• The Journal of Korean Institute of Information Technology
• /
• v.16 no.11
• /
• pp.51-59
• /
• 2018

The Multi-Mission Unmanned Surface Vehicle(MMUSV), which is manufactured using glass Fiber Reinforced Plastic(FRP) material, is designed to perform a surveillance and reconnaissance on the sea. Various navigation sensors, such as RADAR, RIDAR, camera, are mounted on a mast to perform an autonomous navigation. And a dummy gun is mounted on the deck of the MMUSV for a target tracking and disposal. It is necessary to analyze a strength for structures mounted on the deck because the MMUSV performs missions under a severe sea state. In this paper, a strength analysis of the mast structure is performed on static loads and lateral external loads to verify an adequacy of the designed mast through a series of simulations. Based on the results of captive model tests, a strength analysis for a heave motion of the mast structure is conducted using a simulation tool. Also a simulation and fatigue test for a mounting part between the MMUSV and the dummy gun are performed using a specimen. The simulation and test results are represented that a structure of the mast and mounting part of the dummy gun are appropriately designed.he impact amount are performed through simulation and experiments.

• Korean Security Journal
• /
• no.19
• /
• pp.225-244
• /
• 2009

Electronic security system is composed mainly of electronic-information-communication device, so system technology, configuration and management of the electronic security system could be affected by the change of information-communication environment. This study is to propose the future prospect on the development of technique for electronic security system through the analysis of the trend and the actual condition on the development of technique. This study is based on literature study and interview with user and provider of electronic security system, also survey was carried out by system provider and members of security integration company to come up with more practical result. Hybrid DVR technology that has multi-function such as motion detection, target tracking and image identification is expected to be developed. And 'Embedded IP camera' technology that internet server and image identification software are built in. Those technologies could change the configuration and management of CCTV system. Fingerprint identification technology and face identification technology are continually developed to get more reliability, but continual development of surveillance and three-dimension identification technology for more efficient face identification system is needed. As radio identification and tracking function of RFID is appreciated as very useful for access control system, hardware and software of RFID technology is expected to be developed, but government's support for market revitalization is necessary. Behavior pattern identification sensor technology is expected to be developed and could replace passive infrared sensor that cause system error, giving security guard firm confidence for response. The principle of behavior pattern identification is similar to image identification, so those two technology could be integrated with tracking technology and radio identification technology of RFID for total monitoring system. For more efficient electronic security system, middle-ware's role is very important to integrate the technology of electronic security system, this could make possible of installing the integrated security system.

• Journal of Intelligence and Information Systems
• /
• v.29 no.2
• /
• pp.171-187
• /
• 2023

When a person's face is recognized through a recording device such as a low-pixel surveillance camera, it is difficult to capture the face due to low image quality. In situations where it is difficult to recognize a person's face, problems such as not being able to identify a criminal suspect or a missing person may occur. Existing studies on face recognition used refined datasets, so the performance could not be measured in various environments. Therefore, to solve the problem of poor face recognition performance in low-quality images, this paper proposes a method to generate high-quality images by performing image quality improvement on low-quality facial images considering various environments, and then improve the performance of facial feature point detection. To confirm the practical applicability of the proposed architecture, an experiment was conducted by selecting a data set in which people appear relatively small in the entire image. In addition, by choosing a facial image dataset considering the mask-wearing situation, the possibility of expanding to real problems was explored. As a result of measuring the performance of the feature point detection model by improving the image quality of the face image, it was confirmed that the face detection after improvement was enhanced by an average of 3.47 times in the case of images without a mask and 9.92 times in the case of wearing a mask. It was confirmed that the RMSE for facial feature points decreased by an average of 8.49 times when wearing a mask and by an average of 2.02 times when not wearing a mask. Therefore, it was possible to verify the applicability of the proposed method by increasing the recognition rate for facial images captured in low quality through image quality improvement.