• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.317-325
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• 2022

In this study, we propose a technological system designed to provide machine vision-based automatic inspection and autonomous operation services for an entire process related to product inspection in wire harness manufacturing. The smart factory paradigm is a valuable and necessary goal, small companies may encounter steep barriers to entry. Therefore, the best approach is to develop towards this approach gradually in stages starting with the relatively simple improvement to manufacturing processes, such as replacing manual quality assurance stages with machine vision-based inspection. In this study, we consider design issues of a system based on the proposed technology and describe an experimental implementation. In addition, we evaluated the implementation of the proposed technology. The test results show that the adoption of the proposed machine vision-based automatic inspection and operation service system for multi-wire harness production may be considered justified, and the effectiveness of the proposed technology was verified.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.337-346
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• 2022

This paper addresses the problem of vision-based ear loops ansd attachment inspection in mask production lines. This paper focuses on connections with ear loops and mask filter by an efficient combined approach. The proposed method used a template matching, shape detection and summation of histogram with preprocessing. We had a parameter for detecting defects heuristically. If the shape vertices are lower than the parameters our proposed method will find defective mask automatically. After finding normal masks in mask ear loops attachment status inspection algorithm our proposed method conducts attachment amount inspection. Our experimental results showed that the precision is 1 and the recall is 0.99 in the mask attachment status inspection and attachment amount inspection.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.12
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• pp.7-13
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• 1998

In this paper, an automatic ball-stud inspection system has been developed using the computer-aided vision system. Index table has been used to get the rapid measurement and multi-camera has been used to get the high resolution in physical system. Camera calibration was suggested to perform the reliable inspection. Image processing and data analysis algorithms for ball stud inspection system have been investigated and were performed quickly with high accuracy. As a result, inspection system of a ball stud could be used with a high resolution in real time.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.13-23
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• 2001

Most current machine vision systems for industrial inspection were developed with one specific task in mind. Hence, these systems are inflexible in the sense that they cannot easily be adapted to other applications. In this paper, a general vision system framework has been developed that can be easily adapted to a variety of industrial web inspection problems. The objective of this system is to automatically locate and identify \\\"defects\\\" on the surface of the material being inspected. This framework is designed to be robust, to be flexible, and to be as computationally simple as possible. To assure robustness this framework employs a combined strategy of top-down and bottom-up control, hierarchical defect models, and uncertain reasoning methods. To make this framework flexible, a modular Blackboard framework is employed. To minimize computational complexity the system incorporates a simple multi-thresholding segmentation scheme, a fuzzy logic focus of attention mechanism for scene analysis operations, and a partitioning if knowledge that allows concurrent parallel processing during recognition.cognition.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.11
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• pp.61-68
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• 2004

Recently, there has been an increasing demand for computer-vision based inspection and/or measurement system as a part of factory automation equipment. Existing manual inspection method can inspect only specific samples and has low measuring accuracy as well as it increases working time. Thus, in order to improve the objectivity and reproducibility, computer-aided analysis method is needed. In this paper, front and side profile inspection and/or data transfer system are developed using computer-vision during the inspection process on three kinds of pipes coming from a forming line. Straight line and circle are extracted from profiles obtained from vision using Laplace operator. To reduce inspection time, 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 and whether good or bad. Also, an inspection system has been built that each pipe's data and images of good/bad test are stored as files and transferred to the server so that the center can manage them.

• Proceedings of the Optical Society of Korea Conference
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• 2007.07a
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• pp.365-366
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• 2007

Micro jetting drop inspection system is essential to measuring micro drop volume. Measuring pico-liter drop volume is useful for new LCD color filter product process that is based on inkjet printing technology. To upgrade the reliability in drop measurement system, we use the auto focusing & multi drop reiteration & blurring average algorism. First of all we used standard mark for gage R&R in the vision system. Finding the most suitable threshold for multi blurring drop, is the main key of this research. Sensitivity of vision system is a standard in measuring the upgrade system level. So, suitable threshold can upgrade the performance of jetting drop inspection system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.19-24
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• 2004

A novel fast parallel NTGST is proposed for high resolution computer vision inspection of the BLUs in a LCD production line. The conventional computation- intensive NTGST algorithm is modified and its C codes are optimized into fast NTGST to be adapted to the SIMD parallel architecture. And then, the input inspection image is partitioned and allocated to each of the P processors in multi-threaded implementation, and the NTGST is executed on SIMD architecture of N data items simultaneously in each thread. Thus, the proposed inspection system can achieve the speedup of O(NP). Experiments using Dual-Pentium III processor with its MMX and extended MMX SIMD technology show that the proposed parallel NTGST is about Sp=8 times faster than the conventional NTGST, which shows the scalability of the proposed system implementation for the fast, high resolution computer vision inspection of the various sized BLUs in LCD production lines.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.12
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• pp.92-99
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• 2004

The formation degree of sustain (ITO pattern) decides quality of PDP (Plasma Display Panel). For this reason, it makes efforts in searching defects more than 30 un as 100%. Now, the existing inspection is dependent upon naked eye or microscope in off-line PDP manufacturing process. In this study developed prototype inspection system of PDP 170 glass is based on line-scan mechanism. Developed system creates information that detects and sorts kinds of defect automatically. Designed inspection technology adopts multi-vision method by slip-beam formation for the minimum of inspection time and detection algorithm is embodied in detection ability of developed system. Designed algorithm had to make good use of kernel matrix that draws up an approach to geometry. A characteristic of defects, as pin hole, substance, protrusion, are extracted from blob analysis method. Defects, as open, short, spots and et al, are distinguished by line type inspection algorithm. In experiment, we could have ensured ability of inspection that can be detected with reliability of up to 95% in about 60 seconds.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.3
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• pp.18-23
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• 2006

The formation degree of sustain (ITO pattern) determines the quality of a PDP (Plasma Display Panel). Thus, in the present study, we attempt to detect 100% of the defects that are larger than $30{\mu}m$. Currently, the inspection method in the PDP manufacturing process is dependent upon the naked eye or a microscope in off-line mode. In this study, a prototype inspection system for PDP ITO patterned glass is developed. The developed system, which is based on a line-scan mechanism, obtains information on the defects and sorts the defects by type automatically. The developed inspection system adopts a multi-vision method using slit-beam formation for minimum inspection time and the detection algorithm is embodied in the detection ability. Characteristic defects such as pin holes, substances, and protrusions are extracted using the blob analysis method. Defects such as open, short, spots and others are distinguished by the line type inspection algorithm. It was experimentally verified that the developed inspection system can detect defects with reliability of up to 95% in about 60 seconds for the 42-inch PDP panel.