• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.334-343
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• 1996

Quality evaluation for food and agricultural products have always been one of the most elusive problems associated with the handling , processing and marketing in a food plant production. In order to detect physical foreign materials in food and agricultural products, non-destructive techniques have been developed for many years. Application of X-ray system to detect physical foreign materials in food and agricultural products could be considered to be a high potential method. Especially , it is impossible to detect internal physical foreign materials by visual inspections. In this study, it was tried to be applied for two different X-ray devices. Soft X-ray system with CdTe sensor and X-ray CT scanner were evaluated for advantage of the detection of non-meltallic foreign materials in food and agricultural products . Though the soft X-ray is not a high energy radiation, it is possible to detect small different density in a material. The CdTe sensor has a high resolution for t e soft X-ray energy region. The density characteristics of foods and foreign material were expressed region. The density characteristics of foods and foreign materials were expressed as a soft X-ray energy spectrum. The energy spectrum was analyzed by a personal computer with a multi-channel analyzer. X-ray CT scanner can provide visual image and analyze by three dimensional information inside food and agricultural products. The X-ray CT scanner using as a medical equipment was used to detect a foreign material. The density characteristics of food and foreign materials in food were tried to be detected by the threshold value on the basis of the CT numbers. The soft X-ray absorption characteristics for acrylin plates and distilled water were obtained and could be found the possibility of detecting a small physical foreign materials such as a plastic wrapping film , a stone and grasshopper in food and agricultural products.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.137-142
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• 2012

The temporal subtraction technique as one of computer aided diagnosis has been introduced in medical fields to enhance the interval changes such as formation of new lesions and changes in existing abnormalities on deference image. With the temporal subtraction technique radiologists can easily detect lung nodules on visual screening. Until now, two-dimensional temporal subtraction imaging technique has been introduced for the clinical test. We have developed new temporal subtraction method to remove the subtraction artifacts which is caused by mis-registration on temporal subtraction images of lungs on MDCT images. In this paper, we propose a new computer aided diagnosis scheme for automatic enhancing the lung nodules from the temporal subtraction of thoracic MDCT images. At first, the candidates regions included nodules are detected by the multiple threshold technique in terms of the pixel value on the temporal subtraction images. Then, a rule-base method and artificial neural networks is utilized to remove the false positives of nodule candidates which is obtained temporal subtraction images. We have applied our detection of lung nodules to 30 thoracic MDCT image sets including lung nodules. With the detection method, satisfactory experimental results are obtained. Some experimental results are shown with discussion.

• Journal of Korean Neurosurgical Society
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• v.29 no.3
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• pp.345-352
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• 2000

Objective : The purpose of this study was to compare computed tomographic angiography(CTA) with conventional cerebral angiography(CCA) and to assess usefulness of CTA in detection and anatomic definition of intracranial aneurysms of the circle of Willis in subarachnoid hemorrhage. Patients and Methods : Fifty consecutive patients with known or suspected intracranial saccular aneurysms underwent CTA with preoperative CCA from 1997 to 1999. Using surface shaded display post-processing technique, CTA was interpreted for the presence, location of aneurysms and anatomic features. The image obtained with CTA was then compared with CCA image. Results : In 47 patients, CCA revealed 57 cerebral aneurysms and CTA revealed 54 aneurysms. Two of the 57 cerebral aneurysms were located outside of the imaging volume of CTA and one case was misdiagnosed. The sensitivity of CTA was 94.7% and the specificity was 100%. The results obtained with CTA were, compared with the results obtained with CCA, equal in determining dome shape, direction and lobularity. However, CTA provided a 3-dimensional representation of aneurysmal lesion very useful for surgical planning. Moreover, CTA was useful for rapid and relatively noninvasive detection of aneurysms in the circle of Willis. Conclusion : CTA can be a diagnostic tool for the patients with acute subarachnoid hemorrhage due to a ruptured aneurysm of the circle of Willis and provides adequate anatomic detail for surgical planning, especially to complex cerebral aneurysms. However, we think CCA is necessary because of CTA limitations including its difficulty in detecting unusually located aneurysms(including those in cavernous sinus or distal artery) and combined vascular lesion (including arteriovenous malformation) and acquiring dynamic flow information.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.213-225
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• 2018

For constructing three-dimensional (3D) spatial information occlusion region problem arises in the process of taking the texture of the building. In order to solve this problem, it is necessary to investigate the automation method to automatically recognize the occlusion region, issue it, and automatically complement the texture. In fact there are occasions when it is possible to generate a very large number of structures and occlusion, so alternatives to overcome are being considered. In this study, we attempt to apply an approach to automatically create an occlusion region based on learning by patterning the blocked region using the recently emerging deep learning algorithm. Experiment to see the performance automatic detection of people, banners, vehicles, and traffic lights that cause occlusion in building walls using two advanced algorithms of Convolutional Neural Network (CNN) technique, Faster Region-based Convolutional Neural Network (R-CNN) and Mask R-CNN. And the results of the automatic detection by learning the banners in the pre-learned model of the Mask R-CNN method were found to be excellent.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.203-208
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• 2019

In this paper, we propose a real-time virtual model synchronization algorithm using object feature detection. The proposed algorithm may be useful to synchronize between real objects and their corresponding virtual models through object feature search in two-dimensional images. It consists of an algorithm to classify objects with colors individually, and an algorithm to analyze the orientation of objects with angles. We can synchronize the motion of the real object with the virtual model by providing the environment of moving the virtual object through the hand without specific controllers. The future research will include the algorithm to synchronize real object with unspecified shapes, colors, and directions to the corresponding virtual object.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4531-4544
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• 2021

Because the traditional network information security vulnerability risk assessment method does not set the weight, it is easy for security personnel to fail to evaluate the value of information security vulnerability risk according to the calculation value of network centrality, resulting in poor evaluation effect. Therefore, based on the network security data element feature system, this study designed a quantitative assessment method of network information security vulnerability detection risk under single transmission state. In the case of single transmission state, the multi-dimensional analysis of network information security vulnerability is carried out by using the analysis model. On this basis, the weight is set, and the intrinsic attribute value of information security vulnerability is quantified by using the qualitative method. In order to comprehensively evaluate information security vulnerability, the efficacy coefficient method is used to transform information security vulnerability associated risk, and the information security vulnerability risk value is obtained, so as to realize the quantitative evaluation of network information security vulnerability detection under single transmission state. The calculated values of network centrality of the traditional method and the proposed method are tested respectively, and the evaluation of the two methods is evaluated according to the calculated results. The experimental results show that the proposed method can be used to calculate the network centrality value in the complex information security vulnerability space network, and the output evaluation result has a high signal-to-noise ratio, and the evaluation effect is obviously better than the traditional method.

• Journal of Surface Science and Engineering
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• v.57 no.4
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• pp.265-273
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• 2024

An amperometric sensor for measuring indole-3-acetic acid (IAA) was studied based on a screen-printed carbon electrode (SPCE) coated with a reduced graphene oxide composite electrocatalyst. The PEI-GO dispersion is uniformly formed through a nucleophilic substitution reaction between the active amine group of Polyethyleneimine (PEI) and the epoxide group exposed on the surface of graphene oxide. And The 3-dimensional PEI-rGO AG (Polyethyleneimine-reduced graphene oxide aerogel) complex was easily prepared through simple heat treatment of the combined PEI-GO dispersion. The proposed composite catalyst electrode, PEI-rGO AG/SPCE, showed a two linear relationship in the low and high concentrations in IAA detection, and the linear equation was I_pa = 0.2883C + 0.0883 (R²=0.9230) at low concentration and Ipa = 0.00464C + 0.6623 (R²=0.9894) at high concentration was proposed, and the detection limit was calculated to be 203.5nM±33.2nM. These results showed the applicability of the PEI-rGO AG composite catalyst as an electrode material for electrocatalysts for the detection of IAA.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1140-1145
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• 2004

Laser-induced incandescence (LII) is introduced as a valuable tool for the characterization of nanoparticles in flame environments. This technique is based on the heating of the particles by a short laser pulse and the subsequent detection of the thermal radiation. It has been applied successfully for the investigation of soot in different fields of application. The evaluation of the temporal decay of the laser-induced incandescence (LII) signal from soot particles is introduced as a technique to obtain two-dimensional distributions of particle sizes and is applied to a laminar diffusion flame. This novel approach to soot sizing exhibits several theoretical and technical advantages compared with the established combination of elastic scattering and LII, especially as it yields absolute sizes of primary particles without requiring calibration. With this technique a spatially resolved 2-D measurement of soot primary particle sizes is feasible in a combination process form the ratio of emission signals obtained at two delay times after a laser pulse, as the cooling behavior is characteristic of particle size.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.1
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• pp.108-113
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• 2017

In this paper, we proposed a three-dimensional(3D) scanning system based on laser vision technique for 3D model reconstruction. The proposed scanning system consists of line laser, camera, and turntable. We implemented the 3D scanning system using low quality elements. Although these are low quality elements, we reduced the 3D data reconstruction errors greatly using two methods. First, we developed a maximum brightness detection algorithm. This algorithm extracts the maximum brightness of the line laser to obtain the shape of the object. Second, we designed a new laser control device. This device helps to adjust the relative position of the turntable and line laser. These two methods greatly reduce the measuring noise. As a result, point cloud data can be obtained without complicated calculations.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.260-262
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• 2003

New Image registration techniques are developed for determining geometric distortions between two images of the same scene. First, the properties of the Fourier transform of a two dimensional function under the affine transformation are given. As a result, techniques for the estimation of the coefficients of the distortion model using the spectral frequency information are developed. Image registration can be achieved by applying the fast Fourier transform (FFT) technique for cross correlation of misregistered imagery to determine spatial distances. The correlation results may be rather broad, making detection of the peak difficult, what can be suppressed by enhancing cross-correlation technique. Yield greatly improves the delectability and high precision of image misregistration.