Dynamic calibration and occlusion handling algorithms for lane tracking

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題名:	Dynamic calibration and occlusion handling algorithms for lane tracking
作者:	Wu, Bing-Fei;Lin, Chuan-Tsai;Chen, Yen-Lin
貢獻者:	Department of Computer Science and Information Engineering
關鍵詞:	Calibration;Cameras;Curve fitting;Detectors;Feature extraction;Fuzzy logic;Fuzzy sets;Graph theory;Heuristic algorithms;Heuristic methods;Image processing;Intelligent robots;Learning algorithms;Portals;Road and street markings;Roads and streets;Splines;Autonomous vehicle;Driving assistance;Image edge detection;Lane detection;Roads;Vision-based
日期:	2009
上傳時間:	2010-04-07 13:27:23 (UTC+0)
出版者:	Asia University
摘要:	Some of the well-known fuzzy clustering algorithms are based on Euclidean distance function, which can only be used to detect spherical structural clusters. Gustafson-Kessel (GK) clustering algorithm and Gath- Geva (GG) clustering algorithm were developed to detect non-spherical structural clusters. However, GK algorithm needs added constraint of fuzzy covariance matrix, GK algorithm can only be used for the data with multivariate Gaussian distribution. A Fuzzy C-Means algorithm based on Mahalanobis distance (FCM-M) was proposed by our previous work to improve those limitations of GG and GK algorithms, but it is not stable enough when some of its covariance matrices are not equal. In this paper, A improved Fuzzy C-Means algorithm based on a Common Mahalanobis distance (FCM-CM) is proposed The experimental results of three real data sets show that the performance of our proposed FCM-CM algorithm is better than those of the FCM, GG, GK and FCM-M algorithms. © 2009 Old City Publishing, Inc.
關聯:	IEEE Transactions on Industrial Electronics 56(5):1757-1773
顯示於類別:	[資訊工程學系] 期刊論文

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