• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.130-133
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• 2005

This paper presents the efficient method to detect the defective detectors of the SWIR band of SPOT 4. The key of this method are to flatten the baseline of the data using high pass band filter instead of differentiation. This method is made up six steps. First step is to apply image enhancement techniques to enhance the lines imaged by defective detector and improve the quality of an image. Second step is processed by summing the enhanced image in line direction. These summed data have the peaks that represent the defective detectors and the curved baseline characterized by the reflectivity of Earth surface. In order to exactly detect these peaks, third step is to flatten the curved baseline using high pass filtering in the frequency domain. In fourth step, the data with flat baseline is normalized to have zero mean and unity standard deviation. In fifth step, the defective detectors are detected using $99.9\%$ confidence interval. Finally, after removing the detected ones in summed data, the steps from third to five are iterated. Three SPOT 4 images, which have different reflectivity of Earth surface and different sensor, were used to validate this method. The overall accuracy of detection for three images was $97.9\%$. This result shows that this method can detect efficiently the lines made by defective detectors.

• Journal of Biomedical Engineering Research
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• v.30 no.6
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• pp.476-481
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• 2009

The most troublesome artifacts in micro computed tomography (micro-CT) are ring artifacts. The ring artifacts are caused by non-uniform sensitivity and defective pixels of the x-ray detector. These ring artifacts seriously degrade the quality of CT images. In flat-panel detector based micro-CT systems, the ring artifacts are hardly removed by conventional correction methods of digital radiography, because very small difference of detector pixel signals may make severe ring artifacts. This paper presents a novel method to remove ring artifacts in flat-panel detector based micro-CT systems. First, the bad lines of a sinogram which are caused by defective pixels of the detector are identified, and then, they are corrected using a cubic spline interpolation technique. Finally, a ring artifacts free image is reconstructed from the corrected projections. We applied the method to various kinds of objects and found that the image qualities were much improved.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.5
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• pp.89-94
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• 2013

The fire testing performed for smoke detector model approval in Korea tests only one kind of fire smoke. A photoelectric spot-type smoke detector using Mie scattering is affected by the wavelength of light beam and the particle diameter. According to UL (Underwriters Laboratories Inc.) 268 standard, this paper analyze the characteristic of the response for a photoelectric spot-type smoke detector on sale in Korea using various fire smokes. Probability that the response time is included in non-defective range is 100% in paper fire, 90% in wood fire and 75% in flammable liquid fire, 90% in wood fire and 75% in flammable liquid fire. According to the estimation for population mean of the response time choosing a confidence level of 99%, a maximum of 19% for wood fire and that of 38% for flammable liquid fire are defective. As the result of analysis of smoke particle, this paper is found that these results are caused by the smoke particles are wide variations in size or have very black.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.506-507
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• 1992

When it comes to the 'Leak Detector System' generally, our country has a large income 'Rotary Type Leak Detector' of foreign goods. The completed development of the 'Line Type Leak-Detector' system was produced to check Whether the containers for small and large on the filling line are auto defective. This system is applied to the filling package Processing during the production and contributed to inproving competiveness of domestic containers manufactures of all society of Industry. Also, high precision and realiablity, very compact size, low cost and Easy set-up etc. by checking the experimental data directly plan, Design and making for '1 Compression Head Control Leak Detector System'. This flexcible system can be equipped with multiple Compression heads depending on the requested prodution test rate and test precision.

• Smart Media Journal
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• v.12 no.9
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• pp.45-59
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• 2023

Weakly supervised object localization (WSOL) is a task of localizing an object in an image using only image-level labels. Previous studies have followed the conventional class activation mapping (CAM) pipeline. However, we reveal the current CAM approach suffers from problems which cause original CAM could not capture the complete defects features. This work utilizes a convolutional neural network (CNN) pretrained on image-level labels to generate class activation maps in a multi-scale manner to highlight discriminative regions. Additionally, a vision transformer (ViT) pretrained was treated to produce multi-head attention maps as an auxiliary detector. By integrating the CNN-based CAMs and attention maps, our approach localizes defective regions without requiring bounding box or pixel-level supervision during training. We evaluate our approach on a dataset of apple images with only image-level labels of defect categories. Experiments demonstrate our proposed method aligns with several Object Detection models performance, hold a promise for improving localization.

• JSTS:Journal of Semiconductor Technology and Science
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• v.6 no.4
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• pp.299-312
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• 2006

This paper presents the results of a novel test structure for process control monitor for uncooled IR detector technology of microbolometer arrays. The proposed test structure is based on resistive network configuration. The theoretical model for resistance of this network has been developed using 'Compensation' and 'Superposition' network theorems. The theoretical results of proposed resistive network have been verified by wired hardware testing as well as using an actual 16x16 networked bolometer array. The proposed structure uses simple two-level metal process and is easy to integrate with standard CMOS process line. The proposed structure can imitate the performance of actual fabricated version of area array closely and it uses only 32 pins instead of 512 using conventional method for a $16{\times}16$ array. Further, it has been demonstrated that the defective or faulty elements can be identified vividly using extraction matrix, whose values are quite similar(within the error of 0.1%), which verifies the algorithm in small variation case(${\sim}1%$ variation). For example, an element, intentionally damaged electrically, has been shown to have the difference magnitude much higher than rest of the elements(1.45 a.u. as compared to ${\sim}$ 0.25 a.u. of others), confirming that it is defective. Further, for the devices having non-uniformity ${\leq}$ 10%, both the actual non-uniformity and faults are predicted well. Finally, using our analysis, we have been able to grade(pass or fail) 60 actual devices based on quantitative estimation of non-uniformity ranging from ＜ 5% to ＞ 20%. Additionally, we have been able to identify the number of bad elements ranging from 0 to ＞ 15 in above devices.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.3
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• pp.513-518
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• 2019

The non-destructive testing equipment using an eddy current was developed to check for defect in the vehicle transmission component. A defect master sample was made to test all types of defects that occur in the component and also an eddy current detector was manufactured and used to test and detect all kinds of defects. In addition, testing was held against the actual defective items to investigate the cause and type of defects, and a comparative study was conducted based on results from the examination. The software system of the eddy current detector was developed so that even a non-specialist can make assessment of detect in the component from the test results displayed on the monitor.

• Textile Coloration and Finishing
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• v.20 no.1
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• pp.48-56
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• 2008

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 are one of the frequently occurring defects. Two algorithms used were compared according to both their processing time and detection rate. First algorithm (algorithm A) was based on morphological image processing such as dilation and opening for effective treatment of defective printing areas while second one (algorithm B) mainly employs well-defined edge detection technique based on canny detector and Zermike moment. It was concluded' that although both algorithms were quite successful, algorithm B showed relatively consistent performance than algorithm A in detecting complex patterns.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 2008.04a
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• pp.217-222
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• 2008

In the last five years, 45 people died and 104 were wounded because of carbon monoxide poisoning accident. CO poisoning accident is higher than any other gas accident in the rate of deaths/incidents. Most of these CO poisoning accidents were caused by defective exhaust tube in the old gas boiler and multi-use facility. In this study, the spread of CO gas released from leakage hole of exhaust tube was analyzed by concentration measuring test. CO gas leaked form exhaust tube in a building was highest concentrated near the ceiling. Through these experiments, the reasonable installation location of CO alarm was made certain and suggested.

• KIEE International Transactions on Electrophysics and Applications
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• v.5C no.3
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• pp.138-142
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• 2005

In this paper, we compared recognition rates between NN(neural networks) and clustering method as a scheme of off-line PD(partial discharge) diagnosis which occurs at the stator coil of traction motor. To acquire PD data, three defective models are made. PD data for classification were acquired from PD detector. And then statistical distributions are calculated to classify model discharge sources. These statistical distributions were applied as input data of two classification tools, BP(Back propagation algorithm) and ANFIS(adaptive network based fuzzy inference system) pre-processed FCM(fuzzy c-means) clustering method. So, classification rate of BP were somewhat higher than ANFIS. But other items of ANFIS were better than BP; learning time, parameter number, simplicity of algorithm.