• Korean Journal of Optics and Photonics
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• v.30 no.2
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• pp.37-47
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• 2019

A reflecting omnidirectional optical system with four spherical and aspherical mirrors, for use with long-wavelength infrared light (LWIR) for night surveillance, is proposed. It is designed to include a collecting pseudo-Cassegrain reflector and an imaging inverse pseudo-Cassegrain reflector, and the design process and performance analysis is reported in detail. The half-field of view (HFOV) and F-number of this optical system are $40-110^{\circ}$ and 1.56, respectively. To use the LWIR imaging, the size of the image must be similar to that of the microbolometer sensor for LWIR. As a result, the size of the image must be $5.9mm{\times}5.9mm$ if possible. The image size ratio for an HFOV range of $40^{\circ}$ to $110^{\circ}$ after optimizing the design is 48.86%. At a spatial frequency of 20 lp/mm when the HFOV is $110^{\circ}$, the modulation transfer function (MTF) for LWIR is 0.381. Additionally, the cumulative probability of tolerance for the LWIR at a spatial frequency of 20 lp/mm is 99.75%. As a result of athermalization analysis in the temperature range of $-32^{\circ}C$ to $+55^{\circ}C$, we find that the secondary mirror of the inverse pseudo-Cassegrain reflector can function as a compensator, to alleviate MTF degradation with rising temperature.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1321-1323
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• 2013

지능형 자동차에서 영상 기반 능동 안전시스템의 신뢰성을 확보하기 위해서는 도로 위의 다양한 객체를 강건하게 검출하고, 추적하는 것이 가장 중요하다. 본 논문에서는 다중 가설 기반 추적 프레임워크를 이용하여, 실시간으로 전방 차량을 검출하고 추적하는 시스템을 제안한다. 제안한 시스템은 다양한 외부 도로 환경에서 획득된 실험 영상에 대하여 10-15Hz 의 처리 속도로, 평균적으로 98%의 인식률을 제공할 수 있다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.149-156
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• 2008

SLAM(Simultaneous Localization and Mapping) system is to find a global position and build a map with sensing data when an unmanned-robot navigates an unknown environment. Two kinds of system were developed. One is used distance measurement sensors such as an ultra sonic and a laser sensor. The other is used stereo vision system. The distance measurement SLAM with sensors has low computing time and low cost, but precision of system can be somewhat worse by measurement error or non-linearity of the sensor In contrast, stereo vision system can accurately measure the 3D space area, but it needs high-end system for complex calculation and it is an expensive tool. In this paper, we implement the SLAM system using a single camera image and a PSD sensors. It detects obstacles from the front PSD sensor and then perceive size and feature of the obstacles by image processing. The probability SLAM was implemented using the data of sensor and image and we verify the performance of the system by real experiment.