• Journal of Astronomy and Space Sciences
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• v.35 no.4
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• pp.263-277
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• 2018

This paper presents a vision-based relative pose estimation algorithm and its validation through both numerical and hardware experiments. The algorithm and the hardware system were simultaneously designed considering actual experimental conditions. Two estimation techniques were utilized to estimate relative pose; one was a nonlinear least square method for initial estimation, and the other was an extended Kalman Filter for subsequent on-line estimation. A measurement model of the vision sensor and equations of motion including nonlinear perturbations were utilized in the estimation process. Numerical simulations were performed and analyzed for both the autonomous docking and formation flying scenarios. A configuration of LED-based beacons was designed to avoid measurement singularity, and its structural information was implemented in the estimation algorithm. The proposed algorithm was verified again in the experimental environment by using the Autonomous Spacecraft Test Environment for Rendezvous In proXimity (ASTERIX) facility. Additionally, a laser distance meter was added to the estimation algorithm to improve the relative position estimation accuracy. Throughout this study, the performance required for autonomous docking could be presented by confirming the change in estimation accuracy with respect to the level of measurement error. In addition, hardware experiments confirmed the effectiveness of the suggested algorithm and its applicability to actual tasks in the real world.

• Current Optics and Photonics
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• v.2 no.4
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• pp.348-355
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• 2018

How to measure the creepage distance of an insulator quickly and accurately is a problem for the power industry at present, and the noticeable concern is that the high voltage insulation equipment cannot be measured online in the charged state. In view of this situation, we develop an on-line measurement system of creepage distance for high voltage insulators based on binocular stereo vision. We have proposed a method of generating linear structured light using a conical off-axis mirror. The feasibility and effect of two ways to solve the interference problem of strong sunlight have been discussed, one way is to use bandpass filters to enhance the contrast ratio of linear structured light in the images, and the other way is to process the images with adaptive threshold segmentation and feature point extraction. After the system is calibrated, we tested the measurement error of the on-line measurement system with a composite insulator sample. Experimental results show that the maximum relative error is 1.45% and the average relative error is 0.69%, which satisfies the task requirement of not more than 5% of the maximum relative error.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.7
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• pp.1260-1272
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• 2008

This paper proposes object detection algorithm using laser scanner and vision system for the path planning of autonomous mobile agents. As the scanner-based method can observe the obstacles in only two dimensions, it is hard to detect the shape and the number of obstacles. On the other hand, vision-based method is sensitive to the environment and has its difficulty in the accurate distance measurement. Thus, we combine these two methods based on K-means algorithm such that the obstacle avoidance and optimal path planning of autonomous mobile agents can be achieved.

• Journal of Biosystems Engineering
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• v.42 no.3
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• pp.227-233
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• 2017

Purpose: Morphological properties of soybean roots are important indicators of the vigor of the seed, which determines the survival rate of the seedlings grown. The current vigor test for soybean seeds is manual measurement with the human eye. This study describes an application of a machine vision technique for rapid measurement of soybean seed vigor to replace the time-consuming and labor-intensive conventional method. Methods: A CCD camera was used to obtain color images of seeds during germination. Image processing techniques were used to obtain root segmentation. The various morphological parameters, such as primary root length, total root length, total surface area, average diameter, and branching points of roots were calculated from a root skeleton image using a customized pixel-based image processing algorithm. Results: The measurement accuracy of the machine vision system ranged from 92.6% to 98.8%, with accuracies of 96.2% for primary root length and 96.4% for total root length, compared to manual measurement. The correlation coefficient for each measurement was 0.999 with a standard error of prediction of 1.16 mm for primary root length and 0.97 mm for total root length. Conclusions: The developed machine vision system showed good performance for the morphological measurement of soybean roots. This image analysis algorithm, combined with a simple color camera, can be used as an alternative to the conventional seed vigor test method.

• Smart Structures and Systems
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• v.24 no.6
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• pp.769-781
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• 2019

Dynamic displacement response of civil structures is an important index for in-construction and in-service structural condition assessment. However, accurately measuring the displacement of large-scale civil structures such as high-rise buildings still remains as a challenging task. In order to cope with this problem, a vision-based system with the use of industrial digital camera and image processing has been developed for long-distance, remote, and real-time monitoring of dynamic displacement of supertall structures. Instead of acquiring image signals, the proposed system traces only the coordinates of the target points, therefore enabling real-time monitoring and display of displacement responses in a relatively high sampling rate. This study addresses the in-situ experimental verification of the developed vision-based system on the Canton Tower of 600 m high. To facilitate the verification, a GPS system is used to calibrate/verify the structural displacement responses measured by the vision-based system. Meanwhile, an accelerometer deployed in the vicinity of the target point also provides frequency-domain information for comparison. Special attention has been given on understanding the influence of the surrounding light on the monitoring results. For this purpose, the experimental tests are conducted in daytime and nighttime through placing the vision-based system outside the tower (in a brilliant environment) and inside the tower (in a dark environment), respectively. The results indicate that the displacement response time histories monitored by the vision-based system not only match well with those acquired by the GPS receiver, but also have higher fidelity and are less noise-corrupted. In addition, the low-order modal frequencies of the building identified with use of the data obtained from the vision-based system are all in good agreement with those obtained from the accelerometer, the GPS receiver and an elaborate finite element model. Especially, the vision-based system placed at the bottom of the enclosed elevator shaft offers better monitoring data compared with the system placed outside the tower. Based on a wavelet filtering technique, the displacement response time histories obtained by the vision-based system are easily decomposed into two parts: a quasi-static ingredient primarily resulting from temperature variation and a dynamic component mainly caused by fluctuating wind load.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.2
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• pp.232-239
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• 2016

Recently, in order to increase the efficiency and mission success rate of UAVs (Unmanned Aerial Vehicles), the necessity for formation flights is increased. In general, GPS (Global Positioning System) is used to obtain the relative position of leader with respect to follower in formation flight. However, it can't be utilized in environment where GPS jamming may occur or communication is impossible. Therefore, in this study, monocular vision is used for measuring relative position. General PC-based vision processing systems has larger size than embedded systems and is hard to install on small vehicles. Thus FPGA-based processing board is used to make our system small and compact. The processing system is divided into two blocks, PL(Programmable Logic) and PS(Processing system). PL is consisted of many parallel logic arrays and it can handle large amount of data fast, and it is designed in hardware-wise. PS is consisted of conventional processing unit like ARM processor in hardware-wise and sequential processing algorithm is installed on it. Consequentially HW/SW co-designed FPGA system is used for processing input images and measuring a relative 3D position of the leader, and this system showed RMSE accuracy of 0.42 cm ~ 0.51 cm.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.6
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• pp.543-551
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• 2015

In this study, a novel method for dimension measurement of large-scale moving objects using stereo camera with 2-degree of freedom (2-DOF) mechanism is presented. The proposed method utilizes both the advantages of stereo vision technique and the enlarged visibility range of camera due to 2-DOF rotary mechanism in measuring large-scale moving objects. The measurement system employs a stereo camera combined with a 2-DOF rotary mechanism that allows capturing separate corners of the measured object. The measuring algorithm consists of two main stages. First, three-dimensional (3-D) positions of the corners of the measured object are determined based on stereo vision algorithms. Then, using the rotary angles of the 2-DOF mechanism the dimensions of the measured object are calculated via coordinate transformation. The proposed system can measure the dimensions of moving objects with relatively slow and steady speed. We showed that the proposed system guarantees high measuring accuracy with some experiments.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.30-34
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• 2006

Recently, there has been an increasing demand for computer-vision-based inspection and/or measurement system as a part of factory automation equipment. In general, it is almost impossible to check the fault of all parts, coming from part-feeding system, with only manual inspection because of time limitation. Therefore, most of manual inspection is applied to specific samples, not all coming parts, and manual inspection neither guarantee consistent measuring accuracy nor decrease working time. Thus, in order to improve the measuring speed and accuracy of the inspection, a computer-aided measuring and analysis method is highly needed. In this paper, a computer-vision-based pipe inspection system is proposed, where the front and side-view profiles of three different kinds of pipes, coming from a forming line, are acquired by computer vision. And the edge detection is processed by using Laplace operator. To reduce the vision processing time, modified Hough transform is used with clustering method for straight line detection. And the center points and diameters of inner and outer circle are found to determine eccentricity of the parts. Also, an inspection system has been built so that the data and images of faulted parts are stored as files and transferred to the server.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.790-797
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• 2001

A simple computer vision technology to measure the middle-ranged depth with a mono camera and a plain mirror is proposed. The proposed system is structured with the rotating mirror in front of the fixed mono camera. In contrast to the previous stereo vision system in which the disparity of the closer object is larger than that of the distant object, the pixel movement caused by the rotating mirror is bigger for the pixels of the distant object in the proposed system. Being inspired by such distinguished feature in the proposed system, the principle of the depth measurement based on the relation of the pixel movement and the distance of object is investigated. Also, the factors to influence the precision of the measurement are analysed. The benefits of the proposed system are low price and less chance of occlusion. The robustness for practical usage is an additional benefit of the proposed vision system.

• Transactions of Materials Processing
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• v.9 no.4
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• pp.404-412
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• 2000

It is desirable to use the square grid analysis with the aid of the stereo vision and image processing techniques in order to automatically measure the surface-strain distribution over a stamped part. But this method has some inherent problems such as the difficulty in enhancement of bad images, the measurement error due to the digital image resolution and the limit of the area that can be measured at a time. Therefore, it is still hard to measure the strain distribution over the entire surface of a medium-or large-sized stamped part even by using an automated strain measurement system. In this study, several methods which enable to solve these problems considerably without losing accuracy and precision In measurement are suggested. The superposition of images that have different high-lightened or damaged part from each other gives much enhanced image. A new algorithm for constructing of the element connectivity from the line-thinned image helps recognize up to 1,000 elements. And the geometry assembling algorithm including the global error minimization makes it possible to measure a large specimen with reliability and efficiency.