亚洲一区欧美在线,日韩欧美视频免费观看,色戒的三场床戏分别是在几段,欧美日韩国产在线人成

基于凹點搜索的重疊果實定位檢測算法研究
作者:
作者單位:

作者簡介:

通訊作者:

中圖分類號:

基金項目:

國家高技術研究發(fā)展計劃(863計劃)資助項目(2006AA10Z259)


Detection and Location Algorithm for Overlapped Fruits Based on Concave Spots Searching
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 圖/表
  • |
  • 訪問統(tǒng)計
  • |
  • 參考文獻
  • |
  • 相似文獻
  • |
  • 引證文獻
  • |
  • 資源附件
  • |
  • 文章評論
    摘要:

    為了能夠快速準確地計算出生長狀態(tài)為靠攏或重疊的成熟類圓果實的形心坐標和半徑,提出了一種基于凹點搜索的快速定位和檢測重疊果實目標的方法。利用色調分量的統(tǒng)計規(guī)律實現(xiàn)背景分離,采用鏈碼跟蹤法獲得單像素果實輪廓,并按步長獲取邊緣特征點;然后利用N點方向編碼差獲取邊緣凹點,確定凹點群,根據閾值確定分割凹點;最后利用改進的Hough變換計算出多個重疊桃子的形心坐標和半徑。研究結果表明,本文算法速度快,果實正確識別率最高可達90.0%,形心和半徑誤差均小于7%。

    Abstract:

    In order to calculate centric coordinates and radius of quasicircular ripe fruits whose growing state was approached or overlapped, a kind of fast location and detection method for fruits object based on concave spots searching was proposed. After the object was segmented from background with hue according to statistical law, the freeman chain code algorithm was used to extract onepixel fruit contour, from which the edge character points were abstracted. Then the edge concave spots which were found by direction coding difference of N points were divided into several concave spot groups, and the segmentation concave spots were located by the threshold. At last, the centric coordinates and radius of several overlapped peaches were calculated based on optimized circular Hough transform. The research results showed that the proposed method had rapid speed, the highest obtainable right recognition rate was 90.0%, and the error rate of centric points and radius was below 7%. 

    參考文獻
    相似文獻
    引證文獻
引用本文

謝忠紅,姬長英,郭小清,朱淑鑫.基于凹點搜索的重疊果實定位檢測算法研究[J].農業(yè)機械學報,2011,42(12):191-196. Xie Zhonghong,Ji Changying,Guo Xiaoqing,Zhu Shuxin. Detection and Location Algorithm for Overlapped Fruits Based on Concave Spots Searching[J]. Transactions of the Chinese Society for Agricultural Machinery,2011,42(12):191-196.

復制
分享
文章指標
  • 點擊次數(shù):
  • 下載次數(shù):
  • HTML閱讀次數(shù):
  • 引用次數(shù):
歷史
  • 收稿日期:
  • 最后修改日期:
  • 錄用日期:
  • 在線發(fā)布日期: 2011-12-19
  • 出版日期:
文章二維碼