• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.14-20
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• 2006

In recent year, as the robot technology is developed, the researches on the artificial muscle actuator that enables robot to move dexterously like biological organ become active. Actuators are key technologies underpinning robotics. Breakthroughs in actuator technology, particular in terms of power-to-weight ratio, or energy-density, will have significant impacts upon the design and control of robotic system. In this paper, a new approach to design and control of shape memory alloy(SMA) actuator is presented to drive the robot hand. SMA wire is divided into many segments and their thermal states of the SMA are controlled individually in a binary manner. This control manner will reduce the hysteresis that the SMA material has and it becomes the fundamental technology to develop the anthropomorphic robot hand. In this paper, the mechanism In the digital step motor of the shape memory alloy that is driven by the segmented binary control, which is a new control technique, is studied. This SMA digital step actuator applies for the robot hand and the driving mechanism of the robot hand is investigated.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.144-149
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• 2005

In recent years, as the robot technology is developed the researches on the artificial muscle actuator that enable robot to move dextrously like biological organ become active. The widely used materials for artificial muscle are the shape memory alloy and the electroactive polymer. These actuators have the higher energy density than the electromechanical actuator such as motor. However, there are some drawbacks for actuator. SMA has the hysterical dynamic characteristics. In this paper the segmented binary control for reducing the hysteresis of SMA is proposed and the simulation of anthropomorphic robotic hand is performed using ADAMS.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.310-313
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• 2005

In recent years, as the robot technology is developed, the researches on the artificial muscle actuator that enable robot to move dexterously like biological organ become active. The widely used materials for artificial muscle are the shape memory alloy and the electro-active polymer. These actuators have the higher energy density than the electro-mechanical actuator such as motor. However, there are some drawbacks for actuator. SMA has the hysterical dynamic characteristics. In this paper, the simulation of anthropomophic robotic hand is performed using ADAMS and the segmented binary control for reducing the hysteresis of SMA is proposed. SMA is controlled by thermo-electric module. The relations between the force and the hysteresis are developed to verify the validity of the suggested method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1232-1235
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• 2005

In recent years, as the robot technology is developed the researches on the artificial muscle actuator that enable robot to move dextrously like biological organ become active. The widely used materials for artificial muscle are the shape memory alloy and the electroactive polymer. These actuators have the higher energy density than the electromechanical actuator such as motor. However, there are some drawbacks for actuator. SMA has the hysterical dynamic characteristics. In this paper the segmented binary control for reducing the hysteresis of SMA is proposed and the simulation of anthropomorphic robotic hand is performed using ADAMS.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.283-288
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• 2001

In this paper, we proposed a method for extracting facial characteristics of human being in an image. Given a pair of gray level sample images taken with and without human being, the face of human being is segmented from the image. Noise in the input images is removed with the help of Gaussian filters. Edge maps are found of the two input images. The binary edge differential image is obtained from the difference of the two input edge maps. A mask for face detection is made from the process of erosion followed by dilation on the resulting binary edge differential image. This mask is used to extract the human being from the two input image sequences. Features of face are extracted from the segmented image. An effective recognition system using the discrete wave let transform (DWT) is used for recognition. For extracting the facial features, such as eyebrows, eyes, nose and mouth, edge detector is applied on the segmented face image. The area of eye and the center of face are found from horizontal and vertical components of the edge map of the segmented image. other facial features are obtained from edge information of the image. The characteristic vectors are extrated from DWT of the segmented face image. These characteristic vectors are normalized between +1 and -1, and are used as input vectors for the neural network. Simulation results show recognition rate of 100% on the learned system, and about 92% on the test images.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.1
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• pp.56-63
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• 2008

This paper describes a 12 bit 1GS/s current mode segmented DAC for WCDMA communication. The proposed circuit in this paper employes segmented structure which consists of 4bit binary weighted structure in the LSB and 4bit thermometer decoder structure in the mSB and MSB. The proposed DAC uses delay time compensation circuits in order to suppress performance decline by delay time in segmented structure. The delay time compensation circuit comprises of phase frequency detector, charge pump, and control circuits, so that suppress delay time by binary weighted structure and thermometer decoder structure. The proposed DAC uses CMOS $0.18{\mu}m$ 1-poly 6-metal n-well process, and measured INL/DNL are below ${\pm}0.93LSB/{\pm}0.62LSB$. SFDR is approximately 60dB and SNDR is 51dB at 1MHz input frequency. Single DAC's power consumption is 46.2mW.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.3
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• pp.224-230
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• 2002

In this paper, a counting algorithm hybridized with an adaptive automatic thresholding method based on Otsu's method and the algorithm that elongates markers obtained by the well-known watershed algorithm is proposed to enhance the exactness of the microcell counting in microscopic images. The proposed counting algorithm can be stated as follows. The transformed full image captured by CCD camera set up at microscope is divided into cropped images of m$\times$n blocks with an appropriate size. The thresholding value of the cropped image is obtained by Otsu's method and the image is transformed into binary image. The microbial cell images below prespecified pixels are regarded as noise and are removed in tile binary image. The smoothing procedure is done by the area opening and the morphological filter. Watershed algorithm and the elongating marker algorithm are applied. By repeating the above stated procedure for m$\times$n blocks, the m$\times$n segmented images are obtained. A superposed image with the size of 640$\times$480 pixels as same as original image is obtained from the m$\times$n segmented block images. By labeling the superposed image, the counting result on the image of microbial cells is achieved. To prove the effectiveness of the proposed mettled in counting the microbial cell on the image, we used Acinetobacter sp., a kind of ammonia-oxidizing bacteria, and compared the proposed method with the global Otsu's method the traditional watershed algorithm based on global thresholding value and human visual method. The result counted by the proposed method shows more approximated result to the human visual counting method than the result counted by any other method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.329-330
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• 2006

The research and development of an actuator are accelerating in the robotics industry. The electricity polymer and SMA actuator are designed simply and are produced a lot of forces per unit volume. Their motions are similar to human's motion, But the repeatability of the electricity polymer actuator is lower. The reaction velocity of the SMA actuator is slow and the travel is short. In this paper, the dynamic characteristic of the segmented SMA is studied. The SMA wire is divided by using the Thermo-electric module(TEM) to control each of segments independently. The MOSFET circuit is used to supply constant currents fer the Thermo-electric module(TEM). The hysteresis and displacement of the SMA wire according to load are measured.

• Journal of Information Display
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• v.3 no.2
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• pp.19-25
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• 2002

In this paper, a new target extraction algorithm is proposed, in which the coordinates of target are obtained adaptively by using the difference image information and the optical BPEJTC(binary phase extraction joint transform correlator) with which the target object can be segmented from the input image and background noises are removed in the stereo vision system. First, the proposed algorithm extracts the target object by removing the background noises through the difference image information of the sequential left images and then controlls the pan/tilt and convergence angle of the stereo camera by using the coordinates of the target position obtained from the optical BPEJTC between the extracted target image and the input image. From some experimental results, it is found that the proposed algorithm can extract the target object from the input image with background noises and then, effectively track the target object in real time. Finally, a possibility of implementation of the adaptive stereo object tracking system by using the proposed algorithm is also suggested.

• Journal of Bio-Environment Control
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• v.1 no.1
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• pp.37-51
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• 1992

Quantizing and extracting visual features of mushroom(Lentinus edodes L.) are crucial to the sorting and grading automation, the growth state measurement, and the dried performance indexing. A computer image processing system was utilized for the extraction and measurement of visual features of front and back sides of the mushroom. The image processing system is composed of the IBM PC compatible 386DK, ITEX PCVISION Plus frame grabber, B/W CCD camera, VGA color graphic monitor, and image output RGB monitor. In this paper, an automatic thresholding algorithm was developed to yield the segmented binary image representing skin states of the front and back sides. An eight directional Freeman's chain coding was modified to solve the edge disconnectivity by gradually expanding the mask size of 3$\times$3 to 9$\times$9. A real scaled geometric quantity of the object was directly extracted from the 8-directional chain element. The external shape of the mushroom was analyzed and converted to the quantitative feature patterns. Efficient algorithms for the extraction of the selected feature patterns and the recognition of the front and back side were developed. The developed algorithms were coded in a menu driven way using MS_C language Ver.6.0, PC VISION PLUS library fuctions, and VGA graphic functions.