• Journal of the Korean Society for Precision Engineering
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• v.28 no.9
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• pp.1011-1017
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• 2011

Servo control loops are a core part in the control architecture of machine tools. Servo control loops manage acceleration, velocity and position of all the axes in a machine tool based on commands. The performance of servo control loops sets the basis for quality of production paris and cycle time reduction. First, this paper presents a general control architecture of machine tools and several control schemes in literature, which can be applicable to machine tools control; including Zero Phase Error Tracking Control (ZPETC) and Cross Coupling Control (CCC). After that, modem control strategies to mitigate the problem of high speed machining are reviewed. In high speed machining, high accelerations excite the machine structure up to high frequencies, thereby exciting the structure's modes of vibration. These structural vibrations need to be damped if accurate positioning or trajectory following is required. Input shaping is an attractive option in dealing with structural vibrations. The advantages and drawbacks of using input shaping technique for machine tools are discussed in detail.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.2
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• pp.168-175
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• 2011

Contouring accuracy of CNC machine tools is very important for high-speed and high-precision machining. In particular, large contour error may occur during corner tracking. In order to reduce the corner contouring error, acceleration and deceleration control or tool-path planning methods have been suggested. However, they do not directly control the corner contouring error. In the meantime, network servo systems are widely used because of their easiness of building and cost effectiveness. Communication latency between the master controller and servo drives, however, may deteriorate contouring accuracy especially during corner tracking. This paper proposes a control strategy that can accurately calculate and directly control the corner contouring error. A prediction control is combined with the above control to cope with communication latency. The proposed control method is evaluated through computer simulation and experiments. The results show its validity and usefulness.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.135-136
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• 2017

When driving at night time environment, the whole body of transports does not visible to us. Due to lack of light conditions, there are only two options, which is clearly visible their taillights and break lights. To improve the recognition correctness of vehicle detection, we present an approach to vehicle detection and tracking using finding contour of the object on binary image at night time. Bilateral filtering is used to make more clearly on threshold part. To remove unexpected small noises used morphological opening. In verification stage, paired tail lights are tracked during their existence in the ROI. The accuracy of the test results for vehicle detection is about 93%.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.77.4-77
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• 2001

The quality of agricultural products is classified with various factors which are measured and determined by destructive and/or nondestructive method. NIR spectrum analysis method is used to determine internal qualities such as a brix and an acidity. CCD color camera is used to measure external quality like color and a size of fruit. today, nondestructive methods are widely researched. The quality and the garde of fruit loaded into a cup automatically and measured in real time by camera and NIR system is determined by internal and external factors. This paper proposes modified boundary tracking algorithm which detects the contour of fruit´s color image and make chain code faster than conventional method ...

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.86-92
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• 2007

A discrete dynamic model for tracking feature points in 2D images is developed. Conventional snake approaches deform a contour to lock onto features of interest within an image by finding a minimum of its energy functional, composed of internal and external forces. The neighborhood around center snaxel is a space matrix, typically rectangular. The structure of the model proposed in this paper is a set of connected vertices. Energy model is designed for its local minima to comprise the set of alternative solutions available to active process. Block on tracking is one dimension, line type. Initial starting points are defined to the satisfaction of indent states, which is then automatically modified by an energy minimizing process. The track is influenced by curvature constraints, ascent/descent or upper/lower points. The advantages and effectiveness of this layer approach may also be applied to feature points tracking of digital image whose pixels have one directional properties with high autocorrelation between adjacent data lines, vertically or horizontally. The test image is the ultrasonic carotid artery image of human body, and we have verified its effect on intima/adventitia starting points tracking.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.1-8
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• 2000

This paper describes an algorithm for semantic video object tracking using semi automatic method. In the semi automatic method, a user specifies an object of interest at the first frame and then the specified object is to be tracked in the remaining frames. The proposed algorithm consists of three steps: object boundary projection, uncertain area extraction, and boundary refinement. The object boundary is projected from the previous frame to the current frame using the motion estimation. And uncertain areas are extracted via two modules: Me error-test and color similarity test. Then, from extracted uncertain areas, the exact object boundary is obtained by boundary refinement. The simulation results show that the proposed video object extraction method provides efficient tracking results for various video sequences compared to the previous methods.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.30-34
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• 1998

Path Planning is one of the important fields in robot technologies. Local path planning may be done in on-line modes while recognizing an environment of robot by itself. In dynamic environments to obtain fluent information for environments vision system as a sensing equipment is a one of the most necessary devices for safe and effective guidance of robots. If there is a predictor that tells what future sensing outputs will be, robot can respond to anticipated environmental changes in advance. The tracking of obstacles has a deep relationship to the prediction for safe navigation. We tried to deal with active contours, that is snakes, to find out the possibilities of stable tracking of objects in image plane. Snakes are defined based on energy functions, and can be deformed to a certain contour form which would converge to the minimum energy states by the forces produced from energy differences. By using point algorithm we could have more speedy convergence time because the Brent's method gives the solution to find the local minima fast. The snake algorithm may be applied to sequential image frames to track objects in the images by these characteristics of speedy convergence and robust edge detection ability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2429-2434
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• 2010

In this paper, we propose a method to extract and analyze palm line with fuzzy method. In order to extract the palm part, we transform the original RGB color space to YCbCr color space and extract sin colors ranging Y:65-255, Cb:25-255, Cr:130-255 and use it as a threshold. Possible noise is removed by 8-directional contour tracking algorithm and morphological characteristic of the palm. Then the edge is extracted from that noise-free image by stretching method and sobel mask Then the fuzzy binarization algorithm is applied to remove any minute noise so that we have only the palm lines and the boundary of the hand. Since the palm line reading is done with major lines, we use the morphological characteristics of the analyzable palm lines and fuzzy inference rules. Experiment verifies that the proposed method is better in visibility and thus more analyzable in palm reading than the old method.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.119-128
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• 2002

This paper proposes an efficient recognition method of car license plate from the car images by using both the dynamical thresholding and the neural network with enhanced learning algorithm. The car license plate is extracted by the dynamical thresholding based on the structural features and the density rates. Each characters and numbers from the p]ate is also extracted by the contour tracking algorithm. The enhanced neural network is proposed for recognizing them, which has the algorithm of combining the modified ART1 and the supervised learning method. The proposed method has applied to the real-world car images. The simulation results show that the proposed method has better the extraction rates than the methods with information of the gray brightness and the RGB, respectively. And the proposed method has better recognition performance than the conventional backpropagation neural network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.1052-1061
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• 2003

In this paper, we propose the car plate recognition using SOM algorithm and describe the parking control system using the proposed car plate recognition. The recognition of car plate was investigated by means of the SOM algorithm. The morphological information of horizontal and vertical edges was used to extract a plate area from a car image. In addition, the 4-direction contour tracking algorithm was applied to extract the specific area, which includes characters from an extracted plate area. The extracted characteristic area was recognized by using the SOM algorithm. In this paper, 50 car images were tested. The extraction rate obtained by the proposed extraction method showed better results than that from the color information of RGB and HSI, respectively. And the car plate recognition using SOM algorithm was very efficient. We develop the parking control system using the proposed car plate recognition that shows performance improvement by the experimental results.