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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/115539

    题名: Real-Time Textureless Object Detection and Recognition Based on an Edge-Based Hierarchical Template Matching Algorithm
    作者: Tsai, Chi-Yi;Yu, Chao-Chun
    关键词: Textureless Object Detection;Textureless Object Recognition;Template Matching;Pose Identification, Line2D Algorithm
    日期: 2018-05-31
    上传时间: 2018-11-08 12:11:10 (UTC+8)
    摘要: Textureless object recognition is a difficult task in computer vision because the object-ofinterest
    (OOI) may not have enough texture information for extracting object features. To address this
    problem, this paper presents a textureless object recognition method based on the existing Line2D
    algorithm. The proposed method employs an edge-based hierarchical template matching method to
    detect and identify a wide variety of textureless objects. Given a reference template image of an OOI, a
    hierarchical edge-template database containing different 2D poses of the OOI was firstly created by
    applying affine transformation with different rotating and scaling settings to the reference template
    image. Next, an edge-based template matching process is performed to detect and recognize the OOI
    by searching matches between the hierarchical edge-template database and the input image. Finally,
    the position and angle posture of the OOI can be determined by the best match having the highest
    similarity measure. Experimental results show that the proposed method not only can efficiently
    recognize the type, quantity, position, and angle information of various textureless objects in the
    image, but also can achieve real-time performance about 24 frames per second (fps) in processing
    640x480 images. Therefore, the proposed algorithm has the potential to be used in many computer
    vision applications.
    關聯: Journal of Applied Science and Engineering 21(2), p.229-240
    DOI: 10.6180/jase.201806_21(2).0011
    显示于类别:[電機工程學系暨研究所] 期刊論文


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