• Journal of Korea Society of Industrial Information Systems
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• v.19 no.4
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• pp.41-52
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• 2014

In this paper, O-ring size measurement algorithm based on a small machine vision inspection equipment which can replace a expensive and large machine vision inspection equipment is presented. The small machine vision inspection equipment acquires a image from a CCD camera shooting a measurement plane which located on a back light and the proposed size measurement algorithm is apply to the image. For improvement of size measurement accuracy, camera lens distortion correction and perspective distortion correction are conducted by software technique. Consider O-ring's shape, ellipse fitting model is applied. In order to increase the reliability of ellipse fitting, RANSAC algorithm is applied.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.126-130
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• 2021

The ball grid array is one of the packaging methods that used in high density printed circuit board. Solder void defects caused by voids in the solder ball during the BGA process do not directly affect the reliability of the product, but it may accelerate the aging of the device on the PCB layer or interface surface depending on its size or location. Void inspection is important because it is related in yields with products. The most important process in the optical inspection of solder void is the segmentation process of solder and void. However, there are several segmentation algorithms for the vision inspection, it is impossible to inspect all of images ideally. When X-Ray images with poor contrast and high level of noise become difficult to perform image processing for vision inspection in terms of software programming. This paper suggests the solution to deal with the suggested problem by means of using Mask R-CNN instead of digital image processing algorithm. Mask R-CNN model can be trained with images pre-processed to increase contrast or alleviate noises. With this process, it provides more efficient system about complex object segmentation than conventional system.

• Journal of Practical Engineering Education
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• v.6 no.1
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• pp.37-42
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• 2014

The automated visual inspection system (machine vision system) for quality assurance is important factory automation equipment in the manufacturing industries, such as display, semiconductor, etc. There is a lot of demand for the machine vision engineers. However, there are no technical training courses for machine vision technologies in vocational schools, colleges and universities. In this paper, we present the implementation of line scan camera based equipment for technical training of the automated visual inspection system. The training system consists of the X-Y stage which is widely used in machine vision industries and its variable image resolution are set to $10-30{\mu}m$. Additionally, this training system can attach the industrial illumination, either the direct illuminator or coaxial illuminator, for verifying the effect of illuminations. This means that the trainee can have a practical training in various equipment conditions and the training system is similar to the automated visual inspection system in industries.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.30-34
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• 2006

Recently, there has been an increasing demand for computer-vision-based inspection and/or measurement system as a part of factory automation equipment. In general, it is almost impossible to check the fault of all parts, coming from part-feeding system, with only manual inspection because of time limitation. Therefore, most of manual inspection is applied to specific samples, not all coming parts, and manual inspection neither guarantee consistent measuring accuracy nor decrease working time. Thus, in order to improve the measuring speed and accuracy of the inspection, a computer-aided measuring and analysis method is highly needed. In this paper, a computer-vision-based pipe inspection system is proposed, where the front and side-view profiles of three different kinds of pipes, coming from a forming line, are acquired by computer vision. And the edge detection is processed by using Laplace operator. To reduce the vision processing time, modified 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 of the parts. Also, an inspection system has been built so that the data and images of faulted parts are stored as files and transferred to the server.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.6
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• pp.30-35
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• 2022

This study has focused on the reliability evaluation of FCT inspection automation equipment for electric rice. To evaluate the reliability of FCT inspection automation equipment, voice analysis, Gray/R/G/B channel experiment, FND segment experiment, and robot position repeatability were performed. In the voice analysis experiment, the comparison value between the recorded and digital output waves was over 99%, indicating a very high result. It was confirmed that both the gray/R/G/B experiment using vision and the FND segment could confirm the output value of the product through vision. The position repeatability of the robot is also excellent, so it is concluded that the inspection effect through the FCT automation system will be excellent.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.257-263
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• 2018

The purpose of this study is to develop an automatic inspection system for a part of the differential drive gear into the transmission. This technology will make using the microvision automatic test equipment and automatic test equipment microlaser. This is that the operator intends to make the defect rate 0 in the inspection stage of the product which has been carelessly processed. The equipment developed in this research project will be applied to many areas. Packaging companies, nut bolt processing company, precisely supplier for printing on top of the semiconductor, SMT, etc. The company wants to sell the vision inspection equipment for various applications. If the defective rate of 0 is achieved through this research project, it is also possible to secure a stable supply from the parent company, and to lay the foundations for exporting based on product reliability. When the automatic inspection system is applied to domestic automobile parts processing companies, the reliability of automobiles in Korea will be greatly increased.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.127-132
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• 2019

In this paper, we propose a visual inspection method of automotive parts for injection molding to improve the appearance quality and productivity of automotive parts. Exterior inspection of existing injection molding automobile parts was generally done by manual sampling inspection by human. First, we applied the edge-tolerance vision inspection algorithm ([1] - [4]) for vision inspection of electronic components (TFT-LCD and PCB) And we propose a new visual inspection method to overcome the problem. In the proposed visual inspection, the inspection images of the parts to be inspected are aligned on the basis of the reference image of good quality. Then, after partial adaptive binarization, the binary block matching algorithm is used to compare the good binary image and the test binary image. We verified the effectiveness of the edge-tolerance vision check algorithm and the proposed appearance vision test method through various comparative experiments using actual developed equipment.

• Journal of Sensor Science and Technology
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• v.33 no.3
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• pp.179-184
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• 2024

In the car industry, welding is a fundamental linking technique used for joining components, such as steel, molds, and automobile parts. However, accurate inspection is required to test the reliability of the welding components. In this study, we investigate the detection of weld beads using 2D image processing in an automatic recognition system. The sample image is obtained using a 2D vision camera embedded in a lighting system, from where a portion of the bead is successfully extracted after image processing. In this process, the soot removal algorithm plays an important role in accurate weld bead detection, and adopts adaptive local gamma correction and gray color coordinates. Using this automatic recognition system, geometric parameters of the weld bead, such as its length, width, angle, and defect size can also be defined. Finally, on comparing the obtained data with the industrial standards, we can determine whether the weld bead is at an acceptable level or not.

• Journal of Information Technology Services
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• v.17 no.3
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• pp.53-61
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• 2018

In this paper, we propose a car sealing monitoring system combined with ICT Technology. The automobile sealer is an adhesive used to bond inner and outer panels of doors, hoods and trunks of an automobile body. The proposed car sealer monitoring system is a system that can accurately and automatically inspect the condition of the automobile sealer coating process in the general often factory production line where the lighting change is very severe. The sealer inspection module checks the state of the applied sealer using an area scan camera. The vision inspection algorithm is adaptive to various lighting environments to determine whether the sealer is defective or not. The captured images and test results are configured to send the task results to the task manager in real-time as a smartphone app. Vision inspection algorithms in the plant outdoors are very vulnerable to time-varying external light sources and by configuring a monitoring system based on smart mobile equipment, it is possible to perform production monitoring regardless of time and place. The applicability of this method was verified by applying it to an actual automotive sealer application process.