• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.3
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• pp.193-200
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• 2016

This paper introduces an algorithm to middle-low price drone's autonomous navigation flight system using computer vision and GPS. Existing drone operative system mainly contains using methods such as, by inputting course of the path to the installed software of the particular drone in advance of the flight or following the signal that is transmitted from the controller. However, this paper introduces new algorithm that allows autonomous navigation flight system to locate specific place, specific shape of the place and specific space in an area that the user wishes to discover. Technology developed for military industry purpose was implemented on a lower-quality hobby drones without changing its hardware, and used this paper's algorithm to maximize the performance. Camera mounted on middle-low price drone will process the image which meets user's needs will look through and search for specific area of interest when the user inputs certain image of places it wishes to find. By using this algorithm, middle-low price drone's autonomous navigation flight system expect to be apply to a variety of industries.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.112-118
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• 2014

This paper deals with a color-based tracking of a moving object. Firstly, existing Camshift algorithm is complemented to improve the tracking weakness in the brightness change of an image which occurs in every frame. The complemented Camshift still shows unstable tracking when the objects with same color of the tracking object exist in background. In order to overcome the drawback this paper proposes the Camshift combined with KLT algorithm based on optical flow. The KLT algorithm performing the pixel-based feature tracking can complement the shortcoming of Camshift. Experimental results show that the merged tracking method makes up for the drawback of the Camshit algorithm and also improves tracking performance.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.324-326
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• 2016

In this study, we have investigated indium tin zinc oxide (ITZO) as an active channel for non-volatile memory (NVM) devices. The electrical and memory characteristics of NVM devices using multi-stack gate insulator SiO2/SiOx/SiOxNy (OOxOy) with Si-rich SiOx for charge storage layer were also reported. The transmittance of ITZO films reached over 85%. Besides, ITZO-based NVM devices showed good electrical properties such as high field effect mobility of 25.8 cm2/V.s, low threshold voltage of 0.75 V, low subthreshold slope of 0.23 V/dec and high on-off current ratio of $1.25{\times}107$. The transmission Fourier Transform Infrared spectroscopy of SiOx charge storage layer with the richest silicon content showed an assignment at peaks around 2000-2300 cm-1. It indicates that many silicon phases and defect sources exist in the matrix of the SiOx films. In addition, the characteristics of NVM device showed a retention exceeding 97% of threshold voltage shift after 104 s and greater than 94% after 10 years with low operating voltage of +11 V at only 1 ms programming duration time. Therefore, the NVM fabricated by high transparent ITZO active layer and OOxOy memory stack has been applied for the flexible memory system.

• Journal of Advanced Navigation Technology
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• v.16 no.3
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• pp.545-552
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• 2012

In this paper, we propose Modified Multi CAMShift Algorithm based on Kalman filter and Weighted Search Windows(KWMCAMShift) that extracts skin color area and tracks several human body parts for real-time human tracking system. We propose modified CAMShift algorithm that generates background model, extracts skin area of hands and head, and tracks the body parts. Kalman filter stabilizes tracking search window of skin area due to changing skin area in consecutive frames. Each occlusion areas is avoided by using weighted window of non-search areas and main-search area. And shadows are eliminated from background model and intensity of shadow. The proposed KWMCAMShift algorithm can estimate human pose in real-time and achieves 96.82% accuracy even in the case of occlusions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.254-260
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• 2019

Recently, a self-camera that generates and distributes a large amount of moving images has been rapidly increasing due to the appearance of SNS such as Facebook, Instagram, and Tweet using mobile. In particular, the amount of SNS connections using mobile phones is significantly increasing in terms of usage, number of connections, and usage time. However, the use of a self-recording system using a smartphone by itself is extremely limited not only in terms of usage but also in frequency of use. In addition, the conventional unattended recording system is a very expensive system that automatically records and tracks an object to be photographed using an infrared signal. Therefore, this paper developed a low cost unmanned recording system using mobile phone. The system consists of a commercial mobile camera, a servomotor for moving the camera from side to side, a microcontroller for controlling the motor, and a commercial wireless Bluetooth earset for video audio input. And it is an unmanned automation system using mobile, and anyone can record image by self image tracking.