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This paper describes a multi-resolution stereovision system for detecting the front-vehicle in advanced safety vehicles (ASVs). The two asynchronous CMOS cameras in the proposed system are mounted on a platform that can be easily clamped to the rearview mirror of a vehicle for detecting vehicles ahead. The asynchronous binocular platform provides a small low-cost obstacle detection system for practical ASVs that is easy to set up. The system uses a stereovision vehicle detection algorithm for real-time matching because the exposure times of the CMOS cameras are not synchronous. The algorithm uses a line segment matching module to match the extreme points of the horizontal and vertical edge segments at different resolutions to decrease the search area and computing complexity. As the distance of each matched segment can be calculated from the disparity value, each vehicle can be detected by clustering the segments that have similar distances in a searching and distance estimation module. The system was evaluated using static and dynamic analyses. Experimental results show that the proposed system can robustly and accurately detect the front-vehicles in real time under different illumination and road conditions.

被引用紀錄


Chang, H. C. (2007). 灰色理論與模糊類神經網路之研究及應用 [doctoral dissertation, National Central University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0031-0207200917343277
簡偉丞(2011)。適應性車道偏離警示與夜間前車碰撞警示系統〔碩士論文,國立中央大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0031-1903201314421127
楊沅智(2012)。可適應天候變化的前車碰撞警示系統〔碩士論文,國立中央大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0031-1903201314443189
Chen, C. F. (2014). 以Meteor為基礎之Cadabia資料庫系統安全框架 [master's thesis, National Chung Cheng University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0033-2110201613585593

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