• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.420-425
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• 2003

Generally, reverse engineering means getting CAD data from unidentified shape using vision or 3D laser scanner system. In this paper, we studied unidentified model by machine vision based reverse engineering system to get information about in-processing model. Recently, vision technology is widely used in current factories, because it could inspect the in-process object easily, quickly, accurately. The following tasks were mainly investigated and implemented. We obtained more precise data by corning camera's distortion, compensating slit-beam error and revising acquired image. Much more, we made similar curves or surface with B-spline approximation for precision. Until now, there have been many case study of shape recognition. But it was uncompatible to apply to the field, because it had taken too many processing time and has frequent recognition failure. This paper propose recognition algorithm that prevent such errors and give applications to the field.

• Agricultural and Biosystems Engineering
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• v.6 no.2
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• pp.47-53
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• 2005

AMachine vision is a promising tool for the autonomous guidance of farm machinery. Conventional CCD camera for the machine vision needs a desktop PC to install a frame grabber, however, a web camera is ready to use when plugged in the USB port. A web camera with a notebook PC can replace existing camera system. Autonomous steering control system of this research was intended to be used for combine harvester. If the web camera can recognize cut/uncut edge of crop, which will be the reference for steering control, then the position of the machine can be determined in terms of lateral offset and heading angle. In this research, a white line was used as a cut/uncut edge of crop for steering control. Image processing algorithm including capturing image in the web camera was developed to determine the desired travel path. An experimental vehicle was constructed to evaluate the system performance. Since the vehicle adopted differential drive steering mechanism, it is steered by the difference of rotation speed between left and right wheels. According to the position of vehicle, the steering algorithm was developed as well. Evaluation tests showed that the experimental vehicle could travel within an RMS error of 0.8cm along the desired path at the ground speed of $9\sim41cm/s$. Even when the vehicle started with initial offsets or tilted heading angle, it could move quickly to track the desired path after traveling $1.52\sim3.5m$. For turning section, i.e., the curved path with curvature of 3 m, the vehicle completed its turning securely.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.3
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• pp.49-56
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• 2014

Generally, the tool presetter is utilized to align and measure some specific dimensions of a machine tool. It is classified into two types(contact and contactless) according to the measurement method, and the optical sensor based contactless scheme has the advantages of measurement flexibility and convenience. This paper describes the design and realization of an industrial tool presetter using machine vision and linear scaler. Before measurement, the objective tool is attached to the mechanical mount and is aligned with the optical apparatus. After capturing tool images, the suggested image processing algorithm calculates its dimesions accurately, combining the traversing distance from the linear scaler. Experimental results conforms that the present tool presetter system has the precision within ${\pm}20um$ error.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.3
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• pp.58-67
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• 2000

Electron gun heaters are used to heat a cathode in video(TV) monitors. Major defects of the electron gun heaters include dimensional inaccuracy and pollution with dirty materials. In this paper, to save the labor and time being taken to inspect the heaters, a machine vision system is considered. For the system, a new algorithm is developed to measure the 9 different dimensions of each heater and to detect polluted defects. The algorithm consists of three stages. In the first stage, the center of the heater image is obtained and then its boundary detection is performed. For the efficient boundary detection, a mask called the sum mask is used. In the second stage of the algorithm, a set of fiducial points are determined on the boundary image. Finally, using the fiducial points specified dimensions are measured and the amount of polluted area is computed in the third stage. The performance of the algorithm is evaluated for a set of real specimens. The results indicate that measurements obtained by the algorithm satisfy the tolerance limits fur most of the dimensions and the algorithm detects the polluted defects successfully.

• Korean Journal of Construction Engineering and Management
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• v.5 no.2 s.18
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• pp.90-105
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• 2004

Machines for crack sealing automation have been continually developed since the early 1990's because of the effectiveness of crack sealing that would be able to improve safety, quality and productivity. It has been considered challenging problem to detect crack network in pavement which includes noise (oil marks, skid marks, previously sealed cracks and inherent noise). Moreover, it is required to develop crack network mapping and modeling algorithm in order to accurately inject sealant along to the middle of cut crack network. The primary objective of this study is to propose machine vision algorithms (digital image processing algorithm and path planning algorithm) for fully automated pavement crack sealing. It is anticipated that the effective use of the proposed machine vision algorithms would be able to reduce error rate in image processing for detecting, mapping and modeling crack network as well as improving quality and productivity compared to existing vision algorithms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.202-208
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• 2016

In this study, the defect in connection with a C-tray was inspected using a low-cost camera. The four test items were the device overlapping in the tray, the bending of the tray, the loaded quantity of the tray, and the device pocket leaving, an algorithm was developed for defining and detecting the above defect types. Therefore, the developed handling system could extend the application of the stack of the c-tray and provide a quantity verification inspection on the packing processing. The machine operation control program, which can ensure the optimal inspection image to match the scan speed, was developed and the control program that can process the user gui and the vision image utilizing the control was developed. Overall, a mechanical system that is practicable for obtaining an image and processing the vision data was designed.

• Journal of Biosystems Engineering
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• v.32 no.3
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• pp.179-189
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• 2007

Most of the seeds of cucurbitaceous rootstock species used for grafting were mainly sown by hand. This study was carried out to develop an on-line discriminating algorithm of seed direction using machine vision and an automatic seeding system. The seeding system was composed of a supplying device, feeding device, machine vision system, reversing device, seeding device and system control section. Machine vision was composed of a color CCD camera, frame grabber, image inspection chamber, lighting and personal computer. The seed image was segmented into a region of seed part and background part using thresholding technique in which H value of HSI color coordinate system. A seed direction was discriminated by comparing position between the center of circumscribed rectangle to a seed and the center of seed image. It took about 49ms to identify and redirect seed. Line-up status of seed was good the more than 95% of a sowed seed. Seeding capacity of this system was shown to be 10,140 grains per hour, which is three times faster than that of a typical worker.

• Journal of Biosystems Engineering
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• v.22 no.1
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• pp.30-40
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• 1997

A computer vision system was built to automatically grade the leaf tobacco. A color image processing algorithm was developed to extract shape, color and texture features. An improved back propagation algorithm in an artificial neural network was applied to grade the Burley type dried leaf tobacco. The success rate of grading in three-grade classification(1, 3, 5) was higher than the rate of grading in six-grade classification(1, 2, 3, 4, 5, off), on the average success rate of both the twenty-five local pixel-set and the sixteen local pixel-set. And, the average grading success rate using both shape and color features was higher than the rate using shape, color and texture features. Thus, the texture feature obtained by the spatial gray level dependence method was found not to be important in grading leaf tobacco. Grading according to the shape, color and texture features obtained by machine vision system seemed to be inadequate for replacing manual grading of Burely type dried leaf tobacco.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.5
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• pp.1-8
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• 2004

In this paper, we propose a machine vision system by which we can measure the size of ALC blocks in real-time in the Production Process. The images obtained by our system were processed by a devised algorithm, specially designed for the enhanced measurement accuracy. from the experimental results, we could find that the required measurement accuracy specification is sufficiently satisfied by using our proposed method.

• IE interfaces
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• v.11 no.1
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• pp.191-197
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• 1998

This paper describes a machine vision algorithm for inspecting a crimpled terminal. The crimpled terminal is one of wire harness assemblies which transmit current or signals between a pair of electrical or electronic assemblies. The major defect considered is wire exposure on wire barrels. To detect the wire exposure, we develope a multi-layer perceptron in which three features extracted from the image of the crimpled terminal are used as input data. The three features are edginess, variance, and total number of valley points(TVP). The multi-layer neural network has been successfully tested on a number of real specimens collected from a wire-harness factory.