• Journal of Digital Convergence
• /
• v.13 no.2
• /
• pp.159-175
• /
• 2015

The two-dimensional QR code has advantages such as directional nature, enough data storage capacity, ability of error correction, and ability of data restoration. There are two major issues like speed and correctiveness of recognition in the two-dimensional QR code. Therefore, this paper proposes a morphology-based algorithm of detecting the interest region of a barcode. Our research contents can be summarized as follows. First, the interest region of a barcode image was detected by close operations in morphology. Second, after that, the boundary of the barcode are detected by intersecting four cross line outside in a code. Three, the projected image is then rectified into a two-dimensional barcode in a square shape by the reverse-perspective transform. In result, it shows that our detection and recognition rates for the barcode image is also 97.20% and 94.80%, respectively and that outperforms than previous methods in various illumination and distorted image environments.

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.2
• /
• pp.85-92
• /
• 2023

Respiratory infections such as COVID-19 mainly occur within enclosed spaces. The presence or absence of abnormal symptoms of respiratory infectious diseases is judged through initial symptoms such as fever, cough, sneezing and difficulty breathing, and constant monitoring of these early symptoms is required. In this paper, image matching correction was performed for the RGB camera module and the thermal imaging camera module, and the temperature of the thermal imaging camera module for the measurement environment was calibrated using a blackbody. To detection the target recommended by the standard, a deep learning-based object recognition algorithm and the inner canthus recognition model were developed, and the model accuracy was derived by applying a dataset of 100 experimenters. Also, the error according to the measured distance was corrected through the object distance measurement using the Lidar module and the linear regression correction module. To measure the performance of the proposed model, an experimental environment consisting of a motor stage, an infrared thermography temperature screening system and a blackbody was established, and the error accuracy within 0.28℃ was shown as a result of temperature measurement according to a variable distance between 1m and 3.5 m.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.28 no.2
• /
• pp.247-254
• /
• 2010

In this paper, a new approach has been studied correcting the geometric distortion of SPOT 4 imagery. Two new equations were induced by the relationship between satellite and the Earth in the space. line-of-sight (LOS) vector adjustment model for SPOT 4 imagery was implemented in this study. This model is to adjust LOS vector under the assumption that the orbital information of satellite provided by receiving station is uncertain and this uncertainty makes a constant error over the image. This model is verified using SPOT 4 satellite image with high look angle and thirty five ground points, which include 10 GCPs(Ground Control Points) and 25 check points, measured by the GPS. In total thirty five points, the geometry of satellite image calculated by given satellite information(such as satellite position, velocity, attitude and look angles, etc) from SPOT 4 satellite image was distorted with a constant error. Through out the study, it was confirmed that the LOS vector adjustment model was able to be applied to SPOT4 satellite image. Using this model, RMSEs (Root Mean Square Errors) of twenty five check points taken by increasing the number of GCPs from two to ten were less than one pixel. As a result, LOS vector adjustment model could efficiently correct the geometry of SPOT4 images with only two GCPs. This method also is expected to get good results for the different satellite images that are similar to the geometry of SPOT images.

• Journal of the Korean Society of Radiology
• /
• v.18 no.1
• /
• pp.45-52
• /
• 2024

In this study, an AI-based algorithm was developed to prevent image quality deterioration and reading errors due to patient movement in PET/CT examinations that use radioisotopes in medical institutions to test cancer and other diseases. Using the Mothion Free software developed using, we checked the degree of correction of movement due to breathing, evaluated its usefulness, and conducted a study for clinical application. The experimental method was to use an RPM Phantom to inject the radioisotope 18F-FDG into a vacuum vial and a sphere of a NEMA IEC body Phantom of different sizes, and to produce images by directing the movement of the radioisotope into a moving lesion during respiration. The vacuum vial had different degrees of movement at different positions, and the spheres of the NEMA IEC body Phantom of different sizes produced different sizes of lesions. Through the acquired images, the lesion volume, maximum SUV, and average SUV were each measured to quantitatively evaluate the degree of motion correction by Motion Free. The average SUV of vacuum vial A, with a large degree of movement, was reduced by 23.36 %, and the error rate of vacuum vial B, with a small degree of movement, was reduced by 29.3 %. The average SUV error rate at the sphere 37mm and 22mm of the NEMA IEC body Phantom was reduced by 29.3 % and 26.51 %, respectively. The average error rate of the four measurements from which the error rate was calculated decreased by 30.03 %, indicating a more accurate average SUV value. In this study, only two-dimensional movements could be produced, so in order to obtain more accurate data, a Phantom that can embody the actual breathing movement of the human body was used, and if the diversity of the range of movement was configured, a more accurate evaluation of usability could be made.

• Progress in Medical Physics
• /
• v.25 no.1
• /
• pp.37-45
• /
• 2014

The accuracy and uniformity of CT numbers are the main causes of radiation dose calculation error. Especially, for the dose calculation based on kV-Cone Beam Computed Tomography (CBCT) image, the scatter affecting the CT number is known to be quite different by the object sizes, densities, exposure conditions, and so on. In this study, the scatter impact on the CBCT based dose calculation was evaluated to provide the optimal condition minimizing the error. The CBCT images was acquired under three scatter conditions ("Under-scatter", "Over-scatter", and "Full-scatter") by adjusting amount of scatter materials around a electron density phantom (CIRS062, Tissue Simulation Technology, Norfolk, VA, USA). The CT number uniformities of CBCT images for water-equivalent materials of the phantom were assessed, and the location dependency, either "inner" or "outer" parts of the phantom, was also evaluated. The electron density correction curves were derived from CBCT images of the electron density phantom in each scatter condition. The electron density correction curves were applied to calculate the CBCT based doses, which were compared with the dose based on Fan Beam Computed Tomography (FBCT). Also, 5 prostate IMRT cases were enrolled to assess the accuracy of dose based on CBCT images using gamma index analysis and relative dose differences. As the CT number histogram of phantom CBCT images for water equivalent materials was fitted with a gaussian function, the FHWM (146 HU) for "Full-scatter" condition was the smallest among the FHWM for the three conditions (685 HU for "under scatter" and 264 HU for "over scatter"). Also, the variance of CT numbers was the smallest for the same ingredients located in the center and periphery of the phantom in the "Full-scatter" condition. The dose distributions calculated with FBCT and CBCT images compared in a gamma index evaluation of 1%/3 mm criteria and in the dose difference. With the electron density correction acquired in the same scatter condition, the CBCT based dose calculations tended to be the most accurate. In 5 prostate cases in which the mean equivalent diameter was 27.2 cm, the averaged gamma pass rate was 98% and the dose difference confirmed to be less than 2% (average 0.2%, ranged from -1.3% to 1.6%) with the electron density correction of the "Full-scatter" condition. The accuracy of CBCT based dose calculation could be confirmed that closely related to the CT number uniformity and to the similarity of the scatter conditions for the electron density correction curve and CBCT image. In pelvic cases, the most accurate dose calculation was achievable in the application of the electron density curves of the "Full-scatter" condition.

• Korean Journal of Remote Sensing
• /
• v.40 no.4
• /
• pp.387-396
• /
• 2024

Most very high-resolution (VHR) satellite images provide rational polynomial coefficients (RPC) data to facilitate the transformation between ground coordinates and image coordinates. However, initial RPC often contains geometric errors, necessitating correction through matching with ground control points (GCPs). A GCP chip is a small image patch extracted from an orthorectified image together with height information of the center point, which can be directly used for geometric correction. Many studies have focused on area-based matching methods to accurately align GCP chips with VHR satellite images. In cases with seasonal differences or changed areas, edge-based algorithms are often used for matching due to the difficulty of relying solely on pixel values. However, traditional edge extraction algorithms,such as canny edge detectors, require appropriate threshold settings tailored to the spectral characteristics of satellite images. Therefore, this study utilizes deep learning-based edge information that is insensitive to the regional characteristics of satellite images for matching. Specifically,we use a pretrained pixel difference network (PiDiNet) to generate the edge maps for both satellite images and GCP chips. These edge maps are then used as input for normalized cross-correlation (NCC) and relative edge cross-correlation (RECC) to identify the peak points with the highest correlation between the two edge maps. To remove mismatched pairs and thus obtain the bias-compensated RPC, we iteratively apply the data snooping. Finally, we compare the results qualitatively and quantitatively with those obtained from traditional NCC and RECC methods. The PiDiNet network approach achieved high matching accuracy with root mean square error (RMSE) values ranging from 0.3 to 0.9 pixels. However, the PiDiNet-generated edges were thicker compared to those from the canny method, leading to slightly lower registration accuracy in some images. Nevertheless, PiDiNet consistently produced characteristic edge information, allowing for successful matching even in challenging regions. This study demonstrates that improving the robustness of edge-based registration methods can facilitate effective registration across diverse regions.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.1
• /
• pp.142-152
• /
• 2016

GPS is not able to be used for indoor positioning and currently most of techniques emerging to overcome the limit of GPS utilize private wireless networks. However, these methods require high costs for installation and maintenance, and they are inappropriate to be used in the place where precise positioning is needed as in indoor parking lots. This paper proposes a vehicular indoor positioning method based on QR-code recognition. The method gets an absolute coordinate through QR-code scanning, and obtain the location (an relative coordinate) of a black-box camera using the tilt and roll angle correction through affine transformation, scale transformation, and trigonometric function. Using these information of an absolute coordinate and an relative one, the precise position of a car is estimated. As a result, average error of 13.79cm is achieved and it corresponds to just 27.6% error rate in contrast to 50cm error of the recent technique based on wireless networks.

• Journal of Digital Convergence
• /
• v.13 no.1
• /
• pp.331-339
• /
• 2015

The purpose of this study is to evaluate utility of rotating adjustment using Xsight spine tracking system in 3D DOF location adjusting method, to minimize error between 6D DOF and 3D DOF in fiducial tracking system. In this study, the result of 6D DOF target location error is $0.124{\pm}0.058mm$, using fiducial inside tumor 3D DOF $0.673{\pm}0.142mm$, outside tumor $1.126{\pm}0.253mm$, apply with Xsight spine tracking system 3D DOF $0.542{\pm}0.103mm$. As the experiment shows, it was demonstrated that rotating adjustment through Xsight spine tracking system is valuable in case of treatment in 3D DOF location error that makes increasing accuracy and dose distribution each approximately 48% and 3%. In accordance with result of this study is useful rotation.

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

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.30 no.1
• /
• pp.97-107
• /
• 2024

Despite the rapid advancement in image recognition technology, achieving perfect digitization of tabular documents and handwritten documents still challenges. The purpose of this study is to improve the accuracy of digitizing the logbook by correcting errors by utilizing associated rules considered during logbook entries. Through this, it is expected to enhance the accuracy and reliability of data extracted from logbook through OCR programs. This model is to improve the accuracy of digitizing the logbook of the training ship "Saenuri" at the Mokpo Maritime University by correcting errors identified after Optical Character Recognition (OCR) program recognition. The model identified and corrected errors by utilizing associated rules considered during logbook entries. To evaluate the effect of model, the data before and after correction were divided by features, and comparisons were made between the same sailing number and the same feature. Using this model, approximately 10.6% of errors out of the total estimated error rate of about 11.8% were identified, and 56 out of 123 errors were corrected. A limitation of this study is that it only focuses on information from Dist.Run to Stand Course sections of the logbook, which contain navigational information. Future research will aim to correct more information from the logbook, including weather information, to overcome this limitation.