• 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.

• 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 the Korean Society for Precision Engineering
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• v.27 no.5
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• pp.7-13
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• 2010

The integrity and accuracy of the drilling hole are decided by positional error, diameter error, the roundness, the straightness, the cylindericity, size of the burr, the surface roundness and others. Among these parameters, positional error and diameter error have the most important parameters. The diameter error has been widely studied, but there has been little research done about the positional error due to the difficulty of measuring it. The measurement of hole location and diameter would be performed by CMM(Coordinate Measurement Machine). However, the usage of CMM requires much time and cost. In order to overcome the difficulties, we have developed a hole location and diameter error measuring device using machine vision. The developed measurement device attached to a CNC machine can determine hole quality quickly and easily.

• Transactions of Materials Processing
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• v.8 no.3
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• pp.294-305
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• 1999

A vision-based surface-strain measurement system has been still improved since the authors devel-oped the first version of it. New algorithms for the subpixel measurement and surface smoothing are introduced to improve the accuracy and precision in the present study. The effects of these algorithms are investigated by error analysis. And the equations required to calculate 3D surface-strain of a shell element are derived from the shape function of a linear solid finite-element. The influences of external factors on the measurement error are also examined, and several trials are made to obtain possible optimal condition which may minimize the error.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.679-684
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• 2019

We propose a method to measure the number of specific species of class using CAFFE model and a method to measure length and width of object using stereo vision. To obtain the width of an object, the location coordinates of objects appearing on the left and right sensor is compared and the distance from the sensor to the object is obtained. Then the length of the object in the image by using the distance and the approximate value of the actual length of the object is calculated.

• 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.

• Smart Structures and Systems
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• v.18 no.3
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• pp.585-599
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• 2016

Steel cables serve as the key structural components in long-span bridges, and the force state of the steel cable is deemed to be one of the most important determinant factors representing the safety condition of bridge structures. The disadvantages of traditional cable force measurement methods have been envisaged and development of an effective alternative is still desired. In the last decade, the vision-based sensing technology has been rapidly developed and broadly applied in the field of structural health monitoring (SHM). With the aid of vision-based multi-point structural displacement measurement method, monitoring of the tensile force of the steel cable can be realized. In this paper, a novel cable force monitoring system integrated with a multi-point pattern matching algorithm is developed. The feasibility and accuracy of the developed vision-based force monitoring system has been validated by conducting the uniaxial tensile tests of steel bars, steel wire ropes, and parallel strand cables on a universal testing machine (UTM) as well as a series of moving loading experiments on a scale arch bridge model. The comparative study of the experimental outcomes indicates that the results obtained by the vision-based system are consistent with those measured by the traditional method for cable force measurement.

• Journal of the Optical Society of Korea
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• v.15 no.1
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• pp.30-37
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• 2011

Binocular-pair images obtained from two cameras can be used to calculate the three-dimensional (3D) world coordinate of a feature point. However, to apply this method, measurement accuracy of binocular vision depends on some structure factors. This paper presents an experimental study of measurement distance, baseline distance, and baseline direction. Their effects on camera reconstruction accuracy are investigated. The testing set for the binocular model consists of a series of feature points in stereo-pair images and corresponding 3D world coordinates. This paper discusses a method to increase the baseline distance of two cameras for enhancing the accuracy of a binocular vision system. Moreover, there is an inflexion point of the value and distribution of measurement errors when the baseline distance is increased. The accuracy benefit from increasing the baseline distance is not obvious, since the baseline distance exceeds 1000 mm in this experiment. Furthermore, it is observed that the direction errors deduced from the set-up are lower when the main measurement direction is similar to the baseline direction.

• Transactions of Materials Processing
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• v.32 no.1
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• pp.20-27
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• 2023

In this study, the deformation of materials was measured using the video and tracking API of OpenCV. Circular markers attached to the material were selected the region of interests (ROIs). The position of the marker was measured from the area center of the circular marker. The position and displacement of the center point was measured along the image frames. For the verification, tensile tests were conducted. In the tensile test, four circular markers were attached along the longitudinal and transverse directions. The strain was calculated using the distance between markers both in the longitudinal and transverse direction. As a result, the stress-strain curve obtained using machine vision is compared to the stress-strain curve obtained from the DIC results. RMSE values of the strain from the machine vision and DIC were less than 0.005. In addition, as a measurement example, a bending angle and springback measurement according to bending deformation, and a moving position measurement of a punch, a blank holder, and a die by time change were performed. Using the proposed method, the deformation and displacement of the materials were measured precisely and easily.

• Journal of Korea Multimedia Society
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• v.5 no.3
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• pp.272-280
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• 2002

In this paper, we present a method to extract a moving object and to measure the distance to it by using the stereo vision system. The moving factor is to be extracted through a match of a pixel unit for the moving object where the adaptive threshold is effectively dealt with to remove changes in the brightness of the image. The distance to moving object is measured by using a stereo vision system which employs a parallel camera. The experimental results show that the proposed algorithm could be effectively applied to distance measurement to moving object because it has an average error of one percent.