• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.341-344
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• 1997

The higher precision in manufacturing field is demanded, the more accurate servo controller is needed. To achieve the high precision, Koren proposed the cross-coupled control (CCC) method. The objective of the CCC is reducing the contour error rather than decreasing the individual axial error. The performance of CCC depends on the contour error model. In this paper we propose a new contour error model which utilizes contour error vector based on parametric curve interpolator. The experimental results show that the new CCC is more accurate than the variable-gain CCC during free-form curve motion.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.4
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• pp.17-22
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• 2002

This paper used an active contour model which was based on level set algorithms and bidirectional curve evolution theory in order to track the shape of the heart acting continuously. Most active contour models would be failed in boundary extraction because of their unstable movement in the edge gap locations. In this paper, we suggest a new active contour model using only image intensity value and additional constraint needed for stable extraction. Our model was successfully run on either shape extraction or object tracking without any position constraints of initial curve. Also demonstrated stable movements and showed good results at weak or missing boundary locations.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.34-40
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• 2008

This paper presents a vision based walking robot control system using hand shape recognition. To recognize hand shapes, the accurate hand boundary needs to be tracked in image obtained from moving camera. For this, we use an active contour model-based tracking approach with mean shift which reduces dependency of the active contour model to location of initial curve. The proposed system is composed of four modules: a hand detector, a hand tracker, a hand shape recognizer and a robot controller. The hand detector detects a skin color region, which has a specific shape, as hand in an image. Then, the hand tracking is performed using an active contour model with mean shift. Thereafter the hand shape recognition is performed using Hue moments. To assess the validity of the proposed system we tested the proposed system to a walking robot, RCB-1. The experimental results show the effectiveness of the proposed system.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.844-847
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• 1996

This paper describes the servo position control for the 2-axis positioning table the servo controller consists of conventional feedback loops, disturbance observer. To reduce the contour error, which occurs in the multi-dimensions machines, cross-coupled controller(CCC) is suggested. A weak point of the CCC is their low effectiveness in dealing with arbitrary nonlinear contour such as circles and parabolas. This paper introduces a new nonlinear CCC that is based on control gains that vary during the contour movement The gains of CCC and adjusted in real time according to the shape of nonlinear contour. The feedback controller based on the disturbance observer compensated for external disturbance, plant uncertainty and bad effectiveness by friction model. Suggested servo controller which improve the contouring accuracy, apply to the 2-axis system. Simulation results on 2-axis table verify the effectiveness of the proposed servo controller.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.289-298
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• 2009

Active Contour Model, that is, Snake algorithm is effective for detection and tracking the objects. However, this algorithm has some drawbacks; numerous parameters must be designed(weighting factors, iteration steps, etc.), a reasonable initialization must be available and moreover suffers from numerical instability. Therefore we propose a novel Energy Corrected Snake(ECS) algorithm which improved on external energy of Snake algorithm for detection and tracking the moving object more effectively. The proposed algorithm uses the difference image, getting when the object is moving. It copies four direction images from the difference image and performs the accumulating compute to erasing image noise, so that it gets external energy steadily. Then external energy united with contour that is computed by internal energy. Consequently we can detect and track the moving object more speedily and easily. To show the effectiveness of the proposed algorithm, we experiment on 3 situations. The experimental results showed that the proposed algorithm outperformed by 6$\sim$9% of detection rate and 6$\sim$11% of tracker detection rate compared with the Snake algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.1 no.1
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• pp.238-248
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• 1998

This paper presents an image analysis method for mearurement correction using the object contour based analysis, which measure the shape features of the imitation missile object. The image analysis is divided into object's tilting angle analysis and corner points detection. The tilting angle is calculated by edge extracting the region-of-interest image and by Radon transform it. The corner points are obtained by contour tracking of binary image and its curvature data processing and analysis. The ability of this presented method is simulated and evaluated by the results of accuracy testing.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.435-437
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• 1998

In this productive system, it needs to control the each axis motion harmoniously to perform accurately for the manufacturing, transporting and printing. Independent Axis Control usually used for this objection. However, if Independent Axis Control mismatched the parameter of each axis system or in the case of free curve tracking or the case of high speed control, there would be big contour error so that cannot achieve control objection. As a result, there is Contour Control method suggested to supply for this defect. This paper carried modeling of biaxial system and implemented Independent Axis Control & Contouring Control on straight line, circular, and coner path by simulation and experiment. If feedrate increased, contour error growed. In consequence, according to this factor, we introduced contouring controller, so we could find the fact that contour error was reduced more than that of independent axis control about each path.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.11
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• pp.591-598
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• 2000

In this thesis, a digital tracking controller is proposed for multi-axis position control system. Tracking and contouring error exist when the machine tool moves along a trajectory in multi-axis system. The proposed scheme enhances the tracking and contouring performance by reducing the errors. Also, an optimal tracking controller reduces the tracking error by the state feedback and the feedforward compensator reduces the effects of a nonlinear disturbance such as friction or dead zone. The proposed control scheme reduces the contour error which occurred when the tool tracks the reference trajectory. Finally, the performance of the proposed controller is exemplified by some simulations and by applying the real XY servo system.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.1-18
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• 2003

The automatic recognition of transport containers using image processing is very hard because of the irregular size and position of identifiers, diverse colors of background and identifiers, and the impaired shapes of identifiers caused by container damages and the bent surface of container, etc. We proposed and evaluated the novel recognition algorithm of container identifiers that overcomes effectively the hardness and recognizes identifiers from container images captured in the various environments. The proposed algorithm, first, extracts the area including only all identifiers from container images by using CANNY masking and bi-directional histogram method. The extracted identifier area is binarized by the fuzzy binarization method newly proposed in this paper and by applying contour tracking method to the binarized area, container identifiers which are targets of recognition are extracted. We proposed and applied the ART2-based RBF network for recognition of container identifiers. The results of experiment for performance evaluation on the real container images showed that the proposed algorithm has more improved performance in the extraction and recognition of container identifiers than the previous algorithms.

• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.213-217
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• 2008

This paper proposes a novel method for the recognition of passports based on the CDM(Conditional Dilation Morphology) masking and the ART2-based RBF neural networks. For the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an ART2-based hybrid network that adapts the ART2 network for the middle layer. This network is applied to the recognition of individual codes. The experiment results showed that the proposed method has superior in performance in the recognition of passport.