• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.438-443
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• 2008

In this paper, segmenting and classifying low contrast defects on flat panel display is one of the key problems for automatic inspection system in practice. Problems become more complicated when the quality of acquired image is degraded by the illumination irregularity. Many algorithms are developed and implemented successfully for the defects segmentation. However, vision algorithms are inherently prone to be dependent on parameters to be set manually. In this paper, one morphological segmentation algorithm is chosen and a technique using frequency domain analysis of input images is developed for automatically selection the morphological parameter. An extensive statistical performance analysis is performed to compare the developed algorithms.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.149-150
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• 2007

In this paper, we propose a novel defects inspection algorithm for TFT-LCD panels. We first compensate the distorted image caused by the camera distortion and the uneven illumination environment using the least squares method and the bezier surface. We find a starting point of each pattern. The reference frame, made by subtract method using several clean patterns, is compared to each pattern to find defects. The simulation example shows that our algorithm not only inspects the defects well, but also is robust to the 1-pixel error.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.6
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• pp.411-416
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• 2006

The critical subject of transverse crack detection in a rail head is treated in this paper. Conventional bulk wave ultrasonic techniques oftenfail because of shelling and other surface imperfections that shield the defects that lie below the shelling. A guided wave inspection technique is introduced here that can send ultrasonic energy along the rail under the shelling with a capability of finding the deleterious transverse crack defects. Dispersion curves are generated via a semi analytical finite element technique along with a hybrid guided wave finite element technique to explore the most suitable modes and frequencies for finding these defects. Sensor design and experimental feasibility experiments are also reported.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.870-876
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• 2017

In this paper, we proposed the automatic vision inspection system using multi-layer perceptron to detect the defects occurred on rail surface. The proposed system consists of image acquisition part and analysis part. Rail surface image is acquired as equal interval using line scan camera and lighting. Mean filter and dynamic threshold is used to reduce noise and segment defect area. Various features to characterize the defects are extracted. And they are used to train and distinguish defects by MLP-classifier. The system is installed on HEMU-430X and applied to analyze the rail surface images acquired from Honam-line at high speed up to 300 km/h. Recognition rate is calculated through comparison with manual inspection results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.379-383
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• 2005

This paper proposes a new steel strip surface inspection system. The system acquires bright and dark field images of defects by using a stroboscopic IR LED light and area camera system and the defect images are preprocessed and segmented in real time for feature extraction. 4113 defect samples of cold roll steel strips are used to develop KNN (k-Nearest Neighbor) classifier which classifies the defects into 8 different types. The developed KNN classifier demonstrates about 85% classifying performance which is considered very plausible result.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.301-306
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• 2003

Spot welding is frequently used for industrial purpose, such as automobile and aerospace industries and household appliances due to its high performance. In these day, robotization and systemization of welding process made it possible to produce more precise or smaller electric parts. And when it comes to welding of steel sheet, the size of nugget must be getting smaller. Therefore, welding conditions are limited to avoid defects, such as deformation, damage, weakening of joining area. In this research, the measurement of the nugget size by the nondestructive inspection has been conducted. As a result, the right estimation of the nugget size and void defects, the detection of corona bond near joining area, the selection of the optimum ultrasonic mode, and set up for ultrasonic inspection are studied. From the trustworthy solutions of nugget size estimated by results of measurement, the optimum inspection conditions depending upon the width of welding parts are determined as well.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.487-493
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• 2004

In this Paper, we propose a lighting system for the stable detection of check defects of the CRT panel through the analysis of the lighting interaction between the lighting unit and the CRT panel. The check defect is very difficult to detect reliably because of its high sensitivity according to the direction of incident light. At first, we model the physical shape of check defects using SEM image. And then we apply physics based illumination model to investigate the optical characteristics of the check defect. Finally, we propose a lighting system for the stable detection of check defect. Experimental results show the feasibility of the proposed lighting system for check inspection.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.2
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• pp.307-313
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• 2008

In this paper, we propose a novel defects inspection algorithm for TFT-LCD panels. We first compensate the distorted image caused by the camera distortion and the uneven illumination environment using the least squares method and the bezier surface. We find a starting point of each pattern for restricting each pattern. A clean image is compared to each pattern to find defects using modified PCSR-G algorithm. The simulation example shows that our algorithm not only inspects the defects well, but also is robust to the 1-pixel error.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.26 no.4
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• pp.263-279
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• 2022

This paper presents an automatic inspection of defects in semiconductor images. We devise a statistical method to find defects on homogeneous background from the observation that it has a log-normal distribution. If computer aided design (CAD) data is available, we use it to construct a signed distance function (SDF) and change the pixel values so that the average of pixel values along the level curve of the SDF is zero, so that the image has a homogeneous background. In the absence of CAD data, we devise a hybrid method consisting of a model-based algorithm and two neural networks. The model-based algorithm uses the first right singular vector to determine whether the image has a linear or complex structure. For an image with a linear structure, we remove the structure using the rank 1 approximation so that it has a homogeneous background. An image with a complex structure is inspected by two neural networks. We provide results of numerical experiments for the proposed methods.

• 한국정보디스플레이학회:학술대회논문집
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• 2002.08a
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• pp.118-121
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• 2002

In this study, we describe the development of viscous inspection equipment for flatron panel glass by Moire phenomenon and propose a new idea to develop an automatic inspection system for viscous or cord defects. It is possible to detect string viscous more easily and the equipment is practically being applied in production line. After using this equipment, the ratio of defective from customer is dropped significantly.