• 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 Society of Manufacturing Process Engineers
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• v.10 no.5
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• pp.51-57
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• 2011

The lightweight and compact actuator with high power is required to perform motion with multiple degrees of freedom. To reduce the size and inertia of a robot manipulator, the mechanical transmission system is used. The shape memory alloy(SMA) is similar to the muscle-tendon-bone network of a human hand. However, there are some drawback and nonlinearity, such as the hysteresis and the stress dependence. In this paper, the design of the underactuated robot hand is studied. The 3-finger dexterous hand is driven by the SMA actuator using segmental mechanism. This digital approach enables to overcome the nonlinearity of SMA wire. The translational displacement of SMA actuator required to bend a phalanx of the underactuated robot hand is estimated and the bending angle of the underactuated robot hand according to input displacement of SMA actuator is predicted by the multi-body dynamic analysis.

• Journal of the Korean Home Economics Association
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• v.43 no.8 s.210
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• pp.115-122
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• 2005

The hand performs functions such as grabbing and other movements. In order to accomplish these movements in various kinds of operational environments, appropriate gloves must be worn to protect your hands. Choosing the appropriate type of glove is very important when wearing gloves in these types of operational environments. The reasons one wears gloves varies depending on age and gender. Unmarried women in their early twenties, for example, occasionally wear gloves for decoration rather than for functional reasons. However, previous studies examined a range of topics, and as such investigations dealing with specific body shape and demands of consumer are needed. Therefore in this study, the hands of unmarried women ranging in age from 20 to 24 were measured and hand shape types were analyzed in order to present basal data which can be used to help design improved glove patterns and produce appropriate, functional gloves. A total of 261 Korean women were measured. Fifty-seven right hand dimensions were measured and five dimensions from both hands were measured. Six factors were identified through factor analysis and those factors constituted $73.259\%$ of total variance. Two clusters of hand shapes were categorized using 6 factor scores by cluster analysis. Type 1 hand shape is defined as long hands with small width, girth, and thickness, long and thin fingers, and high vertical palm height. Type 2 hand shape is defined as short hands with large width, girth and thickness, short fingers, thick knuckles, and short vertical palm height. The characteristics of type 1 and 2 hand shapes are similar to women's hand type classification results from previous reports, but there was a significant difference in subject distribution by type. Therefore, standard data on hand shapes should be produced by developing measuring instruments and selling more accurate standard measuring points. By doing this it could help in the development of improved glove patterns, and also aid in planning production based on hand type.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.5
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• pp.1-9
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• 2010

Generally, dynamic hand gesture recognition is formed through preprocessing step, hand tracking step and hand shape detection step. In this paper, we present advanced dynamic hand gesture recognizing method that improves performance in preprocessing step and hand shape detection step. In preprocessing step, we remove noise fast by using dynamic table and detect skin color exactly on complex background for controling skin color range in skin color detection method using YCbCr color space. Especially, we increase recognizing speed in hand shape detection step through detecting Start Image and Stop Image, that are elements of dynamic hand gesture recognizing, using Guideline. Guideline is edge of input hand image and hand shape for comparing. We perform various experiments with nine web-cam video clips that are separated to complex background and simple background for dynamic hand gesture recognition method in the paper. The result of experiment shows similar recognition ratio but high recognition speed, low cpu usage, low memory usage than recognition method using learning exercise.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.28-36
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• 2013

This study proposed a robust detection algorithm. It detects hands more stably with respect to changes in light and rotation for the identification of a hand shape. Also it satisfies both efficiency of calculation and the function of detection. The algorithm proposed segmented the hand area through pre-processing using a hand shape as input information in an environment with a single camera and then identified the shape using a Self Organized Feature Map(SOFM). However, as it is not easy to exactly recognize a hand area which is sensitive to light, it has a large degree of freedom, and there is a large error bound, to enhance the identification rate, rotation information on the hand shape was made into a database and then a principal component analysis was conducted. Also, as there were fewer calculations due to the fewer dimensions, the time for real-time identification could be decreased.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.585-588
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• 2008

This paper proposes hand gesture recognition using shape similarity method. For this, we require two steps which are aquisition of Hand area and similarity evaluation. First step is extracting hand area using YCbCr color spare. Then eliminate noise through filter and analyzing histogram. For doing this, we ran measure similarity of hand gesture by applying TSR after getting contour. Finally, we utilize shape similarity for recognizing of hand gesture.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.1
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• pp.22-31
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• 2004

This paper deals with the dynamic hand gesture recognition based on computer vision using neural networks. This paper proposes a global search method and a local search method to recognize the hand gesture. The global search recognizes a hand among the hand candidates through the entire image search, and the local search recognizes and tracks only the hand through the block search. Dynamic hand gesture recognition method is based on the skin-color and shape analysis with the invariant moment and direction information. Starting point and ending point of the dynamic hand gesture are obtained from hand shape. Experiments have been conducted for hand extraction, hand recognition and dynamic hand gesture recognition. Experimental results show the validity of the proposed method.

• International Journal of Human Ecology
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• v.8 no.2
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• pp.99-106
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• 2007

In this study, the mechanical properties related to the fabric appearance of well being functional bamboo knitted fabric before and after loess dyeing were evaluated. The mechanical properties of fabrics were measured by KES-F system, that is, shape retention, draping, wrinkle recovery, compression property, and surface properties, and total hand value of three types of knitted fabric, 100% bamboo, 100% cotton, and bamboo / cotton blend (60 / 40) were evaluated before and after loess dyeing. As a result, it was found that appearance density, shape retention, and drape coefficient of cotton knitted fabric were greater than those of bamboo knitted fabric. After loess dyeing, shape retention and drape coefficient, wrinkle recovery of bamboo knitted fabric improved and WC/C and MMD/SMD decreased. According to THV, the hand of bamboo/cotton blend knit is the best among three samples by compensation the weak properties of the two fiber. Therefore, loess dyeing seemed to be a good method for improving shape retention and hand value of 100% bamboo and bamboo blended fabric.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.992-995
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• 2003

A haptic device operated by the user's hand can receive information on position and orientation of the hand and display force and moment generated in the virtual environment to the hand. For realistic haptic display, the detailed information on collision between objects is necessary. In the past, the point-based graphic environment has been used in which the end effector of a haptic device was represented as a point and the interaction of this point with the virtual environment was investigated. In this paper, the shape-based graphic environment is proposed in which the interaction of the shape with the environment is considered to analyze collision or contact more accurately. To this end. the so-called Gilbert-Johnson-Keerthi (GJK) algorithm is adopted to compute collision points and collision instants between two shapes in the 3-D space. The 5- DOF haptic hand controller is used with the GJK algorithm to demonstrate a peg-in-hole operation in the virtual environment in conjunction with a haptic device. It is shown from various experiments that the shape-based representation with the GJK algorithm can provide more realistic haptic display for peg-in-hole operations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.1931-1940
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• 2014

In this paper, we propose a new hand shape recognition algorithm based on the geometric features using the convex-hull from the depth image acquired by Kinect system. Kinect is a camera providing a depth image and user's skeleton information and used for detecting hand region. In the proposed algorithm, hand region is detected in a depth image acquired by Kinect and convex-hull of the region is found. Boundary points caused by noise and unnecessary points for recognition are eliminated in the convex-hull that changes depending on hand shape. Hand shape is recognized by the sum of internal angle of a polygon that is matched with convex-hull reconstructed with selected boundary points. Through experiments, we confirm that proposed algorithm shows high recognition rate not only for five models but also those cases rotated.