English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 71463/104422 (68%)
造訪人次 : 19148143      線上人數 : 260
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    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

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    413-418.pdf634KbAdobe PDF29檢視/開啟


    在政大典藏中所有的資料項目都受到原著作權保護.


    社群 sharing

    著作權政策宣告
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回饋