• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3422-3427
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• 2010

In this paper, we presents a sensor calibration technique using stereo X-ray images to provide efficient inspection of fast moving cargo objects. Stereo X-ray scanned images are acquired from a specially designed equipment which consists of a X-ray source, dual-linear array detector, and a conveyor system. Dual detector is installed so that rectified stereo X-ray images of objects are acquired. Using the stereo X-ray images, we carry out a sensor calibration to find the correspondences between the images and reconstruct 3-D shapes of real objects. Using the Image acquired from the stereo detectors with varying distances, we calculated the GCP(ground control point)of the image. And we figure out the error by comparing calculated GCP and GCP of the real object. The experimental results show the proposed technique can enhance the accuracy of stereo matching and give more efficient visualization for cargo inspection image.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.10
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• pp.886-890
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• 2013

In this paper, a 3D coordinates acquisition method for a mechanical assembly is developed by using multiview X-ray images. The multi-view X-ray images of an object are obtained by a rotary table. From the rotation transformation, it is possible to obtain the 3D coordinates of corresponding edge points on multi-view X-ray images by triangulation. The edge detection algorithm in this paper is based on the attenuation characteristic of the X-ray. The 3D coordinates of the object points are represented on a graphic display, which is used for the inspection of a mechanical assembly.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.323-324
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• 2013

본 논문에서는 2차원 X-ray 영상을 이용하여 3차원 영상을 얻기 위한 전처리 과정으로 2차원 X-ray 영상에서 원하는 뼈 영상을 분할하기 위한 능동적 대퇴골 분할 기법에 대해 제안하고 구현하였다. X-ray 영상의 주된 화질 저하 요인인 잡음을 제거하고 에지 및 밝기 검출을 통하여 정확하고 빠른 뼈 영상 분할 기법을 구현하였고 대퇴골 영상을 통해 검증하였다. 이를 통해 최소한의 2차원 X-ray 영상을 이용하여 3차원 뼈 모델링을 구현하는데 필요한 뼈 영상을 획득하였다.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1059-1062
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• 1999

Recently, X-ray chest radiograph is showing a tendency to take an image of digital radiograph so as to diagnose the pathological pattern of chest in a usual. When the radiologist observes the chest image derived from digital radiograph system on the monitor. he feels difficult to find out because of the sensitivity of chest radiograph. It takes amount of time to adjust the proper image for diagnosis. Therefore, we provided the result and the method of the optimal image equalization for image enhancement.

• Journal of the Korean Society of Radiology
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• v.7 no.3
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• pp.165-173
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• 2013

The purpose of this study is to examine how much the movement at X-ray examinations like breathing or the positioning affects the image during chest or abdomen X-ray examination so as to create an image containing information as much as possible. The study method adopted is doing the X-ray in each of the states including breathing (inspiration & expiration) and movement in the standing chest PA X-ray and simple abdomen X-ray among the kinds of examination selected the most in hospitals and then evaluating them by applying the standards of image evaluation for each region. According to the study result, about the standing chest PA X-ray, the images taken at inspiration contain more information than those taken at expiration or having subtle movement during the examination. About the simple abdomen X-ray, the images taken at expiration contain more information than those taken at inspiration or movement. The above study results imply that regarding general X-ray examination, information we can find from the images may differ significantly according to the region examined, examination purpose, or movement during the examination like breathing.

• Journal of radiological science and technology
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• v.28 no.2
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• pp.111-115
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• 2005

The quality of image from the system that creates medical images by using X-ray depends on the various different reasons such as the X-ray generator, the subject and the image transmission medium. In other words, thereare various factors existing that can influence on the quality of image from the moment when the X-ray is generated and until the final image is created. Therefore, the operator who creates images at the clinical site should make continuous evaluation and observation from the final image. There are various methods of evaluating the medical images, but it is assumed that the MTF measurement method can be suitable for measuring actual or effective resolution. So in this study, the MTF measurement method by using X-ray film has been avoided and the MTF features according to the deterioration of the X-ray system have been measured by using the software (the program used Borland C++ builder software and LEAD tools software) that can measure the MTF of the digital medical images. As the result of this measurement, it has been found out through the MTF graph that the resolution and sharpness from the old x-ray generator with a many years of using and many numbers of times of using were deteriorated for the quality of image comparing to those from the new system. Also a simple and easy measurement method for the MTF from the digital medical images can be obtained in this study.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.997-999
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• 2012

Digital X-ray image detector is widely used for radiodiagnosis. Amorphous selenium has been received attention as one of the major material that confirmed photoconductor of direct methode detector. We analysis the photocurrent using 2-dimensional device simulator when blue-ray (${\lambda}=486nm$) is irradiated and high voltage is biased. We evaluate electron-hole generation rate, electron-hole recombination rate, and electron/hole distribution in the amorphous selenium. This simulation methode is helpful to the analysis of digital X-ray image detector. We expect that many applications will be developed in digital X-ray image detector using 2-dimensional device simulator.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.219-225
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• 2022

In this study, we propose training a support vector machine (SVM) model on top of deep networks for detecting Covid-19 from chest X-ray images. We started by gathering a real chest X-ray image dataset, including positive Covid-19, normal cases, and other lung diseases not caused by Covid-19. Instead of training deep networks from scratch, we fine-tuned recent pre-trained deep network models, such as DenseNet121, MobileNet v2, Inception v3, Xception, ResNet50, VGG16, and VGG19, to classify chest X-ray images into one of three classes (Covid-19, normal, and other lung). We propose training an SVM model on top of deep networks to perform a nonlinear combination of deep network outputs, improving classification over any single deep network. The empirical test results on the real chest X-ray image dataset show that deep network models, with an exception of ResNet50 with 82.44%, provide an accuracy of at least 92% on the test set. The proposed SVM on top of the deep network achieved the highest accuracy of 96.16%.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.108-117
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• 2015

If typical contrast enhancement algorithms for natural images are applied to X-ray images, they may cause artifacts such as overshooting or produce unnatural visual quality because they do not consider inherent characteristics of X-ray images. In order to overcome such problems, we propose a locally adaptive block-based contrast enhancement algorithm for X-ray images. After we derive a weighted cumulative distribution function for each block, we apply it to each block for contrast enhancement. Then, we obtain images that are removed from block effect by adopting block-based overlapping. In post-processing, we obtain the final image by emphasizing high frequency components. Experimental results show that the proposed block-based contrast enhancement algorithm provides at maximum 5-times higher visual quality than the exiting algorithm in terms of quantitative contrast metric.

• Journal of the Korean Geotechnical Society
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• v.27 no.11
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• pp.93-101
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• 2011

High quality X-ray computed microtomography (micro-CT) imaging of internal microstructures and pore space in geomaterials is often hampered by some inherent noises embedded in the images. In this paper, we introduce image calibration techniques for removing the most common noises in X-ray micro-CT, cupping (brightness difference between the periphery and central regions) and ring artifacts (consecutive concentric circles emanating from the origin). The artifacts removal sequentially applies coordinate transformation, normalization, and low-pass filtering in 2D Fourier spectrum to raw CT-images. The applicability and performance of the techniques are showcased by describing extraction of 3D pore structures from micro-CT images of porous basalt using artifacts reductions, binarization, and volume stacking. Comparisions between calibrated and raw images indicate that the artifacts removal allows us to avoid the overestimation of porosity of imaged materials, and proper calibration of the artifacts plays a crucial role in using X-ray CT for geomaterials.