• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.143-151
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• 2017

The generalized Hough transform(GHough) can be used effectively for detecting and extracting an arbitrary-shaped 2-D model in an input image. However, the main drawbacks of the GHough are both heavy computation and an excessive storage requirement. Thus, most of the researches so far have focused on reducing both the time and space requirement of the GHough. But it is still not clear how well their improved algorithms will perform under various noise in an input image. Thus, this paper proposes a new framework that can measure the performance of the GHough quantitatively. For this purpose, we view the GHough as a detector in signal detection theory and the ROC curve will be used to specify the performance of the GHough. Finally, we show that we can evaluate the GHough under various noise conditions in an input image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1176-1182
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• 2021

Recently, with the development of artificial intelligence and IoT technology, automation, and unmanned work are progressing in various fields, and the importance of image processing, which is the basis of AI object recognition, is increasing. In particular, in systems that require detailed data processing, noise removal is used as a preprocessing step, but the existing algorithm does not consider the noise level of the image, so it has the disadvantage of blurring in the filtering process. Therefore, in this paper, we propose a modified Gaussian filter that determines the weight by determining the noise level of the image. The proposed algorithm obtains the noise estimate for the AWGN of the image using quadtree segmentation, determines the Gaussian weight and the pixel weight, and obtains the final output by convolution with the local mask. To evaluate the proposed algorithm, it was simulated compared to the existing method, and superior performance was confirmed compared to the existing method.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.441-447
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• 2018

This study aims to develop digital techniques that enable repeated practice of dental radiography using augmented reality technology. A three-dimensional object was fabricated by superimposing a photograph of an adult model and a computed tomography image of a manikin phantom. The system was structured using 106 radiographs such that one of these saved radiographs is opened when the user attempts to take a radiograph on a mobile device. This system enabled users to repeatedly practice at the pre-clinical stage without exposure to radiation. We attempt to contribute to enhancing dental hygienists' competency in dental radiography using these techniques. However, a system that enables the user to actually take a radiograph based on face recognition would be more useful in terms of practice, so additional studies are needed on the topic.

• Korean Journal of Construction Engineering and Management
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• v.22 no.5
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• pp.48-54
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• 2021

According to the Ministry of Employment and Labor's statistics on occupational fatalities in South Korea, more than half of the fatalities in the past five years have occurred in the construction industry. The stuck-by and caught-in-between accidents associated with construction equipment is the major source of fatalities from construction sites. In order to prevent such accidents in construction sites, the government has spent lots of efforts including proposing the "special law on construction safety" and encouraging the implementation of new technology for accident prevention. However, numerous accidents are still occurred at construction sites and further efforts are still required. In this manner, this study developed a collision prevention technique that can prevent collision between equipment and worker by recognizing location and type of the nearby objects through ultrasound scanning. The study conducted a pilot experiment and the analysis results demonstrate the feasibility of achieving high performance in both object recognition and location estimation. The developed technique will contribute to prevent collision accidents at construction sites and provide the supplemental knowledge on developing automated collision prevention system for construction equipment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.17-22
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• 2022

In this paper, we design a lightweight embedded device that can support intelligent edge computing, and show that the device quickly detects an object in an image input from a camera device in real time. The proposed system can be applied to environments without pre-installed infrastructure, such as an intelligent video control system for industrial sites or military areas, or video security systems mounted on autonomous vehicles such as drones. The On-Device AI(Artificial intelligence) technology is increasingly required for the widespread application of intelligent vision recognition systems. Computing offloading from an image data acquisition device to a nearby edge device enables fast service with less network and system resources than AI services performed in the cloud. In addition, it is expected to be safely applied to various industries as it can reduce the attack surface vulnerable to various hacking attacks and minimize the disclosure of sensitive data.

• Smart Media Journal
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• v.11 no.11
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• pp.25-31
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• 2022

Deep learning-based image processing is essential for autonomous vehicles. To process road images in real-time in a System-on-Chip (SoC) environment, we need to execute deep learning models on a NPU (Neural Procesing Units) specialized for deep learning operations. In this study, we imported seven open-source image processing deep learning models, that were developed on GPU servers, to Texas Instrument Deep Learning (TIDL) NPU environment. We confirmed that the models imported in this study operate normally in the SoC virtual environment through performance evaluation and visualization. This paper introduces the problems that occurred during the migration process due to the limitations of NPU environment and how to solve them, and thereby, presents a reference case worth referring to for developers and researchers who want to port deep learning models to SoC environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.250-252
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• 2022

Recently, with the development of IoT technology and AI, unmanned and automated systems are progressing in various fields, and various application technologies are being studied in systems using algorithms such as object detection, recognition, and tracking. In the case of a system operating based on an image, noise removal is performed as a pre-processing process, and precise noise removal is sometimes required depending on the environment of the system. In this paper, we propose a modified central weight filter algorithm using pixel division of local regions to minimize the blurring that tends to occur in the filtering process and to emphasize the details of the resulting image. In the proposed algorithm, when a pixel of a local area is divided into two areas, the center of the dominant area among the divided areas is set as a criterion for the weight filter algorithm. The resulting image is calculated by convolving the transformed center weight with the pixel value inside the filtering mask.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.47-58
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• 2008

With the recent development of the ubiquitous computing technology, there are increasing interest and research in technologies such as sensors and RFID related to information recognition and location positioning in various ubiquitous fields. Especially, a standard specification was required for compatibility and interoperability in various RTLS(Real-Time Locating Systems) according to the development of RTLS to provide location and status information of moving objects using the RFID Tag. For these reasons, the ISO/IEC published the RTLS standard specification for compatibility and interoperability in RTLS. Therefore, in this paper, we designed and im plemented RTLS based on the spatial DSMS(Data Stream Management Stream) for efficiently managing and searching the incoming data stream of moving objects. The spatial DSMS is an extended system of STREAM(STanford stREam datA Manager) developed by Standford University to make various spatial operations possible. RTLS based on the spatial DSMS uses the SOAP(Simple Object Access Protocol) message between client and server for interoperability and translates client's SOAP message into CQL(Continuous Query Language) of the spatial DSMS. Finally, we proved the efficiency of RTLS based on the spatial DSMS by applying it for the staff location management service.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.3
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• pp.360-366
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• 2014

Kimchi is a Korean traditional fermented food with various health functionalities. However, the protective effects of kimchi against Alzheimer's disease (AD) have not been studied yet. In this study, the protective activities of kimchi extract against oxidative stress and AD were investigated in an amyloid beta ($A{\beta}$)-induced AD model using ICR mice. Kimchi extract exerted strong scavenging activities against 1,1-diphenyl-2-picrylhydrazyl and hydroxyl radical. In addition, T-maze, object cognition, and water maze tests were carried out using the AD model. The $A{\beta}_{25-35}$-injected groups showed impairment of cognition and memory. However, the abilities of novel object recognition and new route awareness were improved by administration of kimchi extract (100 and 200 mg/kg/day) for 2 weeks. Furthermore, the results on water maze test indicated that kimchi extract exerted protective activity against cognitive impairment induced by $A{\beta}_{25-35}$. The present study suggested that kimchi protected against $A{\beta}$-induced impairment of memory and cognition as well as attenuated oxidative stress.

• Smart Media Journal
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• v.13 no.4
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• pp.114-123
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• 2024

This paper proposes AR stone tower content, an experiential content based on wearable augmented reality (AR). Although wearable augmented reality is gaining attention, the acceptance of the technology is still focused on specialized applications such as industrial sites. On the other hand, the proposed AR stone tower content is based on the material of 'stone tower' so that general users can relate to it and easily participate in it, and it is organized to utilize space in a moving environment and find and stack stones based on natural hand gestures. The proposed AR stone tower content was implemented in the HoloLens 2 environment and evaluated by general users through a pilot exhibition in a small art museum. The evaluation results showed that the overall satisfaction with the content averaged 3.85, and the content appropriateness for the stone tower material was very high at 4.15. In particular, users were highly satisfied with content comprehension and sound, but somewhat less satisfied with object recognition, body adaptation, and object control. The above user evaluations confirm the resonance and positive response to the material, but also highlight the difficulties of the average user in experiencing and interacting with the wearable AR environment.