English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 80990/80990 (100%)
造訪人次 : 41144862      線上人數 : 420
RC Version 7.0 © 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


    請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/26826


    題名: A novel hybrid approach based on sub-pattern technique and whitened PCA for face recognition
    作者: Hsieh,PC;Tung,PC
    貢獻者: 機械工程研究所
    關鍵詞: COMPONENT ANALYSIS
    日期: 2009
    上傳時間: 2010-06-29 18:01:09 (UTC+8)
    出版者: 中央大學
    摘要: Recently, in a task of face recognition, some researchers presented that independent component analysis (ICA) Architecture I involves a vertically centered principal component analysis (PCA) process (PCA 1) and ICA Architecture II involves a whitened horizontally centered PCA process (PCA II). They also concluded that the performance of ICA strongly depends on its involved PCA process. This means that the computationally expensive ICA projection is unnecessary for further process and involved PCA process of ICA, whether PCA I or II, can be used directly for face recognition. But these approaches only consider the global information of face images. Some local information may be ignored. Therefore, in this paper, the sub-pattern technique was combined with PCA I and PCA II, respectively, for face recognition. In other words, two new different sub-pattern based whitened PCA approaches (which are called Sp-PCA I and Sp-PCA II, respectively) were performed and compared with PCA I, PCA II, PCA, and sub-pattern based PCA (SpPCA). Then, we find that sub-pattern technique is useful to PCA I but not to PCA II and PCA. Simultaneously, we also discussed what causes this result in this paper. At last, by simultaneously considering global and local information of face images. we developed a novel hybrid approach which combines PCA II and Sp-PCA I for face recognition. The experimental results reveal that the proposed novel hybrid approach has better recognition performance than that obtained using other traditional methods. (C) 2008 Elsevier Ltd. All rights reserved.
    關聯: PATTERN RECOGNITION
    顯示於類別:[機械工程研究所] 期刊論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML748檢視/開啟


    在NCUIR中所有的資料項目都受到原著作權保護.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明