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

基于改進(jìn)型C—V模型的植物病斑圖像分割
作者:
作者單位:

作者簡(jiǎn)介:

通訊作者:

中圖分類(lèi)號(hào):

基金項(xiàng)目:

國(guó)家自然科學(xué)基金資助項(xiàng)目(60975007、61001100、61003151)


Segmentation of Plant Lesion Image Using Improved C—V Model
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 圖/表
  • |
  • 訪(fǎng)問(wèn)統(tǒng)計(jì)
  • |
  • 參考文獻(xiàn)
  • |
  • 相似文獻(xiàn)
  • |
  • 引證文獻(xiàn)
  • |
  • 資源附件
  • |
  • 文章評(píng)論
    摘要:

    針對(duì)植物病斑圖像背景復(fù)雜且分割難問(wèn)題,提出一種基于水平集和加權(quán)顏色信息的C—V模型。借助水平集方法對(duì)病斑圖像的R、G、B分量圖像顏色信息取加權(quán)值,以差分圖像能量作為能量函數(shù)最終值,以適應(yīng)不同的病害種類(lèi)。試驗(yàn)結(jié)果表明,經(jīng)過(guò)R、G、B加權(quán)的黃瓜紅粉病病斑圖像使用4R—G圖像模型、蘋(píng)果銹病病斑圖像使用3R—G—B圖像模型自動(dòng)分割的效果較好,比傳統(tǒng)C—V模型分割性能好,抗噪性好,可擴(kuò)展性好。

    Abstract:

    In view of complex background of lesion images and the difficulty in segmentation, an improved C—V model based on level set and weighted color information was proposed and applied into agricultural lesion image segmentation. The segmentation model of weighted color information based on level set was suitable to different diseases identification and could identify lesion disease automatically. Experimental results show that the proposed model has better property than C—V model, and has many advantages such as anti-noise and scalability properties on 4R—G image model for cucumber pink and 3R—G—B image model for apple rust disease.

    參考文獻(xiàn)
    相似文獻(xiàn)
    引證文獻(xiàn)
引用本文

胡秋霞,田杰,何東健,寧紀(jì)鋒.基于改進(jìn)型C—V模型的植物病斑圖像分割[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2012,43(5):157-161. Hu Qiuxia, Tian Jie, He Dongjian, Ning Jifeng. Segmentation of Plant Lesion Image Using Improved C—V Model[J]. Transactions of the Chinese Society for Agricultural Machinery,2012,43(5):157-161.

復(fù)制
分享
文章指標(biāo)
  • 點(diǎn)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(xiàn)發(fā)布日期: 2012-06-07
  • 出版日期: