• Journal of the Semiconductor & Display Technology
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• v.19 no.3
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• pp.12-18
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• 2020

In semiconductor manufacturing, defect detection is critical to maintain high yield. Currently, computer vision systems used in semiconductor photo lithography still have adopt to digital image processing algorithm, which often occur inspection faults due to sensitivity to external environment. Thus, we intend to handle this problem by means of using Mask R-CNN instead of digital image processing algorithm. Additionally, Mask R-CNN can be trained with image dataset pre-processed by means of the specific designed digital image filter to extract the enhanced feature map of Convolutional Neural Network (CNN). Our approach converged advantage of digital image processing and instance segmentation with deep learning yields more efficient semiconductor photo lithography inspection system than conventional system.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.225-230
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• 2009

We propose a template matching method for component inspection of SMD assembly system. To discriminate wrong assembled components, the input image of component is matched with its standard image by template matching algorithm. For a fast inspection system, the calculation time of matching algorithm should be reduced. Since the standard images of all components located in a PCB are stored in computer, it is desirable to reduce the memory size of standard image. We apply the discrete wavelet transformation to reduce the image size as well as the calculation time. Only 7% memory of the BMP image is used to discriminate goodness or badness of components assembly. Comparative results are presented to verify the usefulness of the proposed method.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.5
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• pp.135-143
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• 2000

The vision system is easy to use the exclusive use as a independent computer system but it is not much popularization by reason of expensive and difficult to adapt to the various fields, because it is easy to the existed computer system, the price is cheap and also it can use to the various measurement purpose which user wanted and programed. The measurement method of the vehicle axle casing nut welding part is that measure the value of the welding part to adapt the actual operation program from using the ratio between the actual length of the standard specimen and the length of image, to measure the ratio between the actual product and the camera image. A defect is found by the assembled visual inspection system. The inspection algorithm which estimates the quality of welded product is developed and also, the software program which processes the automatic test function of the inspection system. We make the foundation of the inspection automatic system and we will help to apply other welding machine.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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• pp.1089-1095
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• 2010

We propose an image segmentation method for auto-teaching system of PCB (Printed Circuit Board) assembly inspection machines. The inspection machine acquires images of all components in PCB, and then compares each image with its standard image to find the assembly errors such as misalignment, inverse polarity, and tombstone. The component window that is the area of component to be acquired by camera, is one of the teaching data for operating the inspection machines. To reduce the teaching time of the machine, we newly develop the image processing method to extract the component window automatically from the image of PCB. The proposed method segments the component window by excluding the soldering parts as well as board background. We binarize the input image by use of HSI color model because it is difficult to discriminate the RGB colors between components and backgrounds. The linear combination of the binarized images then enhances the component window from the background. By use of the horizontal and vertical projection of histogram, we finally obtain the component widow. The experimental results are presented to verify the usefulness of the proposed method.

• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.238-244
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• 2021

Image mosaicking is a common and useful technique to visualize a global map by stitching a large number of local images obtained from visual surveys in underwater environments. In particular, visual inspection of underwater structures using underwater robots can be a potential application for image mosaicking. Feature-based pairwise image registration is a commonly employed process in most image mosaicking algorithms to estimate visual odometry information between compared images. However, visual features are not always uniformly distributed on the surface of underwater structures, and thus the performance of image registration can vary significantly, which results in unnecessary computations in image matching for poor-conditioned image pairs. This study proposes a pairwise registrability measure to select informative image pairs and to improve the overall computational efficiency of underwater image mosaicking algorithms. The validity and effectiveness of the image mosaicking algorithm considering the pairwise registrability are demonstrated using an experimental dataset obtained with a full-scale ship in a real sea environment.

• Proceedings of the Optical Society of Korea Conference
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• 2008.07a
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• pp.403-404
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• 2008

This report described the development of Vision Inspector program which can simulate numerically the image acquisition process of Machine Vision System for automatic optical inspection of any products. The program consists of an illuminator, a product to be inspected, and a camera with image sensor, and the final image obtained by ray tracing.

• International Journal of Contents
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• v.14 no.3
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• pp.17-26
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• 2018

To ensure safety of bridges, it is critical to inspect and assess physical and functional conditions regularly. Presently, most highway bridges in the U.S. are inspected visually. However, this method of inspection is often influenced by the bridge inspector's knowledge and experience. So, reliability and accuracy of inspection results may be problematic. To solve such problems, an extensive number of robotics systems and image processing techniques for bridge inspection methods have been proposed. These robotics systems and image processing techniques are used to measure various bridge conditions, such as apparent damage, displacement and dynamic characteristics. This paper provides a comprehensive review of robotics systems and image processing technologies used in bridge inspection.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2335-2338
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• 2003

This paper presents a real-time PCB (Printed Circuit Board) vision inspection system. This system can detect the OPEN and SHORT of the PCB which of the line width is 150$\mu\textrm{m}$. Our PCB inspection system is based on the referential method. Since the size of the captured PCB image is very large, the image is divided into 512${\times}$512 images to apply the accurate alignment efficiently. To correct the misalignment between the reference image and the inspection image, pattern matching is performed. In order to implement the proposed algorithm in real-time, we use the SIMD instruction and the double buffering structures. Our experiential results show the effectiveness of the developed inspection algorithm.

• Textile Coloration and Finishing
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• v.21 no.1
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• pp.53-58
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• 2009

A real-time inspection system has been developed by combining CCD based image processing algorithm and a standard lighting equipment. The system was tested for defective fabrics showing nozzle contact scratch marks, which were one of the frequently occurring defects. Multi-resolution analysis(MRA) algorithm were used and evaluated according to both their processing time and detection rate. Standard value for defective inspection was the mean of the non-defect image feature. Similarity was decided via comparing standard value with sample image feature value. Totally, we achieved defective inspection accuracy above 95%.

• Journal of the Semiconductor & Display Technology
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• v.11 no.3
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• pp.39-44
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• 2012

Electronics in modern lives have become more miniaturized and precise. Multi Layered Ceramic Capacitor (MLCC) occupies 50% of electronic components consisting of electronics. This high volume of the production needs high speed and more precise machine performances. The dominate parts of the production equipments are the module transporting components and the visual inspection module. Most visual inspection has been off-line because of the image processing time. In this paper, a new image processing method is proposed to reduce thousands of matrix calculation for image processing and realize on-line high speed inspection.