• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.744-749
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• 2012

In this paper, we suggest that how to improve an accuracy of mobile robot's localization by using the sensor network information which fuses the machine vision camera, encoder and IMU sensor. The heading value of IMU sensor is measured using terrestrial magnetism sensor which is based on magnetic field. However, this sensor is constantly affected by its surrounding environment. So, we isolated template of ceiling using vision camera to increase the sensor's accuracy when we use IMU sensor; we measured the angles by pattern matching algorithm; and to calibrate IMU sensor, we compared the obtained values with IMU sensor values and the offset value. The values that were used to obtain information on the robot's position which were of Encoder, IMU sensor, angle sensor of vision camera are transferred to the Host PC by wireless network. Then, the Host PC estimates the location of robot using all these values. As a result, we were able to get more accurate information on estimated positions than when using IMU sensor calibration solely.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.2
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• pp.98-103
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• 2010

In this paper, imaging processing study obtained from CCD image and thermography image was performed in order to treat easily thermographic data without any risks of personnels who conduct the condition monitoring for the abnormal or failure status occurrable in industrial power plants. This imaging processing is also applicable to the predictive maintenance. For confirming the broad monitoring, a methodology producting single image from the panorama technique was developed no matter how many cameras are employed, including fusion method for discrete configuration for the target. As results, image fusion from quick realtime processing was obtained and it was possible to save time to track the location monitoring in matching the images between CCTV and thermography.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.27-38
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• 2019

Sensors collect information for Internet of Things (IoT)-based services. However, indoor construction sites have a poor communication environment and many interfering elements that make it difficult to collect sensor information. In this study, a network was constructed between a Bluetooth Low Energy (BLE)-based IoT device based on a serverless IoT framework and a router. This experimental environment was applied to large- and small-scale indoor construction sites. Experiments were performed to test the communication performance of BLE-based IoT devices and routers at indoor construction sites. An analysis of the received signal strength indication (RSSI) graph patterns collected from the communication between the BLE-based IoT devices and routers for different testbed site situation revealed areas with good communication performance and poor communication performance due to interfering factors. The results confirmed that structural components of the building as well as the materials, equipment, and temporary facilities used in indoor construction interfere with the communication performance. Construction project managers will require improved technical knowledge of IoT, such as optimizing the router placement and matching communication between the router and workers, to improve the communication performance for large-scale indoor construction.

• Journal of Computing Science and Engineering
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• v.4 no.4
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• pp.368-387
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• 2010

We propose a novel method for the registration of 3D CT scans to 2D endoscopic images during the image-guided medialization laryngoplasty. This study aims to allow the surgeon to find the precise configuration of the implant and place it into the desired location by employing accurate registration methods of the 3D CT data to intra-operative patient and interactive visualization tools for the registered images. In this study, the proposed registration methods enable the surgeon to compare the outcome of the procedure to the pre-planned shape by matching the vocal folds in the CT rendered images to the endoscopic images. The 3D image fusion provides an interactive and intuitive guidance for surgeon by visualizing a combined and correlated relationship of the multiple imaging modalities. The 3D Magic Lens helps to effectively visualize laryngeal anatomical structures by applying different transparencies and transfer functions to the region of interest. The preliminary results of the study demonstrated that the proposed method can be readily extended for image-guided surgery of real patients.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.2
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• pp.37-46
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• 2016

The difference between definition time of GPS (Global Positioning System) position data and actual display time of car positions on a map could reduce the accuracy of car positions displayed in PND (Portable Navigation Device)-type CNS (Car Navigation System). Due to the time difference, the position of the car displayed on the map is not its current position, so an improved method to fix these problems is required. It is expected that a method that uses predicted future positionsto compensate for the delay caused by processing and display of the received GPS signals could mitigate these problems. Therefore, in this study an analysis was conducted to correct late processing problems of map positions by mapmatching using a Kalman filter with only GPS position data and a RRF (Road Reduction Filter) technique in a light-weight CNS. The effects on routing services are examined by analyzing differences that are decomposed into along and across the road elements relative to the direction of advancing car. The results indicate that it is possible to improve the positional accuracy in the along-the-road direction of a light-weight CNS device that uses only GPS position data, by applying a Kalman filter and RRF.

• Proceedings of the KSMRM Conference
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• 2002.11a
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• pp.106-106
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• 2002

Purpose： The purposes of our study are (1) to develop a brain phantom which can be used for multimodal image registration, (2) to evaluate the accuracy of image registration with the home-made phantom. Method： A brain phantom which could be used for image registration technique of CT-MR and CT-SPECT images using chamfer matching was developed. The brain phantom was specially designed to obtain imaging dataset of CT, MR, and SPECT. The phantom had an external frame with 4 N-shaped pipes filled with acryl rods for CT, MR imaging and Pb rods for SPECT imaging. 8 acrylic pipes were inserted into the empty space of the brain phantom to be imaged for geometric evaluation of the matching. Accuracy of image fusion was assessed by the comparison between the center points of the section of N-shaped bars in the external frame and the inserted pipes of the phantom. Technique with partially transparent, mixed images using color on gray was used for visual assessment of the image registration process.

• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.229-242
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• 2005

Photogrammetry is a current method of GIS data acquisition. However, as a matter of fact, a large manpower and expenditure for making detailed 3D spatial information is required especially in urban areas where various buildings exist. There are no photogrammetric systems which can automate a process of spatial information acquisition completely. On the other hand, LiDAR has high potential of automating 3D spatial data acquisition because it can directly measure 3D coordinates of objects, but it is rather difficult to recognize the object with only LiDAR data, for its low resolution at this moment. With this background, we believe that it is very advantageous to integrate LiDAR data and stereo CCD images for more efficient and automated acquisition of the 3D spatial data with higher resolution. In this research, the automatic urban object recognition methodology was proposed by integrating ultra highresolution stereo images and LiDAR data. Moreover, a method to enable more reliable and detailed stereo matching method for CCD images was examined by using LiDAR data as an initial 3D data to determine the search range and to detect possibility of occlusions. Finally, intellectual DSMs, which were identified urban features with high resolution, were generated with high speed processing.

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.73-83
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• 2020

Purpose: The purpose of this study is to confirm the matching of the electron density between tissue and gas due to variation of abdominal gas volume in MRgART (Magnetic Resonance-guided Adaptive Radiation Therapy) for pancreatic cancer patients, and to confirm the effect on the dose change and treatment time. Materials and Methods: We compared the PTV and OAR doses of the initial plan and the AGC(Abdominal gas correction) plans to one pancreatic cancer patient who treated with MRgART using the ViewRay MRIdian System (Viewray, USA) at this clinic. In the 4fx AGC plans, Beam ON(%) according to the patient's motion error was checked to confirm the effect of abdominal gas volume on treatment time. Results: Comparing the Initial plan with the average value of AGC plan, the dose difference was -7 to 0.1% in OAR and decreased by 0.16% on average, and in PTV, the dose decreased by 4.5% to 5.5% and decreased by 5.1% on average. In Adaptive treatment, as the abdominal gas volume increased, the Beam ON(%) decreased. Conclusion: Abdominal gas volume variation causes dose change due to inaccurate electron density matching between tissue and gas. In addition, if the abdominal gas volume increases, the Beam ON(%) decreases, and the treatment time may increase due to the motion error of the patient. Therefore, in MRgART, it is necessary to check the electron density matching and minimize the variability of the abdominal gas.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.78-82
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• 2010

Purpose: Recently, South Korea has seen a rapidly increased incidence of both breast and thyroid cancers. As a result, the I-131 scan and lymphoscintigraphy have been performed more frequently. Although this type of diagnostic imaging is prominent in that visualizes pathological conditions, which is similar to previous nuclear diagnostic imaging techniques, there is not much anatomical information obtained. Accordingly, it has been used in different ways to help find anatomical locations by transmission scan, however the results were unsatisfactory. Therefore, this study aims to realize an imaging technique which shows more anatomical information through the fusion of gamma and realistic imaging. Materials and Methods: We analyzed the data from patients who were examined by the lymphoscintigraphy and I-131 additional scan by Symbia Gamma camera (SIEMENS) in the nuclear medicine department of the National Cancer Center from April to July of 2009. First, we scanned the same location in patients by using a miniature camera (R-2000) in hyVISION. Afterwards, we scanned by gamma camera. The data we obtained was evaluated based on the scanning that measures an agreement of gamma and realistic imaging by the Gamma Ray Tool fusion program. Results: The amount of radiation technicians and patients were exposed was generated during the production process of flood source and applied transmission scan. During this time, the radiation exposure dose of technicians was an average of 14.1743 ${\mu}Sv$, while the radiation exposure dose of patients averaged 0.9037 ${\mu}Sv$. We also confirmed this to matching gamma and realistic markers in fusion imaging. Conclusion: Therefore, we found that we could provide imaging with more anatomical information to clinical doctors by fusion of system of gamma and realistic imaging. This has allowed us to perform an easier method in which to reduce the work process. In addition, we found that the radiation exposure can be reduced from the flood source. Eventually, we hope that this will be applicable in other nuclear medicine studies. Therefore, in order to respect the privacy of patients, this procedure will be performed only after the patient has agreed to the procedure after being given a detailed explanation about the process itself and its advantages.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.437-443
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• 2015

This paper presents face recognition based on the fusion of visible image and thermal infrared (IR) texture estimated from the face image in the visible spectrum. The proposed face recognition scheme uses a multi- layer neural network to estimate thermal texture from visible imagery. In the training process, a set of visible and thermal IR image pairs are used to determine the parameters of the neural network to learn a complex mapping from a visible image to its thermal texture in the low-dimensional feature space. The trained neural network estimates the principal components of the thermal texture corresponding to the input visible image. Extensive experiments on face recognition were performed using two popular face recognition algorithms, Eigenfaces and Fisherfaces for NIST/Equinox database for benchmarking. The fusion of visible image and thermal IR texture demonstrated improved face recognition accuracies over conventional face recognition in terms of receiver operating characteristics (ROC) as well as first matching performances.