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作物病害圖像中重疊病斑分離算法
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    摘要:

    針對(duì)傳統(tǒng)的分水嶺分割算法的不足,,應(yīng)用了一種基于標(biāo)記測(cè)地重建的分水嶺算法對(duì)棉花重疊病斑圖像進(jìn)行分離,。首先對(duì)病斑二值圖像利用多尺度距離變換獲得病斑的距離圖像,,通過(guò)極限腐蝕操作檢測(cè)出標(biāo)記種子,;然后以種子標(biāo)記為基礎(chǔ),,運(yùn)用形態(tài)學(xué)測(cè)地重建運(yùn)算獲取測(cè)地影響區(qū)骨架SKIZ——分水嶺線,;最后利用分水嶺線與原病斑圖像進(jìn)行交集運(yùn)算,,從而得到分離的圖像,。運(yùn)用該算法對(duì)棉花重疊病斑圖像進(jìn)行分離,,試驗(yàn)結(jié)果表明:該方法能較好地將圖像中的重疊病斑分離,,并較好地保存病斑邊緣信息,對(duì)圖像中的微小結(jié)構(gòu)和噪聲不敏感,具有良好的魯棒性,。

    Abstract:

    For accurately isolating the overlapping spots in crop disease images, an improved watershed algorithm named marker-reconstruction watershed algorithm was presented. Firstly, the binary spots image was transformed to distance image by multi-scale distance transform operator and makers (seed) were detected by using ultimate erosion. Then, geodesic SKIZ (i.e., watershed division lines) has been obtained by geodesic reconstruction operator constrained by marking seed image. Finally, the watershed division lines were subtracted from the original binary image. Applying the proposed method in cotton disease images, the experimental results indicated that the method could validly and effectively separate overlapping spots in the image, moreover, preferably protect the spots edge. This method is insensitive to noise and tiny outlier of the image.

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張艷誠(chéng),毛罕平,胡波,李明喜.作物病害圖像中重疊病斑分離算法[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2008,39(2):112-115.[J]. Transactions of the Chinese Society for Agricultural Machinery,2008,39(2):112-115.

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