• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.40-44
• /
• 2002

Precision correction is the process of geometrically aligning images to a reference coordinate system using GCPs(Ground Control Points). Many applications of remote sensing data, such as change detection, mapping and environmental monitoring, rely on the accuracy of precision correction. However it is a very time consuming and laborious process. It requires GCP collection, the identification of image points and their corresponding reference coordinates. At typical satellite ground stations, GCP collection requires most of man-powers in processing satellite images. A method of automatic registration of satellite images is demanding. In this paper, we propose a new algorithm for automatic precision correction by GCP chips and RANSAC(Random Sample Consensus). The algorithm is divided into two major steps. The first one is the automated generation of ground control points. An automated stereo matching based on normalized cross correlation will be used. We have improved the accuracy of stereo matching by determining the size and shape of match windows according to incidence angle and scene orientation from ancillary data. The second one is the robust estimation of mapping function from control points. We used the RANSAC algorithm for this step and effectively removed the outliers of matching results. We carried out experiments with SPOT images over three test sites which were taken at different time and look-angle with each other. Left image was used to select UP chipsets and right image to match against GCP chipsets and perform automatic registration. In result, we could show that our approach of automated matching and robust estimation worked well for automated registration.

• Journal of the Korean Society for Precision Engineering
• /
• v.5 no.1
• /
• pp.84-93
• /
• 1988

The on-line detection of the chip flow is one of the most important technologies in com- pletly automatic operation of machine tool, such as FMS and Unmanned Factories. This problem has been studied by many researchers, however, it is not solved as yet. For the recognition of chip flow in this study, the dynamic cutting force components due to the chip breaking were measured by dynamometer of piezo-electric type, and the frequency components of cutting force were also analyzed. From the measured results, the effect of cutting conditions and tool geometry on the dynamic cutting force component and chip formation were investigated in addition to the relationships between frequency of chip breaking (fB) and side serrated crack (fC) of chip. As a result, the following conclusions were obtaianed. 1) The chip formations have a large effect on the dynamic cutting force components. When chip breaking takes place, the dynamic cutting force component greatly increases, and the peridoic components appear, which correspond to maximum peak- frequency. 2) The crater wear of tool has a good effect on the chip control causing the chiup to be formed as upward-curl shape. In this case, the dymamic cutting force component greatly increases also 3) fB and fC of chip are closely corelated, and fC of chips has a large effect on the change of the situation of chip flow and dynamic cutting force component. 4) Under wide cutting conditions, the limit value (1.0 kgf) of dynamic cutting force component exists between the broken and continuous chips. Accordingly, this value is suitable for recognition of chip flow in on-line control of the cutting process.

• Journal of Korean Neurosurgical Society
• /
• v.37 no.5
• /
• pp.370-374
• /
• 2005

Objective: We investigated the morphologic changes within 24 hours after a single ${\gamma}$-irradiation in the rat brain. Methods: Forty Sprague-Dawley rats were used. After a burr hole trephination on right parietal area, cerebral hemisphere was irradiated with 2Gy and 5Gy using iridium-192($^{192}Ir$), respectively. The effect was assessed at 4, 8, 12 and 24 hours after irradiation. The histological changes were scored following the detection of edema or disarray severity. TUNEL-positive cells exhibiting apoptotic morphology were counted in irradiated region. Results: Cortical edema and disarray were initially showed at 4 or 8 hour and almost all defined at 24 hour after irradiation. And the injury was wedge shape. TUNEL-positive cells were minimal at 8 hour after irradiation as the number of positive cells were $2.6{\pm}5.27$(n=5) after 2Gy, and $0.8{\pm}0.84$(n=5) after 5Gy. But, the number of apoptotic cells were increased markedly to $60{\pm}6.24$ at 12 hour after 2Gy and to $104{\pm}19.7$ at 24 hour after 5Gy. Conclusion: There were prominent morphologic changes immediately after ${\gamma}$-irradiation. And, apoptosis was increased according to the time period. These findings implicate that brain irradiation induces rapid apoptotic change, which may play an important role in the pathogenesis of radiation-induced pathologic conditions.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.7 no.4
• /
• pp.81-87
• /
• 2003

In this paper, the feasibility of using Shannon's sampling theorem to reconstruct exact mode shapes of a structural system from a limited number of sensor points and localizing damage in that structure with reconstructed mode shapes is investigated. Shannon's sampling theorem for the time domain is reviewed. The theorem is then extended to the spatial domain. To verify the usefulness of extended theorem, mode shapes of a simple beam are reconstructed from a limited amount of data and the reconstructed mode shapes are compared to the exact mode shapes. On the basis of the results, a simple rule is proposed for the optimal placement of accelerometers in modal parameter extraction experiments. Practicality of the proposed rule and the extended Shannon's theorem is demonstrated by detecting damage in laboratory beam structure with two-span via applying to mode shapes of pre and post damage states.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.4
• /
• pp.516-521
• /
• 2010

In this paper, we propose a video-based intelligent unmanned fire surveillance system using fuzzy color models. In general, to detect heat or smoke, a separate device is required for a fire surveillance system, this system, however, can be implemented by using widely used CCTV, which does not need separate devices and extra cost. The systems called video-based fire surveillance systems use mainly a method extracting smoke or flame from an input image only. The smoke is difficult to extract at night because of its gray-scale color, and the flame color depends on the temperature, the inflammable, the size of flame, etc, which makes it hard to extract the flame region from the input image. This paper deals with a intelligent fire surveillance system which is robust against the variation of the flame color, especially at night. The proposed system extracts the moving object from the input image, makes a decision whether the object is the flame or not by means of the color obtained by fuzzy color model and the shape obtained by histogram, and issues a fire alarm when the flame is spread. Finally, we verify the efficiency of the proposed system through the experiment of the controlled real fire.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.8
• /
• pp.181-189
• /
• 2019

An aircraft power distribution device distributes and controls the power generated by the generator and provides overcurrent protection. There are many defect phenomena that make AC power distribution impossible during flight, which poses a problem in because some electronic equipment cannot be operated. We describe a process of deriving the root cause of defects by using vibration testing equipment to simulate the vibration conditions during aircraft flight, which result in defects. The results show that the cause of the defect is internal wiring damage caused by the vibration of the contactor of the AC power distribution device. Therefore, the shape of the contactor was improved to solve this problem. We also improved the test procedure by performing defect detection tests using vibration testing equipment to detect a faulty contactor. As a result of the improvements, a component certification test and flight test proved that the defect phenomena of the AC electrical master box were improved.

• Imaging Science in Dentistry
• /
• v.49 no.1
• /
• pp.59-63
• /
• 2019

Purpose: This study evaluated the prevalence and characteristics of maxillary antroliths using cone-beam computed tomography (CBCT) scans performed for maxillofacial diagnostic purposes. Materials and Methods: CBCT scans of 13,946 patients over the age of 20 were reviewed for maxillary antroliths, and prevalence according to sex, age, and the side of the jaw was calculated. The relationships of single or multiple antroliths with sex, side, and the degree of sinus inflammation were evaluated. The shape and dimension of antroliths were also assessed. The data were analyzed using descriptive statistics, the chi-square or Fisher exact tests, and Kendall's tau-b. Results: A total of 138 (0.99%) of the 13,946 patients showed an antrolith in at least 1 sinus. Only 18 patients presented a bilateral manifestation, which brought the total number of sinuses containing an antrolith to 156 (0.56%). Multiple antroliths were observed in 36 sinuses, and the total number of antroliths was 207: 110 punctate, 65 linear, and 32 amorphous. The antrolith dimensions varied from $1mm^2$ to $91mm^2$ (average, $10.2{\pm}15.5mm^2$). No statistically significant differences were found according to sex, side, and age group (P>0.05). However, there was a statistically significant difference between the multiplicity of antrolith and the degree of sinus inflammation (P<0.05). Conclusion: Cone-beam computed tomography is an effective modality for the detection of incidental antroliths. Maxillary antroliths were found to be very rare and were usually asymptomatic. Dentists should have a comprehensive understanding of their diagnosis and treatment in light of possible associated dental problems.

• Journal of Urban Science
• /
• v.7 no.2
• /
• pp.53-60
• /
• 2018

Digital Twin is a technology that creates a photocopy of real-world objects on a computer and analyzes the past and present operational status by fusing the structure, context, and operation of various physical systems with property information, and predicts the future society's countermeasures. In particular, 3D rendering technology (UAS, LiDAR, GNSS, etc.) is a core technology in digital twin. so, the research and application are actively performed in the industry in recent years. However, UAS (Unmanned Aerial System) and LiDAR (Light Detection And Ranging) have to be solved by compensating blind spot which is not reconstructed according to the object shape. In addition, the terrestrial LiDAR can acquire the point cloud of the object more precisely and quickly at a short distance, but a blind spot is generated at the upper part of the object, thereby imposing restrictions on the forward digital twin modeling. The UAS is capable of modeling a specific range of objects with high accuracy by using high resolution images at low altitudes, and has the advantage of generating a high density point group based on SfM (Structure-from-Motion) image analysis technology. However, It is relatively far from the target LiDAR than the terrestrial LiDAR, and it takes time to analyze the image. In particular, it is necessary to reduce the accuracy of the side part and compensate the blind spot. By re-optimizing it after fusion with UAS and Terrestrial LiDAR, the residual error of each modeling method was compensated and the mutual correction result was obtained. The accuracy of fusion-based 3D model is less than 1cm and it is expected to be useful for digital twin construction.

• Journal of the Korean Society of Radiology
• /
• v.17 no.1
• /
• pp.17-23
• /
• 2023

In this study, the thermoluminescence kinetics of electron trap in Li₆Y_0.5Gd_0.5(BO₃)₃ (LY_0.5G_0.5BO) scintillator for neutron detection composed of Li, Gd, and B with a high neutron response cross-section were investigated. The thermoluminescence glow curve of the LY_0.5G_0.5BO scintillation single crystal was measured and analyzed using the peak shape method, the initial rise method, and the machine learning algorithm to evaluate the physical parameters of the electron trap. The glow curve of the LY_0.5G_0.5BO scintillation single crystal consisted of a single peak. As a result of analyzing this peak, the activation energy, emission order, and frequency factor of the electron trap were 0.61 eV, 1.1, and 1.7×10⁷ s^-1, respectively. In addition, the possibility of thermoluminescence analysis of scintillators using machine learning was confirmed.

• Journal of Internet of Things and Convergence
• /
• v.8 no.1
• /
• pp.59-64
• /
• 2022

Existing edge discovery techniques only found edges of defined shapes based on precise definitions of edges. Therefore, there are many limitations in finding edges for images of complex and diverse shapes that exist in the real world. A method for solving these problems and discovering various types of edges is a cost minimization method. In this method, the cost function and cost factor are defined and used. This cost function calculates the cost of the candidate edge model generated according to the candidate edge generation strategy. If a satisfactory result is obtained, the corresponding candidate edge model becomes the edge for the image. In this study, a new candidate edge generation strategy was proposed to discover edges for images of more diverse shapes in order to improve the disadvantage of only finding edges of a defined shape, which is a problem of the cost minimization method. In addition, the contents of improvement were confirmed through a simple simulation that reflected these points.