• Journal of Information Technology Applications and Management
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• v.29 no.6
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• pp.135-144
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• 2022

In this study, we transformed 4680 type lithium-ion batteries to 3-dimensional CAD models and present a methodology to detect defects using Radon inverse transformation. Transparency was applied to the model to make it look like a CT image when viewed from the front. One normal and three defect models were created and analyzed. The models were saved as image files while rotating at a certain angle. Then, we used the Radon inverse transformation to reconstruct the original 3D geometry from the image files. Finally, we successfully found defects in the defect models for three cases.

• Journal of Navigation and Port Research
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• v.28 no.1
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• pp.43-49
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• 2004

Defects inspection of commodities are very important with those design and manufacturing process and essential to strengthen the competitiveness of those. If on-line automatic defects detection is performed without damaging to products, the production cost shall be curtailed through the reducing man-power, economical management of Q.C(Quality Control). In this paper, it is suggested three spatial filtering methods which can extract the necessary information in case of defects being on the surface of object like iron plate. In addition, the dependence of filtering characteristics on parameters such as the pitch and width of slits is analyzed and the surface defect detection system is constructed. Several experiments were carried out for determining the adequate spatial filtering method through comparing and analyzing effects of parameters like defect's size and shape, intensity of light, noise of coherent source and slit number.

• 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 Korea Multimedia Society
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• v.18 no.3
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• pp.312-322
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• 2015

In this paper a new defect detection method for flat panel display that does not require any separately prepared reference images and shows robustness against problems with regard to pixel tolerance and nonuniform illumination condition is proposed. In order to perform defect detection under any magnification value of camera, the proposed method automatically obtains the value of pattern interval through an image analysis. Using the information for pattern interval, an advanced PCSR-G method presented in this paper utilizes neighboring patterns as its reference images instead of utilizing any separately prepared reference images. Also this paper proposes a scheme to improve the performance of the conventional PCSR-G method by extracting and applying additional information for pixel tolerance and intensity distribution considering the value of pattern interval. Simulation results show that the performance of the proposed method utilizing pixel tolerance and intensity distribution is superior to that of the conventional method. Also, it is proved that the proposed method that is implemented using parallel technique based on GPGPU can be applied to real system.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.4
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• pp.323-329
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• 2013

This perform research of angle rated defect detection conditions and nuclear power plant piping defect detection by lock-In infrared thermography technique. Defects were processed according to change for wall-thinning length, Circumference orientation angle and wall-thinning depth. In the used equipment IR camera and two halogen lamps, whose full power capacitany is 1 kW, halogen lamps and target pipe's distance fixed 2 m. To analysis of the experimental results ensure for the temperature distribution data, by this data measure for defect length. Reliability of lock-In infrared thermography data is higher than Infrared thermography data. This through research, Shape of angle rated defect is identified industry place. It help various angles defect detection in the nuclear power plant in operation.

• Journal of the Semiconductor & Display Technology
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• v.20 no.1
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• pp.88-93
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• 2021

The automotive industry is developing day by day. Among them, it is very important to prevent accidents while driving. However, despite the importance of developing automobile industry technology, accidents due to road defects increase every year, especially in the rainy season. To this end, we proposed a road defect detection system for road management by converging deep learning and raspberry pi, which show various possibilities. In this paper, we developed a system that visually displays through a map after analyzing the images captured by the Raspberry Pi and the route GPS. The deep learning model trained for this system achieved 96% accuracy. Through this system, it is expected to manage road defects efficiently at a low cost.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.8-11
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• 2012

Automated Vision Inspection (AVI) systems automatically detect any defect feature in a surface image. The performance of the system can be measured under a special circumstances such as ultimate defect detection. In this situation, the defect signal level is similar to noise level and it becomes hard to make a solid decision with AVI systems. In this paper, we propose an effective preprocessing technique to enhance SNR (Signal to Noise Ratio). The method is motivated by some principles of HVS (Human Visual System) and RLC (Run Length Coding) techniques is used for this purpose. The proposed preprocessing technique enhances SNR under ultimate defect conditions and improves overall performance of AVI system.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1331-1346
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• 2018

Aiming at the problem that the gradient-based edge detection operators are sensitive to the noise, causing the pseudo edges, a triqubit-state measurement-based edge detection algorithm is presented in this paper. Combing the image local and global structure information, the triqubit superposition states are used to represent the pixel features, so as to locate the image edge. Our algorithm consists of three steps. Firstly, the improved partial differential method is used to smooth the defect image. Secondly, the triqubit-state is characterized by three elements of the pixel saliency, edge statistical characteristics and gray scale contrast to achieve the defect image from the gray space to the quantum space mapping. Thirdly, the edge image is outputted according to the quantum measurement, local gradient maximization and neighborhood chain code searching. Compared with other methods, the simulation experiments indicate that our algorithm has less pseudo edges and higher edge detection accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.171-171
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• 2000

We have developed m innovative surface inspection system for automated quality control for steel products in POSCO. We had ever installed the various kinds of surface inspection systems, such as a linear CCD and a laser typed surface inspection systems at cold rolled strips production lines. But, these systems cannot fulfill the sufficient detection and classification rate, and real time processing performance. In order to increase detection and classification rate, we have used the Dark, Bright and Transition Field illumination and area type CCD camera, and fur the real time image processing, parallel computing has been used. In this paper, we introduced the automatic surface inspection system and real time image processing technique using the Object Detection, Defect Detection, Classification algorithms and its performance obtained at the production line.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.3
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• pp.193-199
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• 2015

Active thermography techniques have the capability of inspecting a broad range simultaneously. By evaluating the phase difference between the defected area and the healthy area, the technique indicates the qualitative location and size of the defect. Previously, the development of the defect detection method used a variety of materials and the test specimen was done. In this study, the proposed technique of lock-in is verified with artificial specimens that have different size and depth of subsurface defects. Finally, the defect detection capability was evaluated using comparisons of the phase image and the amplitude image according to the size and depth of defects.