• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.6
• /
• pp.525-534
• /
• 2018

Camera calibration is the process of determining the parameters such as the focal length of a camera, the position of a principal point, and lens distortions. For this purpose, images of checkerboard have been mainly used. When targets were automatically recognized in checkerboard image, the existing studies had limitations in that the user should have a good understanding of the input parameters for recognizing the target or that all checkerboard should appear in the image. In this study, a methodology for automatic target recognition was proposed. In this method, even if only a part of the checkerboard image was captured using rectangles including eight blobs, four each at the central portion and the outer portion of the checkerboard, the index of the target can be automatically assigned. In addition, there is no need for input parameters. In this study, three conditions were used to automatically extract the center point of the checkerboard target: the distortion of black and white pattern, the frequency of edge change, and the ratio of black and white pixels. Also, the direction and numbering of the checkerboard targets were made with blobs. Through experiments on two types of checkerboards, it was possible to automatically recognize checkerboard targets within a minute for 36 images.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.32 no.4
• /
• pp.265-272
• /
• 2019

In this paper, a vision-based deep learning algorithm and image processing method are proposed to detect bolt-loosening in steel connections. To achieve this objective, the following approaches are implemented. First, a bolt-loosening detection method that includes regional convolutional neural network(RCNN)-based deep learning algorithm and Hough line transform(HLT)-based image processing algorithm are designed. The RCNN-based deep learning algorithm is developed to identify and crop bolts in a connection image. The HLT-based image processing algorithm is designed to estimate the bolt angles from the cropped bolt images. Then, the proposed vision-based method is evaluated for verifying bolt-loosening detection in a lab-scale girder connection. The accuracy of the RCNN-based bolt detector and HLT-based bolt angle estimator are examined with respect to various perspective distortions.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.4
• /
• pp.7-12
• /
• 2019

Ambient backscatter communication is limited to channel estimation technique through a pilot signal, which is a channel estimation method in current RF communication, due to transmission power efficiency. In a limited transmission power environment, the research of traditional ambient backscatter communication has been studied assuming that it is an ideal channel without signal distortions due to channel conditions. In this paper, we propose an expectation-maximization(EM) algorithm, one of the blind channel estimation techniques, as a channel estimation method in ambient backscatter communication system which is the state of channel following normal distribution. In the proposed system model, the simulations confirm that channel estimate through EM algorithm is approaching the lower bound of the mean square error compared with the Bayesian Cramer-Rao Boundary(BCRB) to check performance. It shows that the channel parameter can be estimated in the ambient backscatter communication system.

• Imaging Science in Dentistry
• /
• v.49 no.2
• /
• pp.159-169
• /
• 2019

Purpose: Cone-beam computed tomography (CBCT) is widely used for 3-dimensional assessments of cranio-maxillo-facial relationships, especially in patients undergoing orthognathic surgery. We have introduced, for reference in CBCT cephalometry, an anatomical mid-sagittal plane (MSP) identified by the nasion, the midpoint between the posterior clinoid processes of the sella turcica, and the basion. The MSP is an updated version of the median plane previously used at our institution for 2D posterior-anterior cephalometry. This study was conducted to test the accuracy of the CBCT measures compared to those obtained using standard posterior-anterior cephalometry. Materials and Methods: Two operators measured the inter-zygomatic distance on 15 CBCT scans using the MSP as a reference plane, and the CBCT measurements were compared with measurements made on patients' posterior-anterior cephalograms. The statistical analysis evaluated the absolute and percentage differences between the 3D and 2D measurements. Results: As demonstrated by the absolute mean difference (roughly 1 mm) and the percentage difference (less than 3%), the MSP showed good accuracy on CBCT compared to the 2D plane, especially for measurements of the left side. However, the CBCT measurements showed a high standard deviation, indicating major variability and low precision. Conclusion: The anatomical MSP can be used as a reliable reference plane for transverse measurements in 3D cephalometry in cases of symmetrical or asymmetrical malocclusion. In patients who suffer from distortions of the skull base, the identification of landmarks might be difficult and the MSP could be unreliable. Becoming familiar with the relevant software could reduce errors and improve reliability.

• The Journal of Advanced Prosthodontics
• /
• v.13 no.2
• /
• pp.107-116
• /
• 2021

PURPOSE. Several studies focused on the accuracy of intra-oral scanners in implant dentistry, but the data of inter-implant distances were not widely mentioned. Therefore, this study aimed to evaluate the effect of distance between two implants on the surface distortion of scanned models generated by intra-oral scanners. MATERIALS AND METHODS. Three models with the distances between two fixed scan bodies of 7, 14, and 21 mm were fabricated and scanned with a highly precise D900L dental laboratory scanner as reference models. Fifteen scans were performed with TRIOS3 and CEREC Omnicam intra-oral scanners. Trueness, precision, and angle deviation of the test models were analyzed (α=.05). RESULTS. There was a significant difference among inter-implant distances in both intraoral scanners (P<.001). The error of trueness and precision increased with the increasing inter-implant length, while the angle deviation did not show the same trend. A significant difference in the angle deviation was found among the inter-implant distance. The greatest angle deviation was reported in the 14-mm group of both scanners (P<.05). In contrast, the lowest angle deviation in the 21-mm group of the TR scanner and the 7-mm of the CR scanner was reported (P<.001). CONCLUSION. The inter-implant distance affected the accuracy of intra-oral scanner. The error of trueness and precision increased along with the increasing distance between two implants. However, the distortions were not clinically significant. Regarding angle deviation, the clinically significant angle deviation may be possible when using intra-oral scanners in the partially edentulous arch.

• Current Optics and Photonics
• /
• v.6 no.6
• /
• pp.550-564
• /
• 2022

Optical microscopy is a useful tool for study in the biological sciences. With an optical microscope, we can observe the micro world of life such as tissues, cells, and proteins. A fluorescent dye or a fluorescent protein provides an opportunity to mark a specific target in the crowd of biological samples, so that an image of a specific target can be observed by an optical microscope. The optical microscope, however, is constrained in resolution due to diffraction limit. Super-resolution microscopy made a breakthrough with this diffraction limit. Using a super-resolution microscope, many biomolecules are observed beyond the diffraction limit in cells. In the case of volumetric imaging, the super-resolution techniques are only applied to a limited area due to long imaging time, multiple scattering of photons, and sample-induced aberration in deep tissue. In this article, we review recent advances in super-resolution microscopy for volumetric imaging. The super-resolution techniques have been integrated with various modalities, such as a line-scan confocal microscope, a spinning disk confocal microscope, a light sheet microscope, and point spread function engineering. Super-resolution microscopy combined with adaptive optics by compensating for wave distortions is a promising method for deep tissue imaging and biomedical applications.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.11
• /
• pp.4290-4309
• /
• 2020

In recent years, advancements in machine learning capabilities have allowed it to see widespread adoption for tasks such as object detection, image classification, and anomaly detection. However, despite their promise, a limitation lies in the fact that a network's performance quality is based on the data which it receives. A well-trained network will still have poor performance if the subsequent data supplied to it contains artifacts, out of focus regions, or other visual distortions. Under normal circumstances, images of the same scene captured from differing points of focus, angles, or modalities must be separately analysed by the network, despite possibly containing overlapping information such as in the case of images of the same scene captured from different angles, or irrelevant information such as images captured from infrared sensors which can capture thermal information well but not topographical details. This factor can potentially add significantly to the computational time and resources required to utilize the network without providing any additional benefit. In this study, we plan to explore using image fusion techniques to assemble multiple images of the same scene into a single image that retains the most salient key features of the individual source images while discarding overlapping or irrelevant data that does not provide any benefit to the network. Utilizing this image fusion step before inputting a dataset into the network, the number of images would be significantly reduced with the potential to improve the classification performance accuracy by enhancing images while discarding irrelevant and overlapping regions.

• Korea Trade Review
• /
• v.44 no.2
• /
• pp.83-94
• /
• 2019

Article 17 of the Marine Insurance Act (MIA) states that "A contract of marine insurance is a contract based upon the utmost good faith, and if the utmost good faith be not observed by either party, the contract may be avoided by the other party." In the Carter v. Boehm case, Lord Mansfield was the first to provide a comprehensive description of the duty of utmost good faith, which is analyzed here. This judgement not only laid the foundation for the Modern English Insurance Act, but it also influenced the draft of the English Insurance Act of 2015, which aimed at correcting distortions that occurred during the application of statue law and common law thereafter. The duty of utmost good faith, applied between Lord Mansfield's insured and insurer presents the context of information asymmetry of the insured and insurer entering contracts. In the absence of information asymmetry, in contrast to the effects of being in both sides of the duty of utmost good faith, alleviating the duty of disclosure of the insured, and it is also clear that the warning of the severity of the retrospective avoidance of the breach of duty of disclosure and the need for its limited application have already been pointed out. Furthermore, considering the principle of retrospective avoidance, the duty of utmost good faith should be understood as a concept limited to the duty of disclosure before a contract is concluded

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.18 no.4
• /
• pp.93-102
• /
• 2008

Fingerprint sensor interoperability refers to the ability of a system to compensate for the variability introduced in the finger data of individual due to the deployment of different sensors. The purpose of this paper is the development of a compensation algorithm by which the interoperability of fingerprint recognition can be improved among various different fingerprint sensors. In this paper we show that a simple transformation derived to form a Taylor series expansion can be used in conjunction with a set of corresponding minutia points to improve the correspondence of finer fingerprint details within a fingerprint image. This is demonstrated by an applying the transformation to a database of fingerprint images and examining the minutiae match scores with and without the transformation. The EER of the proposed method was improved by average 60.94% better than before compensation.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.31 no.3
• /
• pp.387-400
• /
• 2021

The increase in number of streaming platforms and contents thereof, owing to an advancement of cloud environment, has triggered the rapid proliferation of illegally replicated contents as well as legal contents. This necessitates the development of technology capable of discriminating the copyright infringement of various contents. The Korea Copyright Protection Agency operates a video content demonstration system using AI, but it has limitations on distortions such as resolution changes. In this paper, we propose the powerful mechanism using skeleton, which is resistant against distorted video contents and capable of discriminating copyright infringement of platforms streaming illegal video contents. The proposed mechanism exploits the calculation of Hamming distance to the original video by converting collected data into binary ones for the efficient calculation. As a result of the experiment, the proposed mechanism have demonstrated the discrimination of illegally replicated video contents with an accuracy of 94.79% and average magnitude of 215KB.