weight in specification calculation recognize user confirming similarity through search. Could experiment method to propose and know that the awareness rate through analysis with the wave rises.