English  |  正體中文  |  简体中文  |  Items with full text/Total items : 94286/110023 (86%)
Visitors : 21691117      Online Users : 422
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version
    ASIA unversity > 資訊學院 > 資訊工程學系 > 期刊論文 >  Item 310904400/8690


    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/8690


    Title: Dynamic calibration and occlusion handling algorithms for lane tracking
    Authors: Wu, Bing-Fei;Lin, Chuan-Tsai;Chen, Yen-Lin
    Contributors: Department of Computer Science and Information Engineering
    Keywords: 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
    Date: 2009
    Issue Date: 2010-04-07 13:27:23 (UTC+0)
    Publisher: Asia University
    Abstract: 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.
    Relation: IEEE Transactions on Industrial Electronics 56(5):1757-1773
    Appears in Collections:[資訊工程學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    0KbUnknown262View/Open
    405.doc38KbMicrosoft Word341View/Open


    All items in ASIAIR are protected by copyright, with all rights reserved.

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback