• Korean Journal of Remote Sensing
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• v.18 no.3
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• pp.147-153
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• 2002

The real-time reception and recording of down-link mission data from a satellite requires the highest reliability because the data lost in receiving process cannot be recovered. The data receiving and recording system has moved from a set of dedicated hardware and software components to commercial-off-the-shelf (COTS) components in order to reduce the system cost as well as to upgrade the system easily for handling other satellite data. The use of COTS hardware and middleware components prevents the system developer from correcting or modifying the internal operations of the COTS components, and hence, instant performance degradation of the COTS components which affects the reliable data acquisition must be covered by a software algorithm. This paper introduces the instant performance problem of a COTS data recording device which leads to the data loss in the real-time data reception and recording process. As a result, the requirement of the modification of the conventional data read/write technique is issued. In order to overcome the data loss problem due to the use of COTS components and the conventional software technique, a new algorithm called a software buffering technique is proposed. The experiments show that the application of the proposed technique results in reliable real-time reception and recording of high speed serial data.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.55-61
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• 2019

In this paper, if images are acquired in all-time situations through various sensors (EO/IR, SAR, GMTI, LiDAR) used for defense purposes, the images can be analyzed and expressed in augmented reality(AR). Various algorithms are used to process images with augmented reality, and depending on the situation, it is necessary to decide which algorithms to select and use. Through the performance comparison (error rate, processing time, accuracy) of SIFT, SURF, ORB, and BRISK, the representative augmented reality algorithm, it is analyzed and proposed which augmented reality algorithm is effective to use under various situations in the defense field.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.430-439
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• 2019

The CNN (convolutional neural network) based single degradation restoration method shows outstanding performance yet is tailored on solving a specific degradation type. In this paper, we present an algorithm of multi-degradation classification and restoration. We utilize the CNN based algorithm for solving image degradation classification problem using pre-trained Inception-v3 network. In addition, we use the existing CNN based algorithms for solving particular image degradation problems. We identity the restoration order of multi-degraded images empirically and compare with the non-reference image quality assessment score based on CNN. We use the restoration order to implement the algorithm. The experimental results show that the proposed algorithm can solve multi-degradation problem.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.57-65
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• 2019

In this paper, we propose a Rights Management Information(RMI) expression systems for individual sites are integrated and the performance evaluation is performed to find out an efficient comparing and updating method of RMI through various image feature point search techniques. In addition, we proposed a weighted scoring model for both public domain sites and posts in order to use the most latest RMI based on reliable data. To solve problem that most public domain sites are exposed to copyright infringement by providing inconsistent RMI(Rights Management Information) expression system and non-up-to-date RMI information. The weighted scoring model proposed in this paper makes it possible to use the latest RMI for duplicated images that have been verified through the performance evaluation experiments of SIFT and CNN techniques and to improve the accuracy when applied to search engines. In addition, there is an advantage in providing users with accurate original public domain images and their RMI from the search engine even when some modified public domain images are searched by users.

• The Journal of Korea Robotics Society
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• v.16 no.1
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• pp.56-63
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• 2021

As the use of robots in service area increases, research has been conducted to replace human tasks in daily life with robots. Among them, this study focuses on the tidy-up task on a desk using a robot arm. The order in which tidy-up motions are carried out has a great impact on the success rate of the task. Therefore, in this study, a neural network-based method for determining the priority of the tidy-up motions from the input image is proposed. Reinforcement learning, which shows good performance in the sequential decision-making process, is used to train such a task planner. The training process is conducted in a virtual tidy-up environment that is configured the same as the actual tidy-up environment. To transfer the learning results in the virtual environment to the actual environment, the input image is preprocessed into a segmented image. In addition, the use of a neural network that excludes unnecessary tidy-up motions from the priority during the tidy-up operation increases the success rate of the task planner. Experiments were conducted in the real world to verify the proposed task planning method.

• Investigative Magnetic Resonance Imaging
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• v.26 no.2
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• pp.83-95
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• 2022

The purpose of this study was to establish and provide guidelines for the standardized acquisition and interpretation of diffusion-weighted magnetic resonance imaging (DW-MRI) to improve the image quality and reduce the variability of the results interpretation. The standardized protocol includes the use of high-resolution DW-MRI with advanced techniques and post-processing. The aim of the protocol is to increase the effectiveness of the medical image information exchange involved in the construction, activation, and exchange of clinical information for healthcare use. An organized interpretation form could make DW-MRIs' interpretation easier and more familiar. Herein, the authors briefly review the basic principles, optimized image acquisition, standardized interpretation guidelines, false negative and false positive cases of DW-MRI, and provide a standard interpretation form and examples of various cases to help users become more familiar with the DW-MRI.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.99-105
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• 2024

Runway released an updated version, Gen-2, in March 2023, which introduced new features that are different from Gen-1: it can convert text and images into videos, or convert text and images together into video images based on text instructions. This update will be officially open to the public in June 2023, so more people can enjoy and use their creativity. With this new feature, users can easily transform text and images into impressive video creations. However, as with all new technologies, comes the instability of AI, which also affects the results generated by Runway. This article verifies the feasibility of using Runway to generate the desired video from several aspects through personal practice. In practice, I discovered Runway generation problems and propose improvement methods to find ways to improve the accuracy of Runway generation. And found that although the instability of AI is a factor that needs attention, through careful adjustment and testing, users can still make full use of this feature and create stunning video works. This update marks the beginning of a more innovative and diverse future for the digital creative field.

• Korean Journal of Radiology
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• v.23 no.3
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• pp.308-321
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• 2022

Transabdominal ultrasound (TAUS) is useful in all aspects of lesion screening, monitoring activity, or treating/diagnosing any related complications of inflammatory bowel disease. Its ability to screen or diagnose complications is almost the same as that of other methods, such as CT or MRI. Moreover, its noninvasiveness makes it a first-line examination method. A TAUS image depicting ulcerative colitis will show large intestinal wall thickening that is continuous from the rectum, which is mainly due to mucosal layer thickening, while for Crohn's disease, a TAUS image is characterized by a diversity in the areas affected, distribution, and layer structure. Indicators of activity monitoring include wall thickness, wall structure, and vascular tests that use Doppler ultrasound or contrast agents. While all of these have been reported to be useful, at this time, no single parameter has been established as superior to others; therefore, a comprehensive evaluation of these parameters is justified. In addition, evaluating the elasticity of lesions using elastography is particularly useful for distinguishing between fibrous and inflammatory stenoses. However, the lack of objectivity is the biggest drawback of using ultrasound. Standardizing and popularizing the ultrasound process will be necessary, including scanning methods, equipment settings, and image analysis.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.3
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• pp.102-109
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• 2009

Purpose: Flash 3D (pixon(R) method; 3D OSEM) was developed as a software program to shorten exam time and improve image quality through reconstruction, it is an image processing method that usefully be applied to nuclear medicine tomography. If perfoming brain diamox perfusion scan by reconstructing subtracted images by Flash 3D with shortened image acquisition time, there was a problem that SNR of subtracted image is lower than basal image. To increase SNR of subtracted image, we use LEAP collimators, and we emphasized on sensitivity of vessel dilatation than resolution of brain vessel. In this study, our purpose is to confirm possibility of application of LEAP collimators at brain diamox perfusion tomography, identify proper reconstruction factors by using Flash 3D. Materials and methods: (1) The evaluation of phantom: We used Hoffman 3D Brain Phantom with $^{99m}Tc$. We obtained images by LEAP and LEHR collimators (diamox image) and after 6 hours (the half life of $^{99m}Tc$: 6 hours), we use obtained second image (basal image) by same method. Also, we acquired SNR and ratio of white matters/gray matters of each basal image and subtracted image. (2) The evaluation of patient's image: We quantitatively analyzed patients who were examined by LEAP collimators then was classified as a normal group and who were examined by LEHR collimators then was classified as a normal group from 2008. 05 to 2009. 01. We evaluate the results from phantom by substituting factors. We used one-day protocol and injected $^{99m}Tc$-ECD 925 MBq at both basal image acquisition and diamox image acquisition. Results: (1) The evaluation of phantom: After measuring counts from each detector, at basal image 41~46 kcount, stress image 79~90 kcount, subtraction image 40~47 kcount were detected. LEAP was about 102~113 kcount at basal image, 188~210 kcount at stress image and 94~103 at subtraction image kcount were detected. The SNR of LEHR subtraction image was decreased than LEHR basal image about 37%, the SNR of LEAP subtraction image was decreased than LEAP basal image about 17%. The ratio of gray matter versus white matter is 2.2:1 at LEHR basal image and 1.9:1 at subtraction, and at LEAP basal image was 2.4:1 and subtraction image was 2:1. (2) The evaluation of patient's image: the counts acquired by LEHR collimators are about 40~60 kcounts at basal image, and 80~100 kcount at stress image. It was proper to set FWHM as 7 mm at basal and stress image and 11mm at subtraction image. LEAP was about 80~100 kcount at basal image and 180~200 kcount at stress image. LEAP images could reduce blurring by setting FWHM as 5 mm at basal and stress images and 7 mm at subtraction image. At basal and stress image, LEHR image was superior than LEAP image. But in case of subtraction image like a phantom experiment, it showed rough image because SNR of LEHR image was decreased. On the other hand, in case of subtraction LEAP image was better than LEHR image in SNR and sensitivity. In all LEHR and LEAP collimator images, proper subset and iteration frequency was 8 times. Conclusions: We could archive more clear and high SNR subtraction image by using proper filter with LEAP collimator. In case of applying one day protocol and reconstructing by Flash 3D, we could consider application of LEAP collimator to acquire better subtraction image.

• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.551-562
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• 2000

Content-based image retrieval system retrieves an image from a database using visual features. Among approaches to express visual aspects in queries, 'query by sketch' is most convenient and expressive. However, every 'query by sketch' system has the query imperfectness problem. GContent-based image retrieval system retrieves an image from a database using visual features. Among approaches to express visual aspects in queries, 'query by sketch' is most convenient and expressive. However, every 'query by sketch' system has the query imperfectness problem. Generally, the query image produced by a user is different from the intended target image. To overcome this problem, many image retrieval systems use the spatial relationships of the objects, instead of pixel coordinates of the objects. In this paper, a query-converting algorithm for an image retrieval system, which uses the spatial relationship of every two objects as an image feature, is proposed. The proposed algorithm converts the query image into a graph that has the minimum number of edges, by eliminating every transitive edge. Since each edge in the graph represents the spatial relationship of two objects, the elimination of unnecessary edges makes the retrieval process more efficient. Experimental results show that the proposed algorithm leads the smaller number of comparison in searching process as compared with other algorithms that do not guarantee the minimum number of edges.