• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.333-335
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• 2006

In this page, we developed the inspection system for automobile parts using the laser vision sensor. Laser vision sensor has gotten 2 dimensions information and third dimension information of laser vision camera using the vision camera. Used JIG and ROBOT for inspection position transfer. Also, computer integration system developed that control system component pal1s and manage data measurement information. Compare sensor measurement result with CAD Data and verified measurement result effectiveness taking advantage of CAD to get information of measurement object.

• Smart Structures and Systems
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• v.17 no.6
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• pp.935-956
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• 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.

• Wind and Structures
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• v.20 no.2
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• pp.315-326
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• 2015

To overcome the drawbacks of the traditional contact-type sensor for structural displacement measurement, the vision-based technology with the aid of the digital image processing algorithm has received increasing concerns from the community of structural health monitoring (SHM). The advanced vision-based system has been widely used to measure the structural displacement of civil engineering structures due to its overwhelming merits of non-contact, long-distance, and high-resolution. However, seldom currently-available vision-based systems are capable of realizing the synchronous structural displacement measurement for multiple points on the investigated structure. In this paper, the method for vision-based multi-point structural displacement measurement is presented. A series of moving loading experiments on a scale arch bridge model are carried out to validate the accuracy and reliability of the vision-based system for multi-point structural displacement measurement. The structural displacements of five points on the bridge deck are measured by the vision-based system and compared with those obtained by the linear variable differential transformer (LVDT). The comparative study demonstrates that the vision-based system is deemed to be an effective and reliable means for multi-point structural displacement measurement.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.5
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• pp.973-979
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• 2007

A laser vision system is developed to measure the three-dimensional feature of an object. This system consists of two low cost cameras and a cross laser. One camera and a cross laser are used to measure a plane equation of an object. Using this information, the other camera measures a hole size of an object. The proposed system provides 0.05 mm accuracy measurement systems with relatively low cost.

• Journal of Biosystems Engineering
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• v.23 no.5
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• pp.481-490
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• 1998

A computer vision system to measure low flow rate of solid particles was developed and tested to examine its performance with various sized 7 kinds of seeds, perilla, mung bean, paddy, small red bean, black soybean, Cuba bean and small potato tuber. The test was performed for two types of particle flow, continuous and discontinuous. For the continuous flow tested with perilla, mung bean and paddy, the tests resulted correlation coefficients for the flow rates measured by the computer vision and direct method about 0.98. Average errors of the computer vision measurement were in a range of 6∼9%. For the discontinuous flow tested with small red bean, black soybean, Cuba bean and small potato tuber, the tests resulted correlation coefficients for the flow rates measured by the computer vision and direct method 0.98∼0.99. Average errors of the computer vision measurement were in a range of 5∼10%. Performance of the computer vision system was compared with that of the conventional optical sensor to count particles in discontinuous flow. The comparison was done with black soybean, Cuba bean and small potato tuber, and resulted that the computer vision has much better performance than the optical sensor in a sense of precision of the measurement.

• 한국기계연구소 소보
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• s.19
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• pp.69-79
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• 1989

Cutting tool life monitoring is a critical element needed for designing unmanned machining systems. This paper describes a tool wear measurement system using computer vision which repeatedly measures flank and crater wear of a single point cutting tool. This direct tool wear measurement method is based on an interactive procedure utilizing a image processor and multi-vision sensors. A measurement software calcultes 7 parameters to characterize flank and crater wear. Performance test revealed that the computer vision technique provides precise, absolute tool-wear quantification and reduces human maesurement errors.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.11
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• pp.1017-1021
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• 2004

In this paper, a cost-effective integrated 3D system for measuring and sizing foot is proposed. The proposed system employs two CCDs and a laser line projector which are capable of accurately measuring foot. The measurement is based upon the biologically motivated stereo vision principle providing ruggedness against minor system distortions. According to the tolerance, calibration between two different views are implicitly applied. Furthermore, the measurement system employs a measurement base, a frame grabber, a CCD moving cart, a stepping motor and computer. Analysis and design procedure is presented for the calculation of the 3D foot data and the proposed system. Experimental results on the proposed system would verify the concept and system operation.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.494-500
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• 2004

This paper presents a machine vision system, which inspects the measurement of the ALC block on a real-time basis in the production process. The automatic measurement system was established with a CCD camera, an image grabber, and a personal computer without using assembled measurement equipment. Images obtained by this system was processed by an algorithm, specially designed for an enhanced measurement accuracy. For the realization of the proposed algorithm, a preprocessing method that can be applied to overcome uneven lighting environment, boundary decision method, unit length decision method in uneven condition with rocking objects, and a projection of region using pixel summation are developed. From our experimental results, we could find that the required measurement accuracy specification is sufficiently satisfied by using the proposed method.

• Smart Structures and Systems
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• v.20 no.5
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• pp.563-572
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• 2017

The safety of structures is closely associated with the structural out-of-plane behavior. In particular, long and slender beam structures have been increasingly used in the design and construction. Therefore, an evaluation of the lateral and torsional behavior of a structure is important for the safety of the structure during construction as well as under service conditions. The current contact measurement method using displacement meters cannot measure independent movements directly and also requires caution when installing the displacement meters. Therefore, in this study, a vision-based system was used to measure the in-plane and out-of-plane displacements of a structure. The image processing algorithm was based on reference objects, including multiple targets in Lab color space. The captured targets were synchronized using a load indicator connected wirelessly to a data logger system in the server. A laboratory beam test was carried out to compare the displacements and rotation obtained from the proposed vision-based measurement system with those from the current measurement method using string potentiometers. The test results showed that the proposed vision-based measurement system could be applied successfully and easily to evaluating both the in-plane and out-of-plane movements of a beam including twisting rotation.

• Agricultural and Biosystems Engineering
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• v.4 no.1
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• pp.16-21
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• 2003

In the agricultural field, a machine vision system has been widely used to automate most inspection processes especially in quality grading. Though machine vision system was very effective in quantifying geometrical quality factors, it had a deficiency in quantifying color information. This study was conducted to evaluate color of beef using machine vision system. Though measuring color of a beef using machine vision system had an advantage of covering whole lean tissue area at a time compared to a colorimeter, it revealed the problem of sensitivity depending on the system components such as types of camera, lighting conditions, and so on. The effect of color balancing control of a camera was investigated and multi-layer BP neural network based color calibration process was developed. Color calibration network model was trained using reference color patches and showed the high correlation with L*a*b* coordinates of a colorimeter. The proposed calibration process showed the successful adaptability to various measurement environments such as different types of cameras and light sources. Compared results with the proposed calibration process and MLR based calibration were also presented. Color calibration network was also successfully applied to measure the color of the beef. However, it was suggested that reflectance properties of reference materials for calibration and test materials should be considered to achieve more accurate color measurement.