• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.937-945
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• 2014

Multi-modal biometric system can use another biometric trait in the case of having deficiency at a biometric trait. It also has an advantage of improving the performance of personal identification by using multiple biometric traits, so studies on new biometric traits have continuously been performed. The inner face of finger is a relatively new biometric trait. It has two major features of knuckle lines and wrinkles, which can be used as discriminative features. This paper proposes a finger identification method based on displacement vector to effectively process some variation appeared in contactless hand image. At first, the proposed method produces displacement vectors, which are made by connecting corresponding points acquired by matching each pair of local block. It then recognize finger by measuring the similarity among all the detected displacement vectors. The experimental results using pubic CASIA hand image database show that the proposed method may be effectively applied to personal identification.

• Journal of Acupuncture Research
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• v.32 no.2
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• pp.147-167
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• 2015

Objectives : The aim of this study is to summarise pattern-identification of shoulder pain based on the classics of oriental medicine, current literature and domestic papers. Methods : The materials selected were sourced from the classics of oriental medicine, current literature and domestic papers which contained data related to pattern-identification of shoulder pain. The pattern-identifications were compared to determine the similarities, and these were classified. Results : Thirty-five studies were reviewed, and thirty-seven pattern-identifications were collated. These were classified into the following groups: wind-cold-dampness group(n = 8), blood stasis group(n = 3), phlegm group(n = 7), dual deficiency of Qi and blood group(n = 4), deficiency cold group(n = 2), liver-kidney deficiency group(n = 1) and meridian-collateral group(n = 12). Conclusions : On the basis of the classification of pattern-identifications, two groups of pattern-identifications for shoulder pain were suggested. The first group included the pattern-identification associated with a disease-cause, which included the wind-cold-dampness pattern(風寒濕型), blood stasis pattern(瘀血型), phlegm pattern(痰飮型), Qi-blood deficiency pattern(氣血兩虛型), deficiency cold pattern(虛寒型), and liver-kidney deficiency pattern(肝腎虧損型). The second included the pattern-identification associated with the meridian-collateral, which included the hand greater Yin meridian pattern(手太陰經型), hand Yang brightness meridian pattern(手陽明經型), hand lesser Yin meridian pattern(手少陰經型), hand greater Yang meridian pattern(手太陽經型), hand reverting Yin meridian pattern(手厥陰經型), hand lesser Yang meridian pattern(手少陽經型), and foot greater Yang meridian pattern(足太陽經型).

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.114-116
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• 2004

Biometrics consist of technologies that support automatic identification or verification of identity based on behavioral or physical traits. Biometrics can authenticate identities since they measure unique individual characteristics including fingerprints, hand geometry, iris, hand vascular patterns and facial characteristics. we review the state of the hand vascular patterns identification technology and compare other competitive authentication technologies such as cryptography, electronic signature and PKI.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.319-326
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• 2014

According to the increasing mobile security users who have experienced authentication failure by forgetting passwords, user names, or a response to a knowledge-based question have preference for biological information such as hand geometry, fingerprints, voice in personal identification and authentication. Therefore biometric verification of personal identification and authentication for mobile security provides assurance to both the customer and the seller in the internet. Our study focuses on human hand biometric information recognition system for personal identification and personal Authentication, including its shape, palm features and the lengths and widths of the fingers taken from mobile phone photographs such as iPhone4 and galaxy s2. Our hand biometric information recognition system consists of six steps processing: image acquisition, preprocessing, removing noises, extracting standard hand feature extraction, individual feature pattern extraction, hand biometric information recognition for personal identification and authentication from input images. The validity of the proposed system from mobile phone image is demonstrated through 93.5% of the sucessful recognition rate for 250 experimental data of hand shape images and palm information images from 50 subjects.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.268-284
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• 2017

The dorsal hand vein biometric system developed has a main objective and specific targets; to get an electronic signature using a secure signature device. In this paper, we present our signature device with its different aims; respectively: The extraction of the dorsal veins from the images that were acquired through an infrared device. For each identification, we need the representation of the veins in the form of shape descriptors, which are invariant to translation, rotation and scaling; this extracted descriptor vector is the input of the matching step. The optimization decision system settings match the choice of threshold that allows accepting/rejecting a person, and selection of the most relevant descriptors, to minimize both FAR and FRR errors. The final decision for identification based descriptors selected by the PSO hybrid binary give a FAR =0% and FRR=0% as results.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.247-254
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• 2006

Biometrics are getting more and more attention in recent years for security and other concerns. So far, only fingerprint recognition has seen limited success for on-line security check, since other biometrics verification and identification systems require more complicated and expensive acquisition interfaces and recognition processes. Hand-Geometry can be used for biometric verification and identification because of its acquisition convenience and good performance for verification and identification performance. It could also be a good candidate for online checks. Therefore, this paper proposes a Hand-Geometry recognition system based on geometrical features of hand. From anatomical point of view, human hand can be characterized by its length, width, thickness, geometrical composition, shapes of the palm, and shape and geometry of the fingers. This paper proposes thirty relevant features for a Hand-Geometry recognition system. This system presents verification results based on hand measurements of 20 individuals. The verification process has been tested on a size of $320{\times}240$ image, and result of the verification process have hit rate of 95% and FAR of 0.020.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.187-189
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• 2004

This paper presents the system widely used for extraction of human body recognition system in the field of bio-metric identification. The Human body recognition system is used in many fields. This biological is appled to the human recognition in banking and the access control with security. The important algorithm of the identification software usese hand lines and hand shape geometry. We used the simple algorithm and recognizing the person by their hand image from the input camera. The geometrical characteristics in hand shape such as length of finger to whole hand length thickness of finger to length, etc are used.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.506-511
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• 2004

Biometrics is getting more and more attention in recent years for security and other concerns. So far, only fingerprint recognition has seen limited success for on-line security check, since other biometrics verification and identification systems require more complicated and expensive acquisition interfaces and recognition processes. Hand-Geometry has been used for biometric verification and identification because of its acquisition convenience and good performance for verification and identification performance. Hence, it can be a good candidate for online checks. Therefore, this paper proposes a Hand-Geometry recognition system based on geometrical features of hand. From anatomical point of view, human hand can be characterized by its length, width, thickness, geometrical composition, shapes of the palm, and shape and geometry of the fingers. This paper proposes thirty relevant features for a Hand-Geometry recognition system. However, during experimentation, it was discovered that length measured from the tip of the finger was not a reliable feature. Hence, we propose a new technique based on Genetic Algorithm for extraction of the center of nail bottom, in order to use it for the length feature.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1172-1178
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• 2018

A system that control computer presentations by using the hand motion recognition and identification is proposed. The system recognizes and identifies various types of motion in hand motion, controlls the presentation without additional control devices. To recognize hand movements, it performs a face and hand region detection. Facial area is detected using Haar classifier and hand region is extracted according to skin color information on HSV color model. The face area is used to determine the beginning and end of hand gestures, the size and direction of motion. It recognizes various hand gestures and uses them to control computer presentations according to the hand motion identification rules that are proposed and set horizontal and vertical axes from the face area. It is confirmed that 97.2% recognition rate is obtained in about 1200 hand motion recognition experiments and the proposed algorithm is valid in presentation control.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.467-473
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• 2007

In this paper, we present a position-based robot hand tracking scheme where a pan-tilt camera is controlled such that a robot hand is always shown in the center of an image frame. We calculate the rotation angles of a pan-tilt camera by transforming the coordinate systems. In order to identify the model parameters, we applied two optimization techniques: a nonlinear least square optimizer and a particle swarm optimizer. From the simulation results, it is shown that the considered parameter identification problem is characterized by a highly multimodal landscape; thus, a global optimization technique such as a particle swarm optimization could be a promising tool to identify the model parameters of a robot hand tracking system, whereas the nonlinear least square optimizer often failed to find an optimal solution even when the initial candidate solutions were selected close to the true optimum.