• Proceedings of the Optical Society of Korea Conference
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• 2006.07a
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• pp.469-471
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• 2006

This paper describes a efficient insepction method of PCB PADs for AFVI. The methods for PCB inspection have been tried to detect the defects in PCB PADs, but their low detection rate results from pattern variations that are originating from etching, printing and handling processes. The adaptive inspection method has been newly proposed to extract minute defects based on dynamic segments and filters. The vertexes are extracted from CAM master images of PCB and then a lot of segments are constructed in master data. The proposed method moves these segments to optimal directions of a PAD contour and so adaptively matches segments to PAD contours of inspected images, irrespectively of various pattern variations. It makes a fast, accurate and reliable inspection of PCB patterns. Experimental results show that proposed methods are found to be effective for flexible defects detection.

• Journal of the Korea Society of Computer and Information
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• v.20 no.10
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• pp.23-29
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• 2015

In this paper, we suggest a method of detecting defects by applying Hough transform and least squares on ceramic images obtained from non-destructive testing. In the ceramic images obtained from non-destructive testing, the background area, where the defect does not exist, commonly show gradual change of luminosity in vertical direction. In order to extract the background area which is going to be used in the detection of defects, Hough transform is performed to rotate the ceramic image in a way that the direction of overall luminosity change lies in the vertical direction as much as possible. Least squares are then applied on the rotated image to approximate the contrast value of the background area. The extracted background area is used for extracting defects from the ceramic images. In this paper we applied this method on ceramic images acquired from non-destructive testing. It was confirmed that extracted background area could be effectively applied for searching the section where the defect exists and detecting the defect.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.241-244
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• 2006

It is essential to develop a large capacity, non-contact nondestructive inspection system having high reliability to investigate repaired and strengthened structures. Nowadays, an infrared camera is widely used in non-contact nondestructive inspection system. Because an infrared camera is sensitive to the surrounding environment, it is necessary to improve a sensitivity of thermal image information and a relationship between defects and thermal image information. In this papaer, presented is an optimum void detection chart for the optimum conditions to detect infrared rays from inside and outside defects like voids and cracks in concrete structures using extensive computer simulation. Sensitivity studies are performed with respect to variables influencing the temperature distribution such as heating temperature, heating time, and geometries of defect, etc. It may be stated that it could be successfully utilized for the non-contact nondestructive inspection system to detect defects in concrete structures.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.2
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• pp.128-134
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• 2014

Infrared thermography is an emerging approach to non-contact, non-intrusive, and non-destructive inspection of various solid materials such as metals, composites, and semiconductors for industrial and research interests. In this study, data processing was applied to infrared thermography measurements to detect defects in metals that were widely used in industrial fields. When analyzing experimental data from infrared thermographic testing, raw images were often not appropriate. Thus, various data analysis methods were used at the pre-processing and processing levels in data processing programs for quantitative analysis of defect detection and characterization; these increased the infrared non-destructive testing capabilities since subtle defects signature became apparent. A 3D finite element simulation was performed to verify and analyze the data obtained from both the experiment and the image processing techniques.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_2
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• pp.687-697
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• 2022

An automated system is needed for the effectiveness of non-destructive testing. In order to utilize the radiographic testing data accumulated in the film, the types of welding defects were classified into 9 and the shape of defects were analyzed. Data was preprocessed to use deep learning with high performance in image classification, and a combination of one-stage/two-stage method and convolutional neural networks/Transformer backbone was compared to confirm a model suitable for welding defect detection. The combination of two-stage, which can learn step-by-step, and deep-layered CNN backbone, showed the best performance with mean average precision 0.868.

• Journal of the Semiconductor & Display Technology
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• v.23 no.2
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• pp.135-142
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• 2024

Cu-Cu bonding, one of the key technologies in advanced packaging, enhances semiconductor chip performance, miniaturization, and energy efficiency by facilitating rapid data transfer and low power consumption. However, the quality of the interface bonding can significantly impact overall bond quality, necessitating strategies to quickly detect and classify in-process defects. This study presents a methodology for detecting defects in wafer junction areas from Scanning Acoustic Microscopy images using a ResNet-50 based deep learning model. Additionally, the use of the defect map is proposed to rapidly inspect and categorize defects occurring during the Cu-Cu bonding process, thereby improving yield and productivity in semiconductor manufacturing.

• Journal of the Korean Society for Nondestructive Testing
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• v.18 no.6
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• pp.445-454
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• 1998

In order to establish a technical concept for the detection of defects in weldments in thin steel plate, an experimental and theoretical investigation was carried out for artificial defects in a steel plate having a thickness of 2.4mm by using the guided wave technique. In particular the goal was to find the most effective testing parameters paying attention to the relationship between the excitation frequency by a tone burst system and various incident angles. It was found that the test conditions that worked best was for a frequency of 840kHz and an incident angle of 30 or 85 degrees, most of the defects were detected with these conditions. Also, it was clear that a guided wave mode generated under an incident angle of 30 degrees was a symmetric mode, So, and that of 85 degrees corresponded to an antisymmetric mode, Ao. By using the two modes, most of all of the defects could be detected. Furthermore, it was shown that the antisymmetric mode was more sensitive to defects near the surface than the symmetric mode. Theoretical predictions confirmed this sensitivity improvement with Ao for surface defects because of wave structure variation and energy concentration near the surface.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.4 s.193
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• pp.15-20
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• 2007

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.3
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• pp.58-67
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• 2000

Electron gun heaters are used to heat a cathode in video(TV) monitors. Major defects of the electron gun heaters include dimensional inaccuracy and pollution with dirty materials. In this paper, to save the labor and time being taken to inspect the heaters, a machine vision system is considered. For the system, a new algorithm is developed to measure the 9 different dimensions of each heater and to detect polluted defects. The algorithm consists of three stages. In the first stage, the center of the heater image is obtained and then its boundary detection is performed. For the efficient boundary detection, a mask called the sum mask is used. In the second stage of the algorithm, a set of fiducial points are determined on the boundary image. Finally, using the fiducial points specified dimensions are measured and the amount of polluted area is computed in the third stage. The performance of the algorithm is evaluated for a set of real specimens. The results indicate that measurements obtained by the algorithm satisfy the tolerance limits fur most of the dimensions and the algorithm detects the polluted defects successfully.