• Smart Structures and Systems
• /
• 제17권6호
• /
• pp.935-956
• /
• 2016

With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.

• Smart Structures and Systems
• /
• 제30권3호
• /
• pp.287-301
• /
• 2022

The machine-vision based structural displacement measurement methods are widely used due to its flexible deployment and non-contact measurement characteristics. The accuracy of vision measurement is directly related to the image resolution. In the field of computer vision, super-resolution reconstruction is an emerging method to improve image resolution. Particularly, the deep-learning based image super-resolution methods have shown great potential for improving image resolution and thus the machine-vision based measurement. In this article, we firstly review the latest progress of several deep learning based super-resolution models, together with the public benchmark datasets and the performance evaluation index. Secondly, we construct a binocular visual measurement platform to measure the distances of the adjacent corners on a chessboard that is universally used as a target when measuring the structure displacement via machine-vision based approaches. And then, several typical deep learning based super resolution algorithms are employed to improve the visual measurement performance. Experimental results show that super-resolution reconstruction technology can improve the accuracy of distance measurement of adjacent corners. According to the experimental results, one can find that the measurement accuracy improvement of the super resolution algorithms is not consistent with the existing quantitative performance evaluation index. Lastly, the current challenges and future trends of super resolution algorithms for visual measurement applications are pointed out.

• 전기학회논문지
• /
• 제60권1호
• /
• pp.161-166
• /
• 2011

This paper addresses the vision based autonomous walking control system. To handle the obstacles which exist beyond the field of view(FOV), we used the 3d panoramic depth image. Moreover, to decide the avoidance direction and walking motion of a humanoid robot for the obstacle avoidance by itself, we proposed the vision based path planning using 3d panoramic depth image. In the vision based path planning, the path and walking motion are decided under environment condition such as the size of obstacle and available avoidance space. The vision based path planning is applied to a humanoid robot, URIA. The results from these evaluations show that the proposed method can be effectively applied to decide the avoidance direction and the walking motion of a practical humanoid robot.

• 전기학회논문지P
• /
• 제60권2호
• /
• pp.63-67
• /
• 2011

This paper presents the mobile robot control based on vision system. The proposed vision based controller consist of the camera tracking controller and the formation controller. Th e camera controller has the adaptive gain based on IBVS. The formation controller which is designed in the sense of the Lyapunov stability follows the leader. Simluation results show that the proposed vision based mobile robot control is validated for indoor mobile robot applications.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
• /
• pp.5-7
• /
• 1996

We propose a triangulation method based on stereo vision angles. We setup stereo vision systems which extract the depth information to a moving object by detecting a moving object using difference image method and obtaining the depth information by the triangulation method based on stereo vision angles. The feature point of a moving object is used the geometrical center of the moving object, and the proposed vision system has the accuracy of 0.2mm in the range of 400mm.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.2379-2384
• /
• 2005

We propose a novel method for object recognition using the smart tag system with a stereo vision on a pan-tilt mechanism. We developed a smart tag which included IRED device. The smart tag is attached onto the object. We also developed a stereo vision system which pans and tilts for the object image to be the centered on each whole image view. A Stereo vision system on the pan-tilt mechanism can map the position of IRED to the robot coordinate system by using pan-tilt angles. And then, to map the size and pose of the object for the robot to coordinate the system, we used a simple model-based vision algorithm. To increase the possibility of tag-based object recognition, we implemented our approach by using as easy and simple techniques as possible.

• JSTS:Journal of Semiconductor Technology and Science
• /
• 제12권2호
• /
• pp.212-218
• /
• 2012

A stereo vision is able to build three-dimensional maps of its environment. It can provide much more complete information than a 2D image based vision but has to process, at least, that much more data. In the past decade, real-time stereo has become a reality. Some solutions are based on reconfigurable hardware and others rely on specialized hardware. However, they are designed for their own specific applications and are difficult to extend their functionalities. This paper describes a vision system based on a System on a Chip (SoC) platform. A real-time stereo image correlator is implemented using Sum of Absolute Difference (SAD) algorithm and is integrated into the vision system using AMBA bus protocol. Since the system is designed on a pre-verified platform it can be easily extended in its functionality increasing design productivity. Simulation results show that the vision system is suitable for various real-time applications.

• Journal of Information Processing Systems
• /
• 제16권1호
• /
• pp.155-170
• /
• 2020

Passive ranging is a critical part of machine vision measurement. Most of passive ranging methods based on machine vision use binocular technology which need strict hardware conditions and lack of universality. To measure the distance of an object placed on horizontal plane, we present a passive ranging method based on monocular vision system by smartphone. Experimental results show that given the same abscissas, the ordinatesis of the image points linearly related to their actual imaging angles. According to this principle, we first establish a depth extraction model by assuming a linear function and substituting the actual imaging angles and ordinates of the special conjugate points into the linear function. The vertical distance of the target object to the optical axis is then calculated according to imaging principle of camera, and the passive ranging can be derived by depth and vertical distance to the optical axis of target object. Experimental results show that ranging by this method has a higher accuracy compare with others based on binocular vision system. The mean relative error of the depth measurement is 0.937% when the distance is within 3 m. When it is 3-10 m, the mean relative error is 1.71%. Compared with other methods based on monocular vision system, the method does not need to calibrate before ranging and avoids the error caused by data fitting.

• 한국생산제조학회지
• /
• 제8권6호
• /
• pp.26-34
• /
• 1999

This study shows an alternative method for the determination of object's position, based on a computer vision method. This approach develops the vision system model to define the reciprocal relationship between the 3-D real space and 2-D image plane. The developed model involves the bilinear six-view parameters, which is estimated using the relationship between the camera space location and real coordinates of known position. Based on estimated parameters in independent cameras, the position of unknown object is accomplished using a sequential estimation scheme that permits data of unknown points in each of the 2-D image plane of cameras. This vision control methods the robust and reliable, which overcomes the difficulties of the conventional research such as precise calibration of the vision sensor, exact kinematic modeling of the robot, and correct knowledge of the relative positions and orientation of the robot and CCD camera. Finally, the developed vision control method is tested experimentally by performing determination of object position in the space using computer vision system. These results show the presented method is precise and compatible.

• International Journal of Aeronautical and Space Sciences
• /
• 제17권3호
• /
• pp.366-377
• /
• 2016

This paper presents a vision-based guidance method that allows a fixed-wing aircraft to orbit around a target at a given radius. The guidance method uses a simple formula that regulates a relative side-bearing angle estimated by a vision system. The global asymptotic stability of the associated guidance law is demonstrated, and a linear analysis is performed to facilitate the proper selection of the relevant control parameters. A flight experiment is presented to demonstrate the feasibility and performance of the proposed guidance method.