• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.123-125
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• 2006

This paper discusses the method of vision based sensor fusion system for biped robot walking. Most researches on biped walking robot have mostly focused on walking algorithm itself. However, developing vision systems for biped walking robot is an important and urgent issue since biped walking robots are ultimately developed not only for researches but to be utilized in real life. In the research, systems for environment recognition and tole-operation have been developed for task assignment and execution of biped robot as well as for human robot interaction (HRI) system. For carrying out certain tasks, an object tracking system using modified optical flow algorithm and obstacle recognition system using enhanced template matching and hierarchical support vector machine algorithm by wireless vision camera are implemented with sensor fusion system using other sensors installed in a biped walking robot. Also systems for robot manipulating and communication with user have been developed for robot.

• 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.

• Proceedings of the KIEE Conference
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• 2007.11c
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• pp.112-116
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• 2007

If any of the set parameters such as the environment temperature, mold temperature are not maintained at a consistent level, the fail rate of injection molding products is increased. The price of the injection molding machine is very high, so in order to maximize the utilization of the machine that is required the production of a number of different products with minimum fail rate using a single machine. To prevent the defect products by an inspection process with perfect quality is very important to minimizing production of defect products in the molding process. Vision inspection systems are widely utilized in various manufacturing industries for quality assurance purposes. The vision inspection system consists of CCD camera and lighting system to capture the image of the subject of inspection, an image comparison algorithm using to determine the pass/fail of the products, and mechanical devices for the operation of the whole system. This research focuses on the development of the vision inspection system to process the inspection of an automobile parts. We developed a mechanical devices for the inspection of the injection molding products and an image comparison algorithm to determine the pass/fail result of the inspection based on the molding image and the accepted product image.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1030-1035
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• 2014

Machine vision inspection systems have replaced human inspectors in defect inspection fields for several decades. However, the inspection results of machine vision are often affected by small changes of illumination. When small changes of illumination appear in image histograms, the influence of illumination can be decreased by transformation of the histogram. In this paper, we propose an enhanced histogram matching algorithm which corrects distorted histograms by variations of illumination. We use the resolution resizing method for an optimal matching of input and reference histograms and reduction of quantization errors from the digitizing process. The proposed algorithm aims not only for improvement of the accuracy of defect detection, but also robustness against variations of illumination in machine vision inspection. The experimental results show that the proposed method maintains uniform inspection error rates under dramatic illumination changes whereas the conventional inspection method reveals inconsistent inspection results in the same illumination conditions.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.6 s.171
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• pp.127-134
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• 2005

The machine vision has been applied to a number of industrial applications for quality control and automations to improve the manufacturing processes. In this paper, the automation system using the machine vision is developed, which is applicable to the marking process in a steel production process line. The working environment is very harsh to workers so that the automatic system in the steel industry is required increasingly. The developed automatic marking system consists of several mechanical and electrical elements such as the laser position detecting sensor system fur a structured laser beam which is projected to the billet in order to detect the geometry of the billet. An image processing algorithm has been developed to percept the two center positions of a camera and a billet, respectively, and to align two centers. A series of experiments has been conducted to investigate the performance of the proposed algorithm. The results show that two centers of the camera and the billet could be detected very well and differences between two center positions could be also decreased via the proposed location error decreasing algorithm.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.184-186
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• 2004

This paper is about vision system that exhibits automatic examination of the conditions of shaft's worm. The system is composed of three part : image acquisition, vision algorithm, and user interface. The image acquisition part is composed of motor control, illumination and optics. The vision algorithm examines the parts by labeling algorithm using shaft image. User interface is divided into two parts, user interface for feature registering with control value settings and user interface for examination operation. The automatic inspection system of this research is a tool for final examination of shaft worm. This tool can be practically used in production lines with simple adjustments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.733-737
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• 1996

This paper presents a method to measure tile position and orientation of a prismatic polyhedral object (of unknown width, length, height, and number of vertices) using machine vision. The width, length, and origin of workplace where an object is lying are defined as Preliminary operation. The edges of an object are detected from captured image using least sum of square error. The information of an object is determined from the geometric relationships between edges. As an user interface, a versatile image processing program is developed in several modules, and renders a very useful 3D measurement at a limited constraints when adopted in automation of production process. The flexibility of camera position from the algorithm developrf can be used for automated pick and place operations and feeding workpiece u: ;ing assembly robot.

• Journal of Biosystems Engineering
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• v.26 no.6
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• pp.571-578
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• 2001

Production of green pepper has increased for ten years in Korea, as customer's preference of a pepper tuned to fiesta one. This study was conducted to develop an on-line fading algorithm of green pepper using machine vision and aimed to develop the automatic on-line grading and sorting system. The machine vision system was composed of a professive scan R7B CCD camera, a frame grabber and sets of 3-wave fluorescent lamps. The length and curvature, which were main quality factors of a green pepper were measured while removing the stem region. The first derivative of the thickness profile was used to remove the stem area of the segmented image of the pepper. A new boundary was generated after the stem was removed and a baseline of a pepper which was used for the curvature determination was also generated. The developed algorithm showed that the accuracy of the size measurement was 86.6% and the accuracy of the bent was 91.9%. Processing time spent far grading was around 0.17 sec per pepper.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.2
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• pp.3-9
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• 2009

When washing machine is rotated in the laundry, it tends to lean toward one side. This tendency causes a serious vibration. The balance of washing machine plays an important role in order to reduce the vibration by injecting the sand or the salt water into the balance of washing machine. The hot plate welder is used to prevent from outflow of contents. The hot plate welder brings about many problems which is concerned with accidents. The direction recognition and location information of the balance are required in this system. In this paper, the recognition direction of balance in washing machine using machine vision system is studied. The template matching algorithm compares sub-image with original image acquired in real-time to obtain a center point of balance image. The mid points and the edges of balance are estimated by the edge detection and gauging algorithms. The data acquired by these results is used for recognition direction of balance. The automation software for image processing is developed by using LabVIEW.

• Journal of Institute of Convergence Technology
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• v.3 no.2
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• pp.31-37
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• 2013

This paper proposes a vision-based inspection algorithm for a punch which is used when forming the head of the small screws. To maintain good quality of punch, the precise inspection of its dimension and the depth of the punch head is important. A CCD camera and an illumination dome light are used to measure its dimensions. And a structured line laser is also used to measure the depth of the punch head. Resolution and visible area depend on setup between laser and camera which is determined using CAD-based simulation. The proposed method is successfully evaluated using experiment on #2 punch.