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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/103466

    作者: Hsieh, Ching-Tang;Tsai, Han-Yi;Huang, Hsieh-Chang;Yeh, Cheng-Hsiang;Chen, Li-Ming
    贡献者: Dep. of Electrical Engineering, Tamkang University
    关键词: Obstacle Detection, Kinect, Depth Image
    日期: 2015-07-18
    上传时间: 2015-07-27 13:58:55 (UTC+8)
    出版者: Academy of Taiwan Information Systems Research (ATISR)
    摘要: This study proposes an obstacle detection method based on depth information to aid
    the visually impaired people in avoiding obstacles as they move in an unfamiliar
    environment. Firstly, we have applied dilation of morphology and erosion of
    morphology to remove the crushing noise of the depth image and have used the Least
    Squares Method (LSM) in a quadratic polynomial to approximate floor curves and
    determine the floor height threshold in the V-disparity. Secondly, we have searched
    for dramatic changes depth value in accordance with the floor height threshold to find
    out suspicious stair edge points. Thirdly, we have used the Hough Transform to find
    out the location of the drop line. In order to strengthen the characteristics of the
    different objects to overcome the drawbacks of the region growing method, we have
    applied edge detection to remove the edge. Fourthly, we have used the floor height
    threshold and features of the ground to remove ground plane. And then our system has
    used the region growing method to label the tags on different objects. It has analyzed
    each object to determine whether the object is a stair. Fifthly, if the result is neither up
    stair nor down stair, we have used K-SVD algorithm to determine whether the object
    is people. Finally, the system has assisted the users to determine the stairs direction
    and obstacle distance through a voice prompt by Text To Speech (TTS). Experimental
    results show that the proposed system has great robustness and convenience.
    關聯: International Conference on Internet Studies
    显示于类别:[電機工程學系暨研究所] 會議論文


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