• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2003.04a
• /
• pp.245-250
• /
• 2003

Today, automobile world market is highly competitive. In order to strengthen the competitiveness, quality of automobile is recognized as important and efforts are being made to improve the quality of manufactured components. The directional ability of automobile has influenced on driver directly and hence it must be solved on the preferential basis. In the present research an automated vision system has been developed th inspect the front chassis module. To interpret the inspection data obtained for front chassis module, new interpreting algorithm have been developed. Previously the control of tolerance front chassis module was done manually. With the help of the new algorithm developed, the dimension is calculated automatically to check whether the front chassis module is within the tolerance limit or not.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.11
• /
• pp.21-28
• /
• 2023

In manufacturing companies that focus on small-scale production of multiple product varieties, defective products are manually selected by workers rather than relying on automated inspection. Consequently, there is a higher risk of incorrect sorting due to variations in selection criteria based on the workers' experience and expertise, without consistent standards. Moreover, for non-standardized flexible objects with varying sizes and shapes, there can be even greater deviations in the selection criteria. To address these issues, this paper designs a quality inspection system using artificial intelligence-based unsupervised learning methods and conducts research by experimenting with accuracy using a dataset obtained from real manufacturing environments.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.11
• /
• pp.53-61
• /
• 1996

In this paper, efficient techniques for solder joint inspection have been described. Using three layers of ring shaped LED's with different illumination angles, three frames of images are sequentially obtained. From these images the regions of interest (soldered regions) are segmented, and their characteristic features including the average gray level and the percentage of highlights - refereed to as 2D features - are extracted. Based on the backpropagation algorithm of neural networks, each solder joint is classified intor one of the pre-defined types. If the output value is not in the confidence interval, the distribution of tilt angles-referred to as 3D features - is claculated, and the solder joint is classified based on the bayes classfier. The second classifier requires more computation while providing more information and better performance. The proposed inspection system has been implemented and tested with various types of solder joints in SMDs. The experimental results have verified the validity of this scheme in terms of speed and recognition rate.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.11
• /
• pp.974-978
• /
• 2013

AVI (Automatic Vision Inspection) systems automatically detect defect features and measure their sizes via camera vision. AVI systems usually report different measurements on the same defect with some variations on position or rotation mainly because different images are provided. This is caused by possible variations from the image acquisition process including optical factors, nonuniform illumination, random noises, and so on. For this reason, conventional area based defect measuring methods have problems of robustness and consistency. In this paper, we propose a new defect size measuring method to overcome this problem, utilizing volume information that is completely ignored in the area based defect measuring method. The results show that our proposed method dramatically improves the robustness and consistency of defect size measurement.

• Journal of Korea Multimedia Society
• /
• v.15 no.2
• /
• pp.204-214
• /
• 2012

This paper proposes an image segmentation for a vision-based automated defect inspection system on surface image of TFT-LCD(Thin Film Transistor Liquid Crystal Display) panels. TFT-LCD images have non-uniform brightness, which is hard to finding defective regions. Although there are several methods or proposed algorithms, it is difficult to divide the defect with high reliability because of non-uniform properties in the image. Kamel and Zhao disclosed a method which based on logical stage algorithm for segmentation of graphics and character. This method is a one of the local segmentation method that has a advantage. It is that characters and graphics are well segmented in an image which has non-uniform property. As TFT-LCD panel image has a same property, so this paper proposes new algorithm to segment regions of defects based on Kamel and Zhao's algorithm. Our algorithm has an advantage that there are a few ghost objects around the defects. We had experiments to prove performance in real TFT-LCD panel images, and comparing with the FFT(Fast Fourier Transform) method which is used a bandpass filter.

• Journal of the Microelectronics and Packaging Society
• /
• v.8 no.3
• /
• pp.1-9
• /
• 2001

This paper proposes an inspection algorithm for micro ball grid array ($\mu$BGA) solder balls. This algorithm is motivated by the difficulty of finding defect balls by human visual inspection due to their small dimensions. Specifically, it is developed herein an automated vision-based inspection algorithm for $\mu$BGA's, which can inspect solder balls not only for so-called two dimensional errors, such as missings, positions and sizes, but also for height errors. The inspection algorithm uses two dimensional images of $\mu$BGA obtained through special blue illumination, and processes them with a rotation-invariant sub algorithm. It can also detect height errors when a two-camera system is available. Simulation results show that the proposed algorithm is more efficient in detecting ball defects compared with the conventional algorithms.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2006.05a
• /
• pp.631-632
• /
• 2006

The assembly of camera lens modules fur the mobile phone has not been automated so far. They are still assembled manually because of high precision of all parts and hard-to-recognize lens by vision camera. In addition, the very short life cycle of the camera phone lens requires flexible and intelligent automation. This study proposes a fast and accurate identification system of the parts by distributing the camera for 4 degree of freedom assembly robot system. Single or multi-cameras can be installed according to the part's image capture and processing mode. It has an agile structure which enables adaptation with the minimal job change. The framework is proposed and the experimental result is shown to prove the effectiveness.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10b
• /
• pp.1742-1747
• /
• 1991

Since inspection, ID-code recognition, and pattern match processes requiring vision depend upon the high-grade human recognition capability, these processes have conventionally caused a bottle-neck in automatizing sewing system. However, the authors have recently developed the technology of inspecting the surface defects of textiles and recognizing ID-code by fully utilizing the image processing technology. In the ID-code recognition technology, the most difficult data given on patterns can be read as a result of developing the image processing technology and eliminating noises by using a special (fluorescent) ink. The inspection and pattern match technology was verified to be able to put into practical use through evaluation experiments in an experimental plant.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.1
• /
• pp.453-458
• /
• 2016

One of the most common applications of machine vision is quality inspections in automated production. In this study, a welding inspection system that is controlled by a PC and a PLC equipped with a multi-camera setup was developed. The system was designed to measure the primary dimensions, such as the length and width of the welding areas. The TCP/IP protocols and multi-threading techniques were used for parallel control of the optical components and physical distribution. A coaxial light was used to maintain uniform lighting conditions and enhance the image quality of the weld areas. The core image processing system was established through a combination of various algorithms from the OpenCV library. The proposed vision inspection system was fully validated for an actual weld production line and was shown to satisfy the functional and performance requirements.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.21 no.5
• /
• pp.421-427
• /
• 2008

A robot crane truck is developed by the Bridge Inspection Robot Development Interface(BRIDI) for an automated and/or teleoperated bridge inspection. This crane truck looks similar to the conventional bucket crane, but is much smaller in size and light-weight. At the end of the telescoping boom which is 12m long, a robot platform is mounted which allows the operator to scan the bridge structure under the deck trough the camera. Boom vibration induced by wind and deck movement can cause serious problems in this scanning system. This paper presents a control system to mitigate such vibration of the robot boom. In the proposed control system, an actuator is installed at the end of the working boom. This control system is studied using a mathematical model analysis with LQ control algorithm and a scaled model test in the laboratory. The study indicates that the proposed system is efficient for the vibration control of the robot booms, thereby demonstrating its immediate applicability in the field.