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    政大機構典藏 > 理學院 > 資訊科學系 > 期刊論文 >  Item 140.119/110587
    請使用永久網址來引用或連結此文件: http://nccur.lib.nccu.edu.tw/handle/140.119/110587

    題名: A Lightweight Feature Descriptor Using Directional Edge Maps
    作者: 廖文宏
    貢獻者: 資科系
    關鍵詞: directional edge maps ; local feature descriptor ; object detection ; robot vision
    日期: 2014
    上傳時間: 2017-06-29 09:45:59 (UTC+8)
    摘要: The objective of this research is to design a lightweight object detection and recognition engine that requires less space, less power and smaller budget than its PC counterparts. Specifically, we develop novel feature extraction algorithms to take ad-vantage of fixed-point arithmetic. The newly defined descriptor, known as directional edge maps (DEM), can be computed using simple addition/subtraction operations. DEMs are employed as locally invariant features to represent objects of interest. When combined with a modified AdaBoost classifier, the system can be trained to detect and recognize objects of various types. The performance of the proposed descriptor in several object recognition problems are examined and compared in terms of accuracy and efficiency against local binary descriptors (LBP) and Haar-like features.
    關聯: Journal of the Chinese Society of Mechanical Engineers(中國機械工程學刊), 35(5), 413-418
    資料類型: article
    顯示於類別:[資訊科學系] 期刊論文


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