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전조등의 시각적 특성을 이용한 야간 사각 지대 차량 검출 기법
정정은,김현구,박주현,정호열,Joung, Jung-Eun,Kim, Hyun-Koo,Park, Ju-Hyun,Jung, Ho-Youl 대한임베디드공학회 2011 대한임베디드공학회논문지 Vol.6 No.5
The blind spot is an area where drivers visibility does not reach. When drivers change a lane to adjacent lane, they need to give an attention because of the blind spot. If drivers try to change lane without notice of vehicle approaching in the blind spot, it causes a reason to have a car accident. This paper proposes a night-time blind spot vehicle detection using cameras. At nighttime, head-lights are used as characteristics to detect vehicles. Candidates of headlight are selected by high luminance feature and then shape filter and kalman filter are employed to remove other noisy blobs having similar luminance to head-lights. In addition, vehicle position is estimated from detected head-light, using virtual center line represented by approximated the first order linear equation. Experiments show that proposed method has relatively high detection porformance in clear weather independent to the road types, but has not sufficient performance in rainy weather because of various ground reflectors.
통계적 특징 기반 SVM을 이용한 야간 전방 차량 검출 기법
정정은,김현구,박주현,정호열,Joung, Jung-Eun,Kim, Hyun-Koo,Park, Ju-Hyun,Jung, Ho-Youl 대한임베디드공학회 2012 대한임베디드공학회논문지 Vol.7 No.4
A driver assistance system is critical to improve a convenience and stability of vehicle driving. Several systems have been already commercialized such as adaptive cruise control system and forward collision warning system. Efficient vehicle detection is very important to improve such driver assistance systems. Most existing vehicle detection systems are based on a radar system, which measures distance between a host and leading (or oncoming) vehicles under various weather conditions. However, it requires high deployment cost and complexity overload when there are many vehicles. A camera based vehicle detection technique is also good alternative method because of low cost and simple implementation. In general, night time vehicle detection is more complicated than day time vehicle detection, because it is much more difficult to distinguish the vehicle's features such as outline and color under the dim environment. This paper proposes a method to detect vehicles at night time using analysis of a captured color space with reduction of reflection and other light sources in images. Four colors spaces, namely RGB, YCbCr, normalized RGB and Ruta-RGB, are compared each other and evaluated. A suboptimal threshold value is determined by Otsu algorithm and applied to extract candidates of taillights of leading vehicles. Statistical features such as mean, variance, skewness, kurtosis, and entropy are extracted from the candidate regions and used as feature vector for SVM(Support Vector Machine) classifier. According to our simulation results, the proposed statistical feature based SVM provides relatively high performances of leading vehicle detection with various distances in variable nighttime environments.
최연호,조내수,정정은,권우현,이동하,Choi, Youn-Ho,Cho, Nae-Soo,Joung, Jung-Eun,Kwon, Woo-Hyen,Lee, Dong-Ha 한국태양에너지학회 2012 한국태양에너지학회 논문집 Vol.32 No.suppl3
The research of the biological mimics robot which utilizes the operation of the organism is progressed on the ground, aerial, and underwater robot sector. In the field of flying robot, the research for implementing the wing movement structure of the bird and insect is progressed. The joint structure for the wing movement of the bird is implemented. The operation of the wing is simulated. For this purpose, by using the Matlab/Simulink, the joint structure of the wing is modelled. The joint movement of the wing is tested through the simulation.