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    ASIA unversity > 管理學院 > 經營管理學系  > 會議論文 >  Item 310904400/8816

    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/8816

    Title: Design a support vector machine-based intelligent system for vehicle driving safety warning
    Authors: Lin, Che-Chung;Lin, Chi-Wei;Huang, Dau-Chen;Chen, Yung-Hsin
    Contributors: Department of Business Administration
    Keywords: Automobile parts and equipment;Edge detection;Estimation;Hough transforms;Image retrieval;Integrated circuits;Intelligent systems;Intelligent vehicle highway systems;Machine design;Vehicle locating systems;Adjustment mechanisms;Appearance-based;Camera calibrations;Computing power;Detection ranges;Distance estimations;Driving safeties;DSP-based;Dual cores;Edge enhancements;Feature-based;Forward collision warnings;Lane departure warnings;Long hauls;Median filters;Motion vectors;Region of interests;System features;Vanishing points
    Date: 2008
    Issue Date: 2010-04-08 20:16:20 (UTC+8)
    Publisher: Asia University
    Abstract: This paper reports the advancement of a research extension. The outcome is a device installed in a long-haul bus for daily operation. The incumbent system features the combination of Lane Departure Warning (LDW) function and Forward Collision Warning (FCW) function employing the Support Vector Machine (SVM) as the classifier. LDW recognizes the environment as in daytime or in nighttime by detecting a vanishing point and applies the appropriate thresholds for daytime and nighttime to enhance the detecting rate. The algorithmic components of LDW function include image overlapping, median filter, edge-enhancement filter and Hough Transform, while the FCW function identifies vehicles with a feature-based approach and verifies the vehicle candidates by the appearance-based approach. In addition, we propose a new detecting scheme by motion vector (MV) estimation, where the detection doesn't rely on the whole image inside the region of interest (ROI) but on the detection range of three different ranges to concurrently secure high detecting rate and low computing power. Besides, as distance estimation is the crucial part of FCW function, we create an innovative camera calibration algorithm working with an adjustment mechanism to enhance the accuracy of the distance estimation. The combination of refined LDW and FCW functions has successfully implemented in ADI-BF561 600MHz dual core DSP-based embedded system. © 2008 IEEE.
    Relation: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC:938 - 943
    Appears in Collections:[經營管理學系 ] 會議論文

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