• The Journal of the Korean dental association
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• v.57 no.7
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• pp.392-402
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• 2019

The most important part of everyday root canal treatment is diagnosis about the morphology of tooth, root and root canal. Usually this procedure is performed by visual examination and radiographic (panoramic/periapical) examination. However, 2-dimentional radiography has several limitations such as imposition of anatomic structures including buccal/lingual root canals and distortion of images. Recently, owing to the increased interest in dental implant and affordable cost of CBCT equipment, CBCT has been introduced widely in local dental clinics. CBCT is characterized by their lower radiation dose and shorter exposure time than conventional CT scan, and ability of 3-dimentional reconstruction of the dento-alveolar structure. Also in endodontic field, the data from CBCT could be very helpful in diagnosing complex root canal anatomy, apical periodontitis, cause of failure and in determining treatment plan. However, there are some limitations such as radiation dose and artifact. Therefore, clinicians should know about indication, advantages and limitations of CBCT, and properly use it for successful root canal treatment to save the natural teeth.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1479-1494
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• 2020

As an important part of image processing, image demosaicking has been widely researched. It is especially necessary to propose an efficient interpolation algorithm with good visual quality and performance. To improve the limitations of residual interpolation (RI), based on RI algorithm, minimalized-Laplacian RI (MLRI), and iterative RI (IRI), this paper focuses on adaptive RI (ARI) and proposes an improved ARI (IARI) algorithm which obtains more distinct R, G, and B colors in the images. The proposed scheme fully considers the brightness information and edge information of the image. Since the ARI algorithm is not completely adaptive, IARI algorithm executes ARI algorithm twice on R and B components according to the directional difference, which surely achieves an adaptive algorithm for all color components. Experimental results show that the improved method has better performance than other four existing methods both in subjective assessment and objective assessment, especially in the complex edge area and color brightness recovery.

• Journal of Aerospace System Engineering
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• v.15 no.4
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• pp.75-84
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• 2021

A novel robot-operating-system-based flight and mission state communication node for X-Plane 11 flight control simulation environments and its simulation results were discussed. Although the proposed communication method requires considerable implementation steps compared with the conventional MATLAB/Simulink-based User Datagram Protocol (UDP) block utilization method, the proposed method enables a direct comparison of cockpit-view images captured during flight with the flight data. This comparison is useful for data acquisition under virtual environments and for the development of flight control systems. The fixed/rotary-wing and ground terrain elements simulated in virtual environments exhibited excellent visualization outputs, which can overcome time and space constraints on flight experiments and validation of missionary algorithms with complex logic.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1146-1165
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• 2022

A huge amount of data in the form of videos and images is being produced owning to advancements in sensor technology. Use of low performance commodity hardware coupled with resource heavy image processing and analyzing approaches to infer and extract actionable insights from this data poses a bottleneck for timely decision making. Current approach of GPU assisted and cloud-based architecture video analysis techniques give significant performance gain, but its usage is constrained by financial considerations and extremely complex architecture level details. In this paper we propose a data pipeline system that uses open-source tools such as Apache Spark, Kafka and OpenCV running over commodity hardware for video stream processing and image processing in a distributed environment. Experimental results show that our proposed approach eliminates the need of GPU based hardware and cloud computing infrastructure to achieve efficient video steam processing for face detection with increased throughput, scalability and better performance.

• Annual Conference of KIPS
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• 2022.05a
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• pp.627-630
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• 2022

Over the past few years, fake news has become one of the most significant problems. Since it is impossible to prevent people from spreading misinformation, people should analyze the news themselves. However, this process takes some time and effort, so the routine part of this analysis should be automated. There are many different approaches to this problem, but they only analyze the text and messages, ignoring the images. The fake news problem should be solved using a complex analysis tool to reach better performance. In this paper, we propose the approach of training an Artificial Intelligence using an unsupervised learning algorithm, combined with online data parsing tools, providing independence from subjective data set. Therefore it will be more difficult to spread fake news since people could quickly check if the news or article is trustworthy.

• Journal of The Korean Astronomical Society
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• v.29 no.spc1
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• pp.77-78
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• 1996

We perfom a large project for complex study of Blue Compact Galaxies (BCGs) with strong star formation, which includes optical spectroscopy, BVR CCD photometry and HI 21 cm radio survey. The most interesting galaxies are studied also with HST and VLA. In the frame of this project we began the study of H$\alpha$ morphology of BCGs with 6-m telescope. We present and discuss here the results for the first 6 galaxies. We found the noticeable variety of forms for H$\alpha$ morphology comparing to broad band images: from very compact HII region in very center of stellar body (Mark 996, possible dwarf post-merger, old galaxy experiencing strong star formation burst), to very extended gas emission encompassing the whole area traced by stars (SBS 0335-052, the most probable young galaxy in formation).

• Annals of Clinical Neurophysiology
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• v.25 no.1
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• pp.10-18
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• 2023

The ultimate purpose of eye movement is to maintain clear vision by ensuring that images of observed objects are focused on the fovea in the retina. Accurate evaluation of ocular movements, including nystagmus and saccadic intrusions, provides very useful information for determining the overall function and abnormality of the complex oculomotor system, from the peripheral vestibular system to the cerebrum. Eye movement tests are therefore essential for the accurate diagnosis of patients who complain of dizziness and imbalance. They help to predict lesion locations from the peripheral vestibular system to the central cerebral cortex and play an important role in differentiation from other diseases. The methodology of recording and interpreting ocular movements using video-oculography are described in this review article.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.39-47
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• 2023

This study compares various transformation techniques for multifocus image fusion. Multi-focus image fusion is a procedure of merging multiple images captured at unalike focus distances to produce a single composite image with improved sharpness and clarity. In this research, the purpose is to compare different popular frequency domain approaches for multi-focus image fusion, such as Discrete Wavelet Transforms (DWT), Stationary Wavelet Transforms (SWT), DCT-based Laplacian Pyramid (DCT-LP), Discrete Cosine Harmonic Wavelet Transform (DC-HWT), and Dual-Tree Complex Wavelet Transform (DT-CWT). The objective is to increase the understanding of these transformation techniques and how they can be utilized in conjunction with one another. The analysis will evaluate the 10 most crucial parameters and highlight the unique features of each method. The results will help determine which transformation technique is the best for multi-focus image fusion applications. Based on the visual and statistical analysis, it is suggested that the DCT-LP is the most appropriate technique, but the results also provide valuable insights into choosing the right approach.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.27 no.2
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• pp.146-159
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• 2023

This paper proposes a hybrid algorithm combining K-means clustering and watershed algorithms for flower segmentation and counting. We use the K-means clustering algorithm to obtain the main colors in a complex background according to the cluster centers and then take a color space transformation to extract pixel values for the hue, saturation, and value of flower color. Next, we apply the threshold segmentation technique to segment flowers precisely and obtain the binary image of flowers. Based on this, we take the Euclidean distance transformation to obtain the distance map and apply it to find the local maxima of the connected components. Afterward, the proposed algorithm adaptively determines a minimum distance between each peak and apply it to label connected components using the watershed segmentation with eight-connectivity. On a dataset of 30 images, the test results reveal that the proposed method is more efficient and precise for the counting of overlapped flowers ignoring the degree of overlap, number of overlap, and relatively irregular shape.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.674-675
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• 2015

A 3D indoor model becomes an indiscernible component of BIM (Building Information Modeling) and GIS (Geographic Information System). However, a huge amount of time and human resources are inevitable for collecting spatial measurements and creating such a 3D indoor model. Also, a varied forms of 3D indoor models exist depending on their purpose of use. Thus, in this study, three different 3D indoor models are defined as 1) omnidirectional images, 2) a 3D realistic model, and 3) 3D indoor as-built model. A series of reconstruction methods is then introduced to construct each type of 3D indoor models: they are an omnidirectional image acquisition method, a hybrid surveying method, and a terrestrial LiDAR-based method. The reconstruction methods are applied to a large and complex atrium, and their 3D modeling results are compared and analyzed.