• 방송공학회논문지
• /
• 제23권5호
• /
• pp.656-668
• /
• 2018

스티칭 기술은 고화질의 360 VR 영상을 제작하는 과정에서 가장 중요한 요소 기술들 중의 하나이다. 스티칭 기술의 성능을 저하시키는 원인들에는 특징점 추출 과정의 오류, seam finding 과정에서 사용되는 마스크의 왜곡으로 발생하는 오류, 각 영상들의 밝기 보상 오류 등 다양한 원인들이 존재한다. 본 논문에서는 합성되는 각 영상들 간의 시차(View Disparity)가 존재함으로써 스티칭 성능이 저하되는 현상을 분석하고, 이 문제를 해결하기 위해 이음부 탐색(seam finding)의 전처리 과정에서 사용되는 효율적인 알고리즘을 제안한다. 본 논문에서 제안하는 기술을 통해 기존 방법보다 개선된 마스크들을 제작하여 효율적인 이음부 탐색(seam finding)이 수행되도록 하고, 그 결과 개선된 화질을 갖는 360 VR 영상을 얻을 수 있음을 설명한다. 본 논문에서 실시된 다양한 실험들을 통해, 제안된 기술이 시차 왜곡이 존재하는 영상 신호들을 합성하는 과정에 효율적이면서 동작 복잡도도 높지 않음을 보이고 있다.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1997년도 춘계학술대회 논문집
• /
• pp.729-733
• /
• 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

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1996년도 춘계학술대회 논문집
• /
• pp.680-684
• /
• 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.

• 방송공학회논문지
• /
• 제24권6호
• /
• pp.1096-1112
• /
• 2019

현재 360 VR 이미지를 만들어주는 카메라들은 상당히 고가이기에 사람들이 손쉽게 사용할 순 없는 상황이다. 이를 해결하기 위해 휴대 전화의 카메라를 이용해 100여 장의 사진을 360° 촬영을 한 후 Image stitching으로 360 VR 영상을 얻고자 한다. 기존의 장비는 한 번에 360℃ 촬영으로 VR 영상을 만들어내는 반면 휴대 전화를 이용하여 촬영할 경우 영상마다 시차가 생기게 된다. 이로 인해 움직이는 물체가 있는 경우 물체가 여러 장의 영상에서 나타나는 원하지 않는 상황이 생기게 되고 Seam이 물체를 관통하여 부자연스러운 결과 영상을 얻게 된다. 본 논문에서는 시각적으로 두드러지는 물체를 판별할 수 있는 Saliency map을 이용한 Seam finder 알고리즘을 통해 개선된 결과 영상을 얻을 수 있음을 확인했다.

• 방송공학회논문지
• /
• 제23권6호
• /
• pp.896-913
• /
• 2018

360 VR 영상을 구성하는 과정에서 합성되는 영상들 사이의 경계(seam)를 정확하고 효율적으로 추출하는 것은 스티칭된 영상의 화질에 매우 중요한 영향을 끼친다. 기존의 seam finding 기술들인 보로노이(Voronoi) 알고리즘, dynamic programming, graph cut 방법들은 시차(view disparity)가 존재하거나 이동하는 물체가 존재하는 상황에서는 ghost와 같은 왜곡을 발생시킨다. 본 논문에서는 기존 알고리즘들과 달리 물체를 가로지르지 않고, 물체를 피해 배경을 가로질러 접합선을 추출하는 '밝기 대비를 이용한 마스크 추출 방법'을 제안하였다. 이때, 배경과 물체와의 밝기차이를 이용하여, 물체의 형상을 따라 이어지는 접합선을 추출했다. 본 논문의 실험 결과를 통해, 제안하는 기술을 사용하면 왜곡을 감소시키는 위치에서 접합선이 생성되고, 스티칭된 영상의 화질이 개선되는 것을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
• /
• pp.775-778
• /
• 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.

• 한국정밀공학회지
• /
• 제24권10호
• /
• pp.64-74
• /
• 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.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1993년도 추계학술대회 논문집
• /
• pp.550-555
• /
• 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.

• 제어로봇시스템학회논문지
• /
• 제20권2호
• /
• pp.218-222
• /
• 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.