• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.277-283
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• 2021

This paper addresses the problem of vision-based mask filter inspection for mask production systems. Machine learning-based approaches can be considered to solve the problem, but they may not be applicable to mask filter inspection if normal and anomaly mask filter data are not sufficient. In such cases, handcrafted image processing methods have to be considered to solve the problem. In this paper, we propose a hierarchical correlation-based approach that combines handcrafted image processing methods to detect anomaly mask filters. The proposed approach combines image rotation, cropping and resizing, edge detection of mask filter parts, average blurring, and correlation-based decision. The proposed approach was tested and analyzed with real mask filters. The results showed that the proposed approach was able to successfully detect anomalies in mask filters.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.389-390
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• 2006

The goal of this paper is automation of a remocon inspection process using machine vision system. This system prevents error that is occurred by physical and spirit condition of human. Also this system has been developed to raise the reliability of remocon inspection. This system has been developed only using PC, CCD Camera and Visual C++ for universal workplaces. The performance of this system is an accuracy improvement of $2{\sim}3[%]$ and a processing time reduction of about 100[ms] against existing pattern matching method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2113-2120
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• 2013

In this study, an efficient machine vision based inspection system is developed for the in-line measurement of phosphor resin dispensing shapes on LED chip package. Since the phosphor resin (target material) has semitransparent characteristics, illuminated light beam is reflected from the bottom of the chip as well as from the surface. Since such phenomenon can deteriorate inspection reliability, a white LED and a 635nm laser slit beams are experimentally tested to decide suitable illumination optics. Also, specular and diffuse reflection methods are tested to decide suitable optical triangulation. As a result, it can be known that the combination of a white slit beam source and specular reflection method show the best inspection results. The Catmull-Rom spline interpolation is applied to the obtained data to form smoother surface. From the results, it can be conclude that the developed system can be sucessfully applied to the in-line inspection of LED chip packaging process.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.5
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• pp.666-672
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• 2011

In this paper, we describes the development of automatic inspection system for detecting the defects on photovoltaic wafer by using machine vision. Until now, The defect inspection process was manually performed by operators. So these processes caused the produce of poorly-made articles and inaccuracy results. To improve the inspection accuracy, the inspection system is not only configured, but the image processing algorithm is also developed. The inspection system includes dimensional verification and pattern matching which compares a 2-D image of an object to a pattern image the method proves to be computationally efficient and accurate for real time application and we confirmed the applicability of the proposed method though the experience in a complex environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.6
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• pp.1157-1162
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the color product.(bad pallets) An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE color pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labelling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets. The labelling algorithm permits to separate all of the connected components appearing on the pallets. Labelling the connected regions of a image is a fundamental computation in image analysis and machine vision, with a large number of application. Also, we suggested vision processing program in window environment. Simulations and experimental results demonstrate the performance of the proposal algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.587-591
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the color product.(bad pallets) An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE color pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labelling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets. The labelling algorithm permits to separate all of the connected components appearing on the pallets. Labelling the connected regions of a image is a fundamental computation in image analysis and machine vision, with a large number of application. Also, we suggested vision processing program in window environment. Simulations and experimental results demonstrate the performance of the proposal algorithm.

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

• The monthly packaging world
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• s.252
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• pp.45-49
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• 2014

• Journal of the Korean Society for Precision Engineering
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• v.31 no.3
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• pp.261-268
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• 2014

Precision screws have a wide range of industrial applications such as electrical and automotive products. To produce screw threads with high precision, not only high precision manufacturing technology but also reliable measurement technology is required. Machine vision systems have been used in the automatic inspection of screw threads based on backlight illumination, which cannot detect defects on the thread surface. Recently, an omnidirectional inspection system for screw threads was developed to obtain $360^{\circ}$ images of screws, based on front light illumination. In this study, the illumination design for the omnidirectional inspection system was modified by adding a light shield to improve the image uniformity. Optical simulation for various shield designs was performed to analyze image uniformity of the obtained images. The simulation results were analyzed statistically using response surface method, from which optical performance of the omnidirectional inspection system could be optimized in terms of image quality and uniformity.

• 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.