• Journal of Broadcast Engineering
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• v.23 no.5
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• pp.656-668
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• 2018

VR (Virtual Reality) is one of the important research topics in the field of multimedia application system. The quality of the visual data composed from multiple pictures depends on the performance of stitching technique. The stitching module consists of feature extraction, mapping of those, warping, seam finding, and blending. In this paper, we proposed a preprocessing scheme to provide the efficient mask for seam finder. Incorporating of the proposed mask removes the distortion, such as ghost and blurring, in the stitched image. The simulation results show that the proposed algorithm outperforms other conventional techniques in the respect of the subjective quality and the computational complexity.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.729-733
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• 1997

Due to the variety of disturbance, it is not ease to accomplish the in-process detection of weld line with non-contact sensor. To get around this difficulties problem develop an automatic seam tracking weld system, the reliable signal processing algorithm has been recommanded. In this research, laser displacement sensor is applied as a seam finder in the automatic tracking system. The sensor is controlled by a dc servo motor which is mounted at X-Y moving table. X-Y moving table manipulated by an ac servo motor controls the position and velocity of the welding torch. First, X-Y table moves to Y-axis to search the welding joint feature before starting the welding, and welding joint is from the scanning data and weighting factor for each other. Second, weld line is determined using proposed signal processing algorithm during welding process. Form the experimental results, we could see the possibility that laser displacement sensor with procesed algorithm can be used as a seam finder in welding process under the severe noise (spatter,arc light etc.) condition

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.680-684
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• 1996

Welding systems cannot adapt to changes in the joint geometry which may occur due to a variety of reason. Automatic seam tracking technigue is essential to adjust the welding torch position in real time as it moves along the seam. Automatic tracking system must keep the welding speed constant unrelation to the change of the welding path. Therefore, the information from the laser displacement sensor must be converted into the input to operate the X-Y table and to rotate the desired torch position by proposed algorithm. In this research, laser displacement sensor is used as a seam finder in the automatic tracking system. X-Y moving table manipulated by ac servo motor controls the position and velocity of the torch-and-sensor part. DC motor controls the position and velocity of the torch. X-Y table controls the position of sensor and relative position of torch is controlled by dc motor which is mounted at sensor-and-torch part. Sensor is always ahead of torch to preview the weld line. From the experimental results, we could see the possiblity that the laser displacement sensor can be used as a seam finder in welding process and that the seam tracking system controlled by proposed algorithm is well done.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1096-1112
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• 2019

The cameras generating 360 VR image are too expensive to be used publically. To overcome this problem, we propose a way to use smart phones instead of VR camera, where more than 100 pictures are taken by smart phone and are stitched into a 360 VR image. In this scenario, when moving objects are in some of the pictures, the stitched 360 VR image has various degradations, for example, ghost effect and mis-aligning. In this paper, we proposed an algorithm to modify the seam finding algorithms, where the saliency map in ROI is generated to check whether the pixel belongs to visually salient objects or not. Various simulation results show that the proposed algorithm is effective to increase the quality of the generated 360 VR image.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.896-913
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• 2018

Seam finding algorithm is one of the most important techniques to construct the high quality 360 VR image. We found that some degradations, such as ghost effect, are generated when the conventional seam finding algorithms (for examples, Voronoi algorithm, Dynamic Programming algorithm, Graph Cut algorithm) are applied, because those make the inefficient masks which cross the body of main objects. In this paper, we proposed an advanced seam finding algorithm providing the efficient masks which go through background region, instead of the body of objects. Simulation results show that the proposed algorithm outperforms the conventional techniques in the viewpoint of the quality of the stitched image.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.775-778
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• 1996

In this research, the robustness of a seam tracking for the automatic welding system is studied. The laser displacement sensor is used as a seam finder. X-Y moving table drived by ac servo motor controls the position and velocity of the torch-and-sensor part. However, dc servo motor is used to control the position and velocity of the torch. The sensor locates ahead of torch to preview the weld line, and brings about the inaccuracy on the torch tracking. To enhance the robustness on this system against the influence of disturbances and model uncertainty, H$\_$.inf./ control is applied to the angular motion of torch. The simulation shows that the tracking accuracy improved significantly. Also, experimental results give a good performance of H$\_$.inf./ control strategy to the automatic seam tracking system for the welding.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.10
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• pp.64-74
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• 2007

Because of the size and environment in the shipbuilding process, the portable type robot is required for the automatic seam tracking. For this reason, the structure of laser sensor should be considered in the initial design step and the coordinate transformation between welding robot and laser sensor, which is joint finder, must be identified exactly and the real time tracking algorithm based on these consideration could be developed. In this research, laser displacement sensor in which its structure is laser beam's vertical projection, is developed to recognize the location of weld joint. In practical applications, however, images of weld joints are often degraded because of the surface specularity or spatter. To overcome the problem, the constrained joint finding algorithm is proposed. In the approach of coordinate conversion rule for the visual feedback control among welding torch, robot body and laser sensor is applied by the same reference point method. In the real time seam tracking algorithms we propose constrained sampling method which uses look ahead distance. The RLS(Recursive Least Square) filter is applied to obtain the smooth tracking path from the sensitive edge data. From the experimental results, we could see the possibility that the developed laser sensor with proposed processing algorithm and real time seam tracking method can be used as a welding under the shipbuilding condition.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.550-555
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• 1993

The aim of this paper is to present the development of visual seam tracking system equipped with visual range finder. The visual range finder, which consists of a CCD camera and a diode laser system with line generating optics, developed to recognize the types of weld joints and detect the location of weld joints. In practical applications, however, images of the weld joints are often degraded due to spatters, are flares, surface specularity, and welding smoke. To overcome the problem, this paper proposes a syntactic approach which is a class of artificial intelligence techniques. In the approach, the type of weld joint is inferred based upon the production rules which are linguiques grammars consisting of a set of line and junction primitives of laser strip image projected on weld joint. The production rules eliminate several noisy primitives to create new primitives through the merging process of primitives. After the recognition of weld joint, arc welding is started and the location of weld joints is repeatedly detected using a spring model-based template matching in which the template model is a by-product of the recognition process of weld joint. To show the effectiveness of the proposed approach a series of experiments-identification and robotic tracking-are conducted for four different types of weld joints.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.218-222
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• 2014

In this paper, we introduce an autonomous calibration method for a 2D laser displacement sensor (e.g. laser vision sensor and laser range finder) by matching a single point on a flat structure. Many arc welding robots install a 2D laser displacement sensor to expand their application by recognizing their environment (e.g. base metal and seam). In such systems, sensing data should be transformed to the robot's coordinates, and the geometric relation (i.e. rotation and translation) between the robot's coordinates and sensor coordinates should be known for the transformation. Calibration means the inference process of geometric relation between the sensor and robot. Generally, the matching of more than 3 points is required to infer the geometric relation. However, we introduce a novel method to calibrate using only 1 point matching and use a specific flat structure (i.e. circular hole) which enables us to find the geometric relation with a single point matching. We make the rotation component of the calibration results as a constant to use only a single point by moving a robot to a specific pose. The flat structure can be installed easily in a manufacturing site, because the structure does not have a volume (i.e. almost 2D structure). The calibration process is fully autonomous and does not need any manual operation. A robot which installed the sensor moves to the specific pose by sensing features of the circular hole such as length of chord and center position of the chord. We show the precision of the proposed method by performing repetitive experiments in various situations. Furthermore, we applied the result of the proposed method to sensor based seam tracking with a robot, and report the difference of the robot's TCP (Tool Center Point) trajectory. This experiment shows that the proposed method ensures precision.